Guest Posts Archives - Ģý. /blog/category/guest-posts/ Powering Personalisation Thu, 15 Jan 2026 17:11:14 +0000 en-GB hourly 1 https://wordpress.org/?v=7.1.3 /wp-content/uploads/2019/01/YST-LOGO_MASTER_BLUE_DARK_GREY_32.png Guest Posts Archives - Ģý. /blog/category/guest-posts/ 32 32 Smart Travel Planning for Bradford City of Culture /blog/bradford_city_of_culture Tue, 08 Jul 2025 13:06:05 +0000 /?p=43915 The post Smart Travel Planning for Bradford City of Culture appeared first on Ģý..

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Bradford 2025: UK City of Culture

Bradford 2025, a major cultural programme and the UK’s City of Culture initiative, is successfully leveraging smart travel planning tools to enhance visitor experience and encourage sustainable transport choices. As of mid-May 2025, over 10,000 travel plan queries have been processed, reflecting robust engagement and an appetite for digital journey support tools.

Deployment and Technology

A multi-layered digital deployment integrates web and mobile access, offering users automated, personalised low-carbon travel plans. The technology supports bespoke routing to key venues and integrates real-time information, making journey planning seamless and intuitive. Travel plans are automatically emailed to every ticket booker, ensuring consistent user access.

Sustainable Travel and Modal Shift

Travel planning data revealed balanced transport mode preferences—each with roughly 40% share between public transport and driving. For RISE specifically, public transport usage was higher at 43.5%, aligning with planners’ goals to nudge audiences toward greener travel modes. Cycling journey uptake was also identified as a successful element of the programme.

Impact and Engagement

  • Engagement Rates: 23% of all ticket holders and 62% of booking groups engaged with the travel planning tools
  • Ticketing & Reach: 43,709 tickets sold across 16,174 orders
  • Event-Specific Highlights: The RISE opening events saw over 4,000 travel plans generated, covering 20% of attendees

Key Successes

  • Broad and effective digital deployment
  • High engagement with automated personalised travel plans
  • Improved access to cycling and multi-modal journey options
  • Strong public sentiment and positive digital feedback
  • Cross-stakeholder data collaboration and insight sharing

Opportunities for Growth

Looking ahead to rest of the year, Bradford 2025 aims to:

  • Optimise transport for key events in the programme
  • Enhance volunteer and staff travel engagement
  • Improve communication through earlier and repeated travel plan emails
  • Increase sustainable transport uptake through targeted messaging and incentives
  • Collaborate further with local authorities and transport partners

 

Bradford 2025 is proving how data-driven, personalised travel planning can transform the visitor experience while promoting sustainable and inclusive mobility. The programme’s ongoing success illustrates a replicable model for future large-scale events.

Photography by Karol Wyszynski.

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]]> La Nature du Tour de France /blog/la_nature_du_tour_de_france Thu, 10 Apr 2025 12:57:04 +0000 /?p=43321 The post La Nature du Tour de France appeared first on Ģý..

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Hidden Footprint of ‘Low-Carbon’ Sports in Climate Action

Many of the world’s most popular participation sports – running, cycling, etc., are seemingly, in of themselves, environmentally sustainable. Cycling is a particularly intriguing example – doubling up as a sport and arguably the most sustainable practical form of travel. As an activity, cycling is totally carbon-neutral once you take away the production emissions associated with equipment production and food for fuelling the ride. However, when it comes to staging a major cycling event, the carbon footprint is alarming and, in many cases, a reducible impact.

Personal Perspective: The Cyclist’s Carbon Footprint

As an ex-professional cyclist myself, I was deeply concerned with my personal carbon footprint whilst competing; with most months of the year spent travelling from race to race, training camp to training camp, all simultaneously dotted around the world, most often with the only option to reach them being a return flight.

This is the inevitable footprint of professional sport. You are paid to perform over races across the world day in day out, meaning fast, simple travel from place to place. There is certainly room to improve the way in which professional athletes, cyclists in particular, travel – but for the most part this is dictated by the team themselves who decide where and how an athlete is going.

What can be influenced more easily, however, is spectator travel. That is what we’ll be diving a little deeper into in this post.

The Tour de France: A Major Environmental Impact

The Tour de France is the world’s most watched sporting event, attracting 3.5-4 billion viewers annually, with at least 12 million spectating on the side of the road. At a glance the event is a low-carbon spectacle – the world’s best 180 cyclists racing distances of 150-250km daily for 23 days across the best bits of France. Many of these kilometres pass particularly vital and fragile landscapes – such as the rapidly melting glaciers of the Alpes, helping to highlight the importance of environmental protection. And whilst professional cycling isn’t riding a bike for the sake of transport, it is encouraging people to get fitter, healthier and engage in active travel – the positive knock-on effects of this cannot be denied.

Tour de France

The Hidden Environmental Footprint of the Tour

Unfortunately, however, it’s not just bikes. The Tour de France is accompanied by many hundreds of vehicles, going the same distance as the riders or longer, each day. This includes the iconic promotional ‘Caravan’ (which involves an hour-long cavalcade of customised event transport akin to whacky races), at the very least three or four team cars, coaches and various race-specific buses and lorries to not only move the thousands of people working on the event, but the enormous level of infrastructure involved. Then add the coverage aeroplanes and television helicopters, and you have an astonishing environmental impact, even before spectators get involved. Combine this with spectator travel, which can account for up to 80% of the Tour’s carbon footprint, and we witness one of the most carbon-intensive sports events on the planet. The irony is profound.

How Can the Carbon Footprint Be Reduced?

So: how is this avoidable? The answer sits, in equal measures, in the hands of event organisers and spectators. Event organisers can empower and enable spectators and participants to make more sustainable travel choices – in turn, spectators can make the most of sustainable travel advice and incentives by choosing lower-carbon transport. But giving spectators practical and achievable travel options in an event like this is easier said than done.

With a large portion of key destinations and viewing hotspots being in rural and remote areas, void of established public transport links, many rely on their cars to get from A to B whilst watching the race. Most spectators travelling from different countries or continents at the Tour thus fly and hire a car once arriving in France.

Sustainable Travel Solutions: The Role of ‘Ģý.’ and Crowd Distribution

Solutions such as the Ģýý.’ travel demand management platform and travel assistant are well suited to overcome these challenges, especially when integrated with event-specific travel, like spectator shuttle buses. Although encouraging spectators to arrive in France as sustainably as possible is key, ideally without flying, it’s the provision of solutions and services for those travelling domestically to race stages that stands out as the biggest opportunity to influence and nudge travel choices. This would significantly reduce emissions and lessen the strain on the organisation and crowd management side of the Tour de France. It is a notable missing piece in the Tour de France’s large decarbonisation puzzle.

Example of integrated shuttlebus option for Anthropy 25 at The Eden Project

Crowd distribution is key for this. The Tour can lean on ‘attract and disperse methodologies’ used by popular rural tourist destinations. Instead of crowds all travelling to and gathering at the most popular race points, the Tour can promote other lesser-known viewing areas to help disperse the spectators across each race stage’s route. This strategy reduces over-crowding and lessens the need for extensive travel to congested points, improving spectator experience and the overall logistics of the race.

Decarbonising the Tour de France Fleet

It’s also high time that the Tour de France takes the necessary steps to decarbonise its fleet of vehicles. Does it need that many? If so, how can it ensure that all of them are electric and using clean energy? Tackling the carbon footprint of mass participation events, with their unique complexity of multiple route diversions, dynamic and specific timings across different stages, with often multiple, dispersed spectator viewing points in a single day, sometimes day after day, is perhaps a niche challenge. But we can’t solve the climate emergency in one go.

A Global Challenge and Opportunity

There are over 6000 major, spectator-attracting, mass participation sporting events globally each year attracting tens of millions of participants, and a global audience approaching or exceeding 1 billion annually. What is undeniable, is that these events have the power to influence behaviour change in our everyday lives. Purpose driven innovations such as Ģýý.’, with its configurable multimodal routing and personalised travel advice, are designed to and catalyse this potential impact.

As an iconic world-leading event the Tour de France is uniquely positioned to harness and integrate low-carbon technologies and practices, leading by example on how it can dramatically reduce its carbon footprint, and become a conduit for the sustainability that is integral to its nature.

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]]> Taking Control /blog/taking-control Sun, 12 Jan 2025 21:23:22 +0000 /?p=43070 The post Taking Control appeared first on Ģý..

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How the Public Sector is Using Next Generation Travel Demand Management to Boost Public Transport, Reduce Costs, & Achieve Decarbonisation

Hosted by ‘Ģý.’ this webinar took place in January 2025

Watch Below

An insightful webinar that explores regional smart travel partnerships between local authorities, venues, and events, showcasing how next generation travel demand management is enhancing network reach and passenger engagement. Learn how all local authorities can replicate this success with localised digital tools that drive greater use of public transport, delivering new revenues and reducing car dependencies. Discover strategies to accelerate decarbonisation and operational efficiency whilst increasing ridership, and that most importantly, safeguard critical transport services.

Alongside a compelling agenda delivered by senior transport executives, the webinar includes a demonstration of Transport for Greater Manchester’s deployment of ‘Ģý.’ across the region’s Bee Network, followed by a moderated Q&A session.

To book an online session that focuses on the specific priorities of your local area, please click here.

Alternatively, to arrange a face-to-face stakeholder workshop, raise any direct questions or questions for the speakers that we can pass on, please email: client.development@yousmartthing.com

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]]> Directions for an Audience of One /blog/audience-of-one Sun, 05 Jan 2025 15:30:10 +0000 /?p=42964 The post Directions for an Audience of One appeared first on Ģý..

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Will Phillipson, chairman of travel demand management platform Ģýý.’ (YST), hails a new generation of personalised travel planning.

For those wanting to attract visitors to destinations, venues, or events, the title of this post may at first appear counter intuitive, but there is a new paradigm evolving in travel planning that can significantly improve visitor experience, for individuals, and for destinations as a whole.

An Audience of One

The way I see things is the world works in patterns. If you can identify the pattern, you can predict how things will generally progress. If you can apply a pattern to a new industry or sector, you can innovate.

Years ago, the publishing industry began to digitise, moving from analog printing presses and physical typesetting to digital imaging and laser printers or digital presses. In parallel with this transformation, there was a realisation that the industry economics were changing in a way that enabled shorter runs and targeted publications. In other words, digitisation eliminated the huge upfront cost of typesetting – setting up physical type in a press for imprinting on paper.

Desktop publishing, scanning technology, high speed printers, and high-speed networks all came together to introduce ‘Print on Demand’ as a concept – the idea that a book could be printed and delivered to a customer at the point they chose to purchase it, rather than in advance, thus saving on inventory, warehousing, and even transportation costs.

This concept further evolved to ‘Audience of One’ – the idea that a customised publication could be assembled, printed, and delivered for an individual customer. This was revolutionary – the idea that some of or all of the content and even the advertising, could be made bespoke and unique for each customer was never possible at scale before.

Of course, today, we take this for granted. Content is delivered mostly online instead of printed, and dynamic web pages are common; targeted advertising is everywhere; and ‘personalisation’ is what every marketer is pursuing.

A New Generation of Personalised Travel Planning

The travel planning industry seems to have followed much of the same pattern as publishing: we started with offline, paper maps. Some may remember mapping out a trip – taking a highlighter to the map to trace the route and circling points of interest or places to stay enroute. Then came MapQuest, which provided automation of the routing, and allowing one to print out pages and pages of turn-by-turn directions. Yahoo and then Google followed with improved mapping. Waze introduced another paradigm shift – not only mobile – but also dynamic, in that it would update its routing recommendation with real-time traffic and congestion data. This was a huge change that brought a new level of relevance to on-the-go navigation.

Typically, major paradigm changes require complete rethinking and rebuilding of the technology stack – a time consuming and expensive proposition. This is why so many companies fail to jump paradigms – the cost and effort associated with making the rebuild, often at the expense of the existing business, is too high for them to embrace. Google acquired Waze to accelerate their adoption of this paradigm, and Apple has taken many years to achieve parity in its travel planning and navigation services.

What excited me about Ģýý.’ when I was introduced to the company, was that it appears to me to be yet another paradigm shift – another leap forward in concept and technology. Let me explain:

YST does three things differently from existing travel planning products. First, it’s contextual – or even hyper contextual. Second, routes can be prioritised by the destination’s environmental and commercial objectives. Third, it is by-directionally dynamic, as opposed to Waze’s one-way dynamicism, sharing rich data and actionable insights between visitor experience stakeholders.

What this Means for Destinations, Venues, and Events

Every trip you take has a context. You’re going somewhere for a reason. For example, to a concert, or a football match, or a trade show. On Google or Apple maps, your last or first mile instructions to or from the specified location would be the same regardless of your purpose. Moreover, you’d be routed to or from the same point near or at the periphery of the green or grey destination blob on the map, regardless of modal choice, time of day, direction of approach, carbon footprint, ticket or registration type, and any special mobilty requirements.

YST, by contrast, works with the venue managers and event organisers to personalise directions based on all these criteria. YST also works with the transit providers, parking services, and local authorities to understand the broader services in place to support customers getting to a specified destination, venue, or event. Therefore, YST can route you to the appropriate park-and-ride location followed by event specific transit, getting you to the event with the least fuss and stress. YST understands the context of the event – are there optimal transport interchanges, directions, and access points for different ticket types, or separate entrances for supporters of different football teams, and if so, which one should you be routed to? Does that routing entail different public transit considerations, helping to keep opposing teams from using the same metro, tube, or rail lines or stations? All this information is contextual and affects the individuals’ specific travel experience. YST uses it to generate personalised travel plans that are unique to each individual ticket holder or visitor.

But once you have your travel plan, YST is not done! Bi-directional dynamicism, means that YST continues to work with destination, venue, and event stakeholders to help them optimise their services in line with demand. Organisers can access insights into customer journey behaviour, enabling them to more efficiently deploy resources – add or remove transit services; increase or decrease entrance gate operations and staff; manage dwell time to maximise food and beverage sales; even design the efficient positioning of security staff. Its synchronous system of dynamic supply and demand can be implemented for specific events and at scale, to load balance transit networks by socio-economic and environmental objectives. And of course, as these services and schedules change, customers are updated, and directions are adjusted to support a smooth experience.

The pattern I see replaying itself here is simple. Google and Apple and Waze have digitized the navigation experience, even making it dynamic and mobile. However, YST is drilling down on the context, personalising travel planning, not only for the visitor and the venue, but for the purpose of each specific trip. Ģýý.’ provides directions for an ‘Audience of One’, and in so doing, is optimising destination, venue, and event access for everyone.

______________

Will Philipson will be speaking at Taking Control, 22/01/25, a ‘Ģý.’ webinar exploring how the public sector is using next generation travel demand management to boost public transport, reduce costs, and achieve decarbonisation.

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]]> Sustainable Venues /blog/going_green_for_your_events Fri, 29 Nov 2024 16:24:31 +0000 /?p=42990 The post Sustainable Venues appeared first on Ģý..

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Going Green for Your Events

In today’s world, where the environmental impact of every industry is under increasing scrutiny, event organisers have a responsibility to make a top priority. The choices we make when planning events, from the to the , can significantly affect the environment.

Choosing a is a key step towards minimising that footprint, ensuring that gatherings—whether for conferences, or —don’t come at the expense of the planet. ‘Ģý.’ (YST) have welcomed the team at , the UK’s leading venue-sourcing marketplace, to bring you five standout London venues that are leading the way in sustainability, showing that eco-conscious events can be both stylish and impactful.

Why Going Green is Essential in Events

The urgency of addressing climate change is undeniable. Global temperatures continue to rise, ecosystems are under immense pressure, and industries are being called upon to reduce their carbon footprints. The events industry, often overlooked in environmental discussions, is a significant contributor to resource consumption, waste, and greenhouse gas emissions. From large conferences to small , events can produce substantial amounts of waste, including energy consumption, water usage, food waste, and travel-related carbon emissions.

in events goes far beyond eliminating plastic straws and single-use cutlery. It’s about rethinking every aspect of an event, from the choice of venue to the energy sources that power it, production, suppliers and even the travel options for attendees. For instance, venues powered by renewable energy can greatly reduce carbon emissions, while sustainable food sourcing such as using local suppliers and having more meat-free options, can lessen the environmental impact of catering.

Our Top Green Venue Picks

When it comes to finding the perfect venue for an eco-friendly event, it’s essential to choose spaces that prioritise sustainability. This is a great way to start your sustainable journey at the core. Let’s not forget the all-important location, choosing a venue that is in close proximity to public transport links is key to reducing the impact of delegate travel.

As venue experts, we at Hire Space have carefully curated a selection of venues committed to reducing their environmental impact and ideally located, making it easier to plan a green event and letting you focus on other valuable sustainable goals. Let’s dive right in.

1. BMA House

seamlessly blends charm with a strong commitment to sustainability, making it an ideal choice for eco-conscious events. Located in central London, this Grade II listed venue has woven sustainability into its core operations, ensuring that it meets the needs of modern event planners prioritising environmental responsibility. From its zero-to-landfill policy, where waste is recycled, composted or repurposed, to its use of 100% renewable energy, BMA House takes a comprehensive approach to reducing its environmental footprint.

Location:Euston

2. Barbican Centre

is a leading venue in London’s arts and events landscape, renowned for its strong commitment to sustainability. As a hub for conferences, and cultural gatherings, the Barbican is at the forefront of eco-friendly event spaces, aiming to achieve net-zero carbon emissions by 2027. The venue has introduced a host of sustainable practices, such as energy-efficient lighting, water conservation systems and comprehensive waste recycling initiatives, ensuring minimal environmental impact. A standout feature for event organisers is the Barbican’s partnership with local and sustainable food suppliers, offering organic and fair-trade catering options, making it a top choice for eco-conscious events.

Location: Barbican

3. RSA House

is an exceptional venue for events, offering both elegance and sustainability in the heart of London. Known for its forward-thinking approach, the venue is powered by 100% renewable energy, making it a great choice for eco-conscious conferences, meetings and corporate gatherings. With over 90% of its waste recycled and food leftovers composted, RSA House is committed to responsible waste management. Its event catering is equally impressive, featuring seasonal, locally sourced produce that supports sustainable dining. For organisers looking to reduce their event’s carbon footprint, RSA House promotes low-carbon travel options for attendees and offers sustainable event packages, aligning your event with ethical practices.

Location: Charing Cross

4. The Brewery

, a renowned venue in central London, takes its (CSR) seriously, with sustainability being a core focus. It actively reduces its carbon footprint by using 100% renewable energy and strives to reduce waste through a comprehensive recycling and composting programme. The Brewery also supports sustainable travel options, encouraging clients to choose eco-friendly transport. This historic venue also focuses on local sourcing, ensuring that event catering is both sustainable and delicious, making it a great choice for eco-conscious event planners.

Location:Moorgate

5. Church House Westminster

is a leading venue for sustainable events, integrating eco-friendly practices into every aspect of its operations. Perfect for conferences, corporate meetings and , the venue runs entirely on 100% renewable electricity and uses efficient heating and cooling systems to minimise energy consumption. With a zero-to-landfill waste policy, Church House excels in waste management while also supporting local biodiversity, thanks to its proximity to Westminster’s green spaces. The venue also goes a step further by offering clients expert advice on how to reduce their event’s carbon footprint, from sustainable catering options to eco-friendly transport solutions.

Location:Westminster

in the events industry is not just a trend, it is a necessity for protecting our planet and setting your business up for long-term success. such as those listed, are leading examples of how environmental responsibility can be successfully integrated into event planning. As more venues adopt sustainable practices, event planners have the opportunity—and the responsibility—to make choices that align with global environmental goals much more easily. It’s all about doing what you can, wherever you can and starting with your venues is a great way to start.

To find out more about sustainability in events, check out our sustainability hub

Ready to go green for your next event? Explore the best sustainable venues on and make your event truly stand out while supporting a greener future.

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]]> Travel Insights, Q4 2022 /blog/low-carbon-travel-insights-q4-2022/ Sun, 18 Dec 2022 10:31:43 +0000 /?p=40787 The post Travel Insights, Q4 2022 appeared first on Ģý..

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Walking the Green Line

Amid the irony of international dignitaries busting the world’s carbon emissions budget by jetting around the world to talk about the climate change emergency, and the controversy around the environmental legacy of the World Cup, ‘Ģý.’ continues to work with destinations, venues, and events to address sustainability, and the cost-of-living crisis, by nudging people into better travel habits.

Flights are of course an ongoing challenge. Electrification perhaps presents light on the horizon for the aviation industry, supply-chain challenges, the sheer weight of batteries and the physics of propulsion notwithstanding. Sadly, the sector is deeply invested in combustible fuels, and replacing 747’s and A330’s, still in production, with long-distance autonomous electric passenger jets is a major transformation programme that will take years. I’ve reachedout to Elon with a plan to accelerate this and will keep you posted on ourprogress!

In the meantime, small changes, at scale, are our only hope of getting anywhere near to our net-zero targets. “But can’t we just offset?”, I hear you say. Well sorry, but that’s a bit of a COP out. (Excuse the pun!)

Sure, we should embrace the carefully managed removal of emissions that can’t be avoided. Though costly, there are biodiverse technologies that actually sequester carbon from the atmosphere in a reasonable timeframe, rather than buying a random field and planting monocrops that will die out before having any effect whatsoever. The more efficient approach, however, where possible, is undoubtedly behaviour change. And we’ve proved that is it possible, in more places and for more events than you might imagine.

So how do we move people? Motivation requires emotional as well as physical engagement, which typically comes down to marketing.

We’ve done it before. When I grew up (during the 80’s) few people considered recycling. Now it’s the norm. General waste here, plastics and bottles there. I urge those old enough to think back to when we introduced that messaging, and the tech that supported it… bins with different coloured lids! I urge those young enough to think forward, beyond 2050… will you say, “Remember when they used to talk about the climate change emergency?” or “They’ve been talking about the climate change emergency for years, and we’re still making things worse!”

Walking the green line, in budgeting terms, is of course tricky to say the least. With global energy supply challenges almost all organisations with any form of physical presence are faced with hugely increased costs.

Energy is both the cause and the effect.Common sense (and medical science) tells us that active travel and shared journeys improve wellbeing. They also dramatically reduce cost, and our collective carbon footprint. So, what are we waiting for? The problem is that Scope 3 emissions – externalities predominantly generated by visitor travel, and that represent the vast majority of an organisation’s carbon footprint – are considered beyond the control of the destinations, venues and events that cause them, yet this is where the sphere of influence is greatest in terms of motivating behaviour change. At least, emissions from visitor travel were considered beyond the control of destinations, venues, and events, until now.

Local authorities, major events, festivals, Destination Management Organisations, business and retail parks, health and education campuses, and smaller venues are all using our travel demand management technology to plan and provide better access to places, some remote and underserved by public transport networks. They have configured our intuitive online visitor-facing travel assistant to optimise data capture, people flow, dwell time and revenue generation, offering content-enhanced wayfinding and curated low-carbon door-to-door travel plans that nudge visitors towards more sustainable travel.

I hope you find our blog and travel insights posts valuable, and we look forward to working with you into 2023 and beyond!

Warm regards,

Chris

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]]> Getting a Little Headspace During the Pandemic /blog/getting-a-little-headspace-during-the-pandemic/ Mon, 16 Nov 2020 09:56:46 +0000 /?p=28699 The post Getting a Little Headspace During the Pandemic appeared first on Ģý..

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Ģý., Somerset House, Birmingham UK

On behalf of Headspace Group, Edward Smith for Highbury Communications interviewed Chris Thompson about YSTs decision to champion the workplace over working from home full time.

Inthe midst of a second lockdown, how can businesses navigate a safe return to the office once this is over?

As we navigate a second national lockdown, it’s a nervous time for business owners and their employees. Aside from the obvious health and safety concerns that we all share, how will businesses be affected by the prolonged uncertainty around all things Covid-related? And when will we be able to get back to a more normal working environment? For me, that second point is particularly important. The government came under some criticism for its back and forth over the previous ‘return to work’ campaign, so this time around it’s crucial this is managed in the right way. But, by working more closely with workspace providers, and better utilising some of the tools available to us, it is certainly possible to facilitate a safe return to work when the time is right. This would benefit employees, businesses and the wider economy.

The coronavirus pandemic triggered a social experiment in home working – on a scale never seen before. From Twitter offering their staff ‘work from home’ (WFH) as a permanent option, to major PLCs revaluating the tens of millions they spend on real estate each year, it has been a catalyst for major change.

Yet for many businesses, despite some of the benefits of home working, it is far from the ideal. Andy Haldane, the Bank of England’s Chief Economist recently argued that working from home can starve businesses of many of the ‘raw ingredients’ that act as a ‘key source of creative spark’. These include the serendipitous conversations, meetings or environments that trigger ideas.

As the CEO of a fast-growing tech business, I echo Andy’s thoughts. ‘Ģý.’ (YST), offers tech enabled travel management and assistance. We’re a digital platform and our best ideas are the result of teamwork and collaboration. Whilst flexibility is important for us, as a team we value our time in the office together and we get a lot of energy and inspiration from the space we work in. We chose to base ourselves at in central Birmingham because for that very reason – it’s a beautiful, inspiring space and we work alongside lots of other like-minded, interesting and ambitious businesses. I also believe that our working environment is really important from a mental health and wellbeing perspective. I could see the negative impact on my staff during lockdown. WFH is far from an equal playing field.

As the government considers our exit strategy from this second lockdown, how can it avoid the confusion of the previous ‘back to work’ messaging, and help get businesses back into the workspace safely?

Workspace providers have a key role to play. In our experience, coming back into the office in August was a really positive process. From developing a rota system, to working with Headspace Group to reconfigure our office, a raft of new processes were put in place (increased health and safety audits, new levels of cleaning and sanitisation regimes, a greater engagement on general wellbeing, certifications around air quality) to minimise the risks. Headspace undertook a lot of work to ensure the space was Covid-secure, whilst at the same time offering the flexibility to tenants to use the space as it suited them.

Simultaneously, the Government and employers could be better utilising data to further reduce the risk. YST’s own technologyallows for advance planning, staff management and risk mitigation. We use data to help organisations, and their clients/customers/visitors, plan travel in a way that is safe, efficient and socially distant (e.g.suggesting trips to destinations by different transport modes and delivering detailed real-time info and forecast travel demand by venue or event). The easily embedded Travel Assistant plugin for websites or apps allows for advance planning, staff/visitor management and risk mitigation and is applicable to everything from the workplace, education, healthcare and retail to accelerating the recovery of our cultural sector.

We are already working with Transport for West Midlands and the Department for Digital, Culture, Media and Sport to help accelerate the region’s recovery from Covid-19. Understanding demand for our rail and road networks and integrating them more effectively with last-mile routes to destinations, without creating pinch-points and bottlenecks, is a critical tool in helping to rebuild the economy, whilst ensuring public safety.

In many ways, the West Midlands is already leading the way with this, and the same approach could be applied – hand in hand with the efforts of workspace providers – to help get workers back into the office safely.

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]]> iLIDS Research Part 2 /blog/ilids-research-part-2/ Thu, 30 Aug 2018 15:42:25 +0000 http://206.189.16.4/?p=9645 The post iLIDS Research Part 2 appeared first on Ģý..

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Exploiting the powerof smart object recognition

‘iLIDS’ stands for ‘Interactive Locations and Intelligent Digital Signage’. It is part of the Department for Transport’s£9mInnovate UK ‘Accelerating Innovation in Rail’ programme under which Enable iD,The Rail Safety and Standards Board (RSSB), Arriva UK Trains and researchpartners the University of Surreyare researching, developing and testing new technology to improve information, safety andaccessibility on railway station platforms.

Overview

The main motivation for the final project was the original iLIDS requirement to detect the presence of wheelchair users, bicycles, people with luggage/prams to alert staff of potential passengers who might have assistance needs as well as offering intelligent lighting or display solutions which would provide personalised information to these groups of passengers.

Another aspect was to carry out the processing of this information in as much a privacy-preserving manner as possible.

 

Approach

The first part of the project was to ensure that any data from the camera was sent over an encrypted channel. To limit the bandwidth required the receiver could control how much data was sent by the data feed, eg it could request just a single frame or the whole video stream. The client-server architecture of the image transfer application is shown in Figure 4.

Figure 4: Client-Server Architecture of the Video feed

Once the server has received the image, it is passed to the Object Recognition Application. The algorithm was developed to be run such that it could be run on a CPU-only server as well as take advantage of GPU acceleration if a supported graphics card was available.

The object recognition algorithm used was YOLO v3 [3]which was chosen for its claimed speed and accuracy as shown in Figure 5

Figure 5: YOLOv3 performance (from [3])

The application then reported the detected objects and associated confidence levels on a website to illustrate the output generated. The following image is an example output that the program generated:

Figure 6: Sample output of Object Recognition Algorithm

The final part of the project was to use Intel’s Software Guard Extensions (SGX) to protect the processing of the images on an untrusted host (eg a server provided by a cloud provider).SGX is a technology which allows programs to be executed in encrypted areas of memory (enclaves) to protect their data (and code) from the underlying operating system. It promises to provide a secure environment even if the underlying platform is untrusted.

Prototype Evaluation

The following table shows the performance (measured and interpolated) of the object detection algorithm (values with a question mark are estimations):

CPU-ONLY (SINGLE THREAD) CPU-ONLY (MULTIPLE THREADS) CPU-WITH SGX ENABLED (SINGLE THREAD) CPU WITH SGX AND MULTIPLE READING GPU ACCELERATED
Full version of YOLOv3 8000ms 2400ms 87500ms? 26000ms? 30ms
Tiny version of YOLOv3 750ms 300ms 8200ms 3250ms? 5ms

Table 1: Performance of Object Recognition Algorithm (CPU i7-4790@4GHz, GPU: Nvidia GTX 980ti)

The tiny version of YOLOv3 is a simpler model which is less accurate but can be run in memory and processor-constrained environments like mobile phones. The reason why it was included was due to the current memory restrictions on SGX enclaves which limit them to 128Mb of memory but can use more using paging. The tiny version of YOLOv3 requires only 38Mb of data to initialise the model while the full version requires over 240Mb. The actual memory consumption is even higher so that even the tiny version of YOLOv3 required paging to run in the SGX enclave. Note that this explains the poor performance using SGX as the processor constantly needed to swap memory in and out of the enclave during the running of the program.

Nevertheless, the prototype proved that object recognition can be carried out on at reasonable speeds using the tiny version of YOLOv3 even on CPU only servers while a GPU accelerated version is several magnitudes faster.

For the problem of detecting specific objects or number of people on a platform, the algorithm only needs to process an image every few seconds as the objects in questions are likely to be reasonably stationary for a considerable amount of time. As such even the CPU the only version of YOLOv3 could be sufficient (especially the tiny version).

Conclusion and Future Work

The main outcome of this project was to demonstrate the feasibility of processing image data in a secure environment using Intel’s SGX and to establish a performance baseline. Apart from improving the performance, one interesting research direction is to investigate whether the security guarantees of the enclave withstand side-channel attacks, especially when memory needs to get constantly swapped in and out of an enclave as was the case with our set-up.

About – Surry Centre for Cybersecurity

Surry centre of cybersecurity is one of the17 Academic Centres of Excellence in Cyber Security Research (ACEs-CSR)recognised by the UKNational Cyber Security Centre(NCSC)in partnership with theEngineering and Physical Sciences Research Council (EPSRC).

Surry focuses on “Security by Design”, with particular expertise in trusted systems, privacy and authentication, secure communications, and multimedia security and forensics, with human dimensions in security as a cross-cutting theme. We have a strong ethos of applying theory into practice, and the application domains we work in include transportation (automotive, rail), democracy (e-voting), telecommunications, digital economy, and law enforcement.

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]]> iLIDS Research – Part 1 /blog/ilids-research-part-1/ Sat, 30 Jun 2018 16:09:54 +0000 http://206.189.16.4/?p=9623 The post iLIDS Research – Part 1 appeared first on Ģý..

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Capturing and sharing accurate train consist information:

‘iLIDS’ stands for ‘Interactive Locations and Intelligent Digital Signage’. It is part of the Department for Transport’s£9mInnovate UK ‘Accelerating Innovation in Rail’ programme under which Enable iD,The Rail Safety and Standards Board (RSSB), Arriva UK Trains and researchpartners the University of Surreyare researching, developing and testing new technology to improve information, safety andaccessibility on railway station platforms.

Background to the Research

This summer project continued the train consist work that was started as part of the RSSB funded competition “Faster, Safer, Better Boarding and Alighting”. As part of the original project ““, the University of Surrey project team was responsible for producing a prototype application to demonstrate the feasibility of determining the train consist using a low-cost IoT device, in this case, an Orange Pi (). The main issue was the reliability and accuracy of the obtained data which was about 60%. The relative low accuracy was due to only one IoT device being deployed which resulted in some missed coaches for fast- moving trains or additional coaches being reported when two trains passed each other when travelling past the device. An additional drawback of the original solution was the requirement for mains power and availability of an internet connection provided by a 3G mobile modem.

Since the iLIDS project is highly dependent on accurate train consist data being available, one way of addressing this data need is to provide it as part of the overall solution at stations which deploy the iLIDS solution. The summer project aimed to provide a more accurate, cheaper and mobile network-independent solution to the train consist problem.

 

Existing Approach

In the original approach, the following diagram summarised the different components:

Figure 1: Train consist architecture

The scanning device (an Orange PI running Android and some bespoke scanning software developed for the project) would scan for known Service Set IDentifiers(SSIDs), eg “_Chiltern-wifi” or “GWR WiFi” and look for the Media Access Control(MAC) address of the corresponding Access Point(AP). This MAC address together with some metadata (eg date/time, signal strength) is then sent via the mobile network to a web service. This web service then uses the provided information to map it to a serial number of the coach in which the AP is installed. The serial number which is unique is then used to determine the facilities available by consulting the Rolling Stock library. The signal strength and timestamps associated with the various MAC addresses are used to provide an estimate for the train consist which was then visualised on a web page:

 

Figure 2: Visualisation of Train Consist

While almost all (95%) vehicles with modern WIFI hardware were picked up, due to just using one scanner, only 60% of consists were accurately calculated in real-time. Another drawback of the prototype was its reliance of mobile networks to provide internet access and, due to its power consumption, a requirement for at least a USB-port providing around 500mA.

 

New Approach

The following areas needed to be addressed:

1. Accuracy

2. Dependency on mobile network

3. Dependency on a power supply

The last 2 aspects were addressed by switching from a high-specification IoT device like the Orange PI to a simpler device like the PyCom IoT device (). These devices are designed to be low-powered and are supposed to run for months or even years on a battery. Moreover, they offer WIFI scanning as well as being able to join or create (if necessary) a Low-Power Wide Area Network (LPWAN) which uses unlicensed spectrum to transmit their data. The distances that can be covered range from a few kilometres ( in urban areas) to 40 or more kilometres in rural areas.

Since these devices do not need to transmit any data other than their WIFI scans, the speed limitation of the LPWAN is less of a concern.

The accuracy of the scanned data is improved by deploying multiple scanners sufficiently far enough apart to ensure that multiple trains passing a sensor are unlikely to still be passing each other at the next sensor.

The following diagram shows the deployment of the two sensors and an LPWAN gateway on our campus :

Figure 3: LoPy Sensor and gateway deployment

The sensors were placed alongside the rail track of the Guildford<->Reading and Guildford<->Ascot trains. The first sensor was placed furthest away from Guildford station and could only “see” the 2 tracks going passed it. The second sensor was placed closer to Guildford station and actually “overlooked” not only the Reading/Ascot track but also some additional tracks used by the London and Portsmouth bound trains.

The LoPy Sensors formed their own LPWAN network by sending their data to a nano gateway (provided by an additional LoPy IoT device which was configured to act as a gateway, ie it was connected to the internet and transmitted the received data to the web service for further analysis). This nano gateway was placed inside the Duke of Kent building. The distances between it and the furthest sensors were about 250m. The university also runs its own LoRa gateway but that was unfortunately unavailable over the summer.

 

Challenges

Moving from a powerful platform (Orange Pi) to the lower specified PyCom board brought several challenges that needed to be overcome. The main challenges included:

  • The default WIFI scanning rate of the PyCom boards is limited to about one scan every 4s which resulted in poor performance as the train carriages passed too quickly for all the APs to be picked up. This required a modification of the firmware to reduce the scan cycle to a more reasonable 300ms.
  • The number of potential WIFI channels is 13 for the 802 b/g/n/a WIFI standard and if they were all used then cycling through them would require almost 5s. However, the trains in questions were using only a limited number of channels (1,6 and 11). Consequently, the software limited its scanning to those channels and thereby reducing the scan time for these 3 channels to about 1s.
  • Due to the nature of the LPWAN LoRa network, the devices are limited in how much data they can send and therefore each device performed some initial analysis on their captured data and only submitted a reduced data set which contained its version of the train consist. The server-side would then use this information and attempt to resolve any conflicts or ambiguities.
  • The initial plan was to connect to an existing LoRa gateway operated on the University of Surrey’s campus. Unfortunately, this gateway was out of operation during the whole of the summer and meant that the project needed to use the PyCom boards and operate its own “nano” gateway. This meant that the LPWAN LoRa network coverage was limited to about 250m line of sight rather than the expected 1 to 30km. However, it demonstrated that even when there is no existing LoRa network coverage, it can be provided by simply using one or more PyCom boards to work as nano gateways.

 

Outcomes

Having 2 sensors provided the desired boost in accuracy. The sensors were able to determine correctly the direction of travel using the time stamps of when the APs passed the sensor. Moreover, crossing trains could be disambiguated using these multiple sensors.

Unfortunately, while the PyCom boards were battery-powered, their power consumption has not yet been captured precisely. Moreover, there are additional power optimisations that can be made to ensure that the boards minimise their power consumption when no trains are passing.

 

Conclusion and Future Work

The summer project proved that moving to the PyCom boards addressed most of the shortcomings of the original architecture: accuracy, reliance on mobile networks and main power supply.

However, more data will need to be captured to improve the accuracy further and hopefully, the trial at MCO will provide the opportunity. Additionally, the power consumption of these devices needs to be established to determine how long they can operate on one battery charge and whether small solar panels should be fitted to top up the battery during the day.

The summer interns presented their work to representatives of RDG who were very keen to explore the use of this technology further and potentially use the data produced as a feed into their Connecting Train Identifier project which aims to provide train consist data as part of the Darwin feed.

Author

Petar Zdravkov, born and raised in Bulgaria, is a Computer Science student at the University of Surrey, currently doing his placement year in one of the world`s biggest agrochemical companies, working as a Software Developer in the company`s UK based R&D site.

From a talented artist with numerous awards from national art competitions, Petar changes his life-aspiration, from working as a 3D animation and graphics specialist to becoming a computer scientist. Being raised in a farmer`s home and his lifelong experience in agriculture production, helps him find his area of interest, more specific – digitalizing agricultural processes which allows him to focus on multiple areas of such as AI & Deep learning, Mobile and Web Applications development, as well as electrical engineering.

Petar gets his first IT job only after a year in university, despite having no previous knowledge or skills in programming or electrical engineering prior to the beginning of his study. At the end of his second year of study, he is recruited by the University of Surrey as a research assistant, working alongside his friend and classmate Emil Georgiev, on proving that reliable data about train consists can be obtained in real-time using low-powered wi-fi scanning devices. During his participation in the project, he successfully delivers a working prototype of a web-application, capable of extracting data collected by multiple devices from an IoT cloud server, validating the data sets and representing the final train consists sequences.

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]]> Engineering Change /blog/engineering-change/ Fri, 09 Sep 2016 16:29:57 +0000 http://206.189.16.4/?p=2561 The post Engineering Change appeared first on Ģý..

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The Socioeconomics of the Internet of Things

Pictured: Adam Smith, 1723 – 1790. Argued for free trade, market competition and the morality of private enterprise.

Between studies, whilst temping at Enable Software (), I was tasked with writing this blog article. Whilst experienced enough in writing artciels, I was at first unaware of the finer details of the ‘Internet of Things’ (IoT), even if I was still confident I had a relatively good grasp of the concept.

After much research I feel I now have more right to speak on the subject. So what follows is a look over the impact which the emergence of the Internet of Things will have, at a socioeconomic level. I examine impacts for people, industry and for government, as well as the issue of rising data storage and usage and the fine line between what is your private information and what is not. I’ve briefly outlined the uses and concept of IoT throughout, as much for my own benefit as for those who perhaps aren’t fully aware of it.

The Internet of What?

The Internet of Things, a vast network of ‘devices’ connected to the web, spawning private and personal information aimed at revolutionising the way we live our lives. The IoT purports to provide users with a clear and concise method of studying both the mental and physical aspects of their own health, in parallel with connecting entire city infrastructures to improve a wide range of public services. From ‘wearables’ such as Apple’s iWatch and the Fitbit personal exercise monitor, to sensors measuring temperature, traffic congestion and Co2 emissions, numbers of Internet connected devices have been expanding steadily in recent years. Ericsson says it expects IoT sensors and devices to exceed mobile phones as the largest category of connected devices in 2018. Gartner forecasts 20.8 billon connected devices by 2020 and McKinsey projects annual revenue growth of 32.6%, reaching an IoT market valuation of $3.7 billion in the same period.

The more one studies the application and proliferation of the Internet of Things the more the numbers stack up. It is quietly transforming the way the average person lives their life as well as shaping methods used by governments to monitor their citizen’s welfare, and the process with which markets and companies engage consumers. It seems the IoT is as much about observing and changing human behaviour, on an individual level and at scale, as it is about little black boxes or shiny new technology.

As a humanities strudent I’m truly no technology expert, I really have very little authority to speak on the technical side of IoT so I’ll stick to the basic uses and principles as an outline, then look more in depth at its usefulness to society, the implications of its widespread introduction, and people’s thoughts and fears about such technology.

At the moment I am an undergraduate of Economics and Politics. Studying these combined subjects and their intertwining relationship between governments, business and the general public is fascinating to me, which is why IoT’s widespread and mainstream introduction is of such interest. Beyond just being innovative and a step-change in the use of the internet, the Internet of Things is set to become a tool that bonds differing aspects of society together.

Having been brought up in a digital era as well as being of an age which is targeted heavily by establishments who are part of this technological revolution, I can see that the socioeconomic impact of the Internet of Things will likely have great influence upon my life those around me. Uses will range from affecting the way I go about my day, to my health and well-being as well as my consumer interests and the way companies target me. From a layman’s perspective I can see the cost-benefit to corporate enterprise alongside the IoT’s effect on the everyday person, in the case of the latter, externalities (unintended effects) that can evidently be both positive and negative.

The Business Case for IoT

From an economic viewpoint, in my opinion the IoT ticks all the boxes. It is capable of increasing efficiency for society, business and government; indeed, many towns and cities around the world are implementing Internet of Things frameworks to create so called ‘smart cities’. From South Korea to Capetown and Tokyo to Torronto, large-scale IoT networks are seen as a viable and economical tool. Transportation has been adapted to meet modern needs through various IoT inspired solutions, Enable iD’s ‘MyJrny’ intelligent mobility platform is one of them, aimed at improving travel through deeper integration with local information and services that compliment people’s journeys. I’ll look at this example again shortly. My focus however lies upon the wider benefits initiatives such as this can deliver.

Smart city IoT developments exhibit how organisations and regional government authority bodies have been working together to benefit the citizens. The main economic argument for this cooperation is the potential for improved efficiency seen as a result. The UK Government Chief Scientific Advisor, Sir Mark Walport, cites IoT as “the second digital revolution”, highlighting transport, energy, healthcare, agriculture and buildings as sectors best placed to take advantage of its’ real-time data in order to streamline operational activities. Whilst improving transport systems and reducing lateness or even the stress of travel evidences a granular benefit to people’s private lives, as acknowledges, at scale one can begin to measure the impact on wider society and correlate cause and effect between a vast range of political, environmental and socioeconomic factors.

This type of cooperation between industries and the public sector is perhaps then vital to furthering society. While market economists such as Adam Smith and Milton Friedman may have argued that free-trade competition inherently improves efficiency, it seems smart city IoT ‘cooperations’ that match the public sector’s regulatory and compliance challenges with private sector capability and drive for shareholders returns, can yield wider social benefits for individuals whilst also satisfying enterprise. This and arguably produces greater socioeconomic benefits for all. Indeed the ‘shared resource – shared economy’ business models of companies such as Uber and Air B&B could not have been realised without state sponsored licensing combined with the free market economy. IoT provides the catalyst for these conditions through the interconnectivity of regulation and real-time supply and demand.

(in) Security

The potential benefits to business are clearly significant, technology gurus and investors could no doubt talk for days about the inner workings and how firms could potentially increase in size ten-fold, but fundamentally none of this matters if IoT doesn’t work for me and you. We need to benefit clearly and in a user friendly way. Essentially, if the individuals benefit then IoT-based services will most likely be a roaring success in the near future. However, my concern is that if society doesn’t have the feeling that all our information is safe and secure then IoT will not reach its full potential. It’s a point of view shared by Ireland’s Minister for European Affairs, EU Digital Single Market & Data Protection, Dara Murphy, in his forward to the Government Data Forum’s ‘’ report:

“…Smart Cities bring huge potential benefits in producing more efficient, productive, sustainable, resilient, transparent, fair and equitable cities. We need to ensure that we carve a path that allows us to harness these benefits while at the same time, ensuring that we do not compromise data privacy, data protection or data security.”

Security is clearly a defining factor and we should all be mindful of it when connecting any ‘thing’ to the Internet, body, car, home or workplace!

On the positive side IoT appears set to connect relationships together in a cohesive and simplistic way, both within your private life and in terms of your relationship with the business world. The possibilities for this in terms of efficiency and ease of access to the market rewards both the user and the business. While the greater link between private and commercial life may worry some, this seems set to be advantageous. Simplicity of booking tickets online for instance; as is a focus of ‘MyJrny’, a connection between those tickets and alternative routes or methods of transport represents a more efficient system and positive socio-economic effect. Other similar examples have also been demonstrated in a magnitude of apps based upon using systems such as HAT (Hub-of-All-Things) and IFTTT (If This Then That), both platforms that focus largely on making daily tasks automatic and simple through better technology.

The subsequent personal data generated, beyond just the hardware and intended utility, also has its uses in socio-economic terms. It provides ‘insight’ that enables businesses to better tailor services to an individual’s needs, creating mutual benefit. The frictionless generation of customer data and information, which emerges as a bi-product of an IoT driven service, can drive down companies’ data-capture and customer profiling costs at the same time as generating increased revenue through personalised offers and higher sales conversion.

Privacy by Design

Aside from the economics and security of the Internet of Things, socially the progression in data generation can benefit all of us, sharing our information across databases so that it can be queried in order make our lives that much better. Enable iD focuses on doing this in a secure way, maintaining anonymity and protecting individuals’ privacy.

IoT systems designed to enhance services through personalisation are being used in environmentally friendly energy and water systems built in homes. They are currently most notable in the form of ‘smart’ thermostats such as Nest and Hive. They’re built to enable out-of-home control, track usage and nudge us with tips on becoming more efficient, as well as automatically becoming more cost effective.

Health has also seen innovations due to IoT and the storage of patient’s data. For example ‘fall detection’ apps exist in care homes for the elderly and disabled, assisting those affected as well as carers. Further to this, sports scientists see the benefit of IoT in monitoring progress and vital signs on sports fields and during training, a practice that has potential to boost health and wellbeing within the community. And by and large it’s down to whether or not we allow our data to be shared with third party organisations.

Of course the implementation of the Internet of Things does generate more debate and discussion around the idea of privacy, and what privacy law actually entitles us to in our lifetime. A major fear of many is the potential for IoT technologies to analyse and share data between machines, abstracted from human intervention. This autonomous sharing of ‘artificial intelligence’, across little black boxes and computer server farms collectively termed ‘the cloud’, inevitably raises questions about those who write the rules for controlling and utilising such sensitive and private information. Given the shared infrastructure of the web, even with best intentions, what level of control is it actually possible to implement? The idea of ‘the robots taking over’ (or least being managed by a select few) will no doubt have an impact on the acceptance of IoT-based services.

While security and privacy issues won’t put off all users, with many simply accepting the subsequent growth of personal data storage we are already seeing, a significant number may withhold consent. The world’s largest technical professional organization, The Institute of Electrical and Electronics Engineers (IEEE), states in its recent that, “users need to be able to give informed consent to data collection”. Users, however, have limited time and technical knowledge to become ‘informed’. In many cases I fear this factor of imperfect or incomplete information will result in people giving away their personal information without understanding the risks involved, or how their information may be stored and used and stored. Where consent may be given, it will not necessarily be ‘informed’.

Don’t Believe the Hype

Whilst the Internet of Things is fantastic in technical terms, socially public fears may hold back its development and economic impact.

The media undoubtedly plays a key role in influencing people’s views. Unfortunately the big stories most commonly foster scaremongering and fear, the idea that technology and those who preside over it cannot be trusted. Perhaps IoT’s biggest problem is that with the current debate around how governments and big business use private information, it plays into journalists’ hands in terms of its potential for invasion of privacy, leaks and hacking. If a company that utilises IoT were to sell sensitive information to a third party on the black market, for example, then the whole idea of interconnected services could fail for everyone. Hopefully, for the most part would not be the case. Most companies do have corporate social responsibility in respect of both employees and customers enshrined in their founding articles of association. The success of IoT does however rely upon business and government being able to proactively act on these principals and implement social responsibility in order for people to gain trust in their systems.

If individuals trust their data is secure, will not be hacked or sold, development of the Internet of Things and its associated real-time information could create an almost un-paralleled economic impact and positive shift in the way we live everyday life. To achieve this the hype around IoT and Big Data needs to be demystified and understood by users just as it does but by those implementing the technology, and those reporting in it. The potential economic gain should be seen as an incentive to ensure the public is fully aware of all aspects of IoT and personalised data usage. This awareness campaign could perhaps start with a greater focus personal identity and how technology can influence it, throughout our education system.

The Future

Over the next decade the entire landscape of data storage and public opinion on data security may change. The Inernet of Things looks, by my reckoning, to be socio-economically beneficial, but the question remains as to how large or small the benefit will be.

Make information readily available and technically simple to the average person and IoT may take off at greater speed, personal data may increase ten-fold and everyone may win from this. Failing that, personal data and the free flow of private information may remain a terrifying idea to some, or worse, a terrifying relaity. With these positions acknowleged I belive the emergence of the Internet of Things is both socially and economically necessary for growth in the modern age, set hopefully to be advantageous to all. If cities benefit, governments benefit, businesses benefit and importantly you benefit, surly that is a net socioeconic effect worth engineering.

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]]> The HAT, IoT & the Cloud /blog/the-hat-iot-the-cloud/ Thu, 24 Sep 2015 11:40:26 +0000 http://206.189.16.4/?p=1546 Original article published onHub of All Things. It’s commonly stated that individuals: a) don’t know...

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]]> Original article published on.

It’s commonly stated that individuals: a) don’t know what their personal data is worth, and b) give it up in exchange for “free” services, which then are powered economically by the value of the large amount of user data in terms of targeted advertising, marketing recommendations, analytics, and so forth. This is the famous two-sided market.In a similar way, the Internet of Things (IoT) has largely evolved a collection of services that often appear to be free, but in fact make this same trade-off. Hence, smart metering for utilities empowers the electricity-generating and grid companies to optimise their price/performance better, just as Tesco’s Clubcard allows the supermarket group to optimise its range and quality of goods.

What is currently somewhat different in the IoT world from the cloud world is that each of the services in the different IoT sectors is separate and exists in a silo. Hence, you cannot (easily) connect information between your smart meter, your home security management, your environmental control, your home and in-car entertainment systems, your fitness and wellbeing monitoring and control, and your social media (email, messaging, diaries, etc).

Where all websites on the Internet are connected and possibly linked, and all e-mail systems (whether web mail or traditional) are in principle inter-working, the IoT world is not. In fact, an IoT is a collection of many disjointed networks of things, using the Internet to transfer sensor and actuator data to and from each IoT service sector’s cloud service, and offering, typically, only a remote web API to the user.

Does this sound familiar? It is actually pretty much like Facebook and Google Search, which are essentially monopolies in each of their respective sectors of social networks, and of search engines. Hence IoT is not so different at one level.

At another level however, it IS different, because no one is able to offer third-party integration of IoT services in the current structure. In other word, no one can become the Google Search+Analytics of Things. If someone could however, it might prove to be problematic in terms of risks to end-users.

Enter the HAT – the Hub of All Things.

At the top level, the HAT offers a, which works like many other exchanges; it’s a marketplace, like a currency exchange, for HAT data.

At the next level down are the actual HATs, of which there can be many. These are places where we unpick the silos and collect together all the data for a user or a set of users. A user’s data is stored in a personal cloud, possibly one personal cloud per person (i.e. 10 billion clouds worldwide, potentially) ideally, but can also be stored in a HAT, and certainly is mirrored (a copy kept) in the HAT.

 

Strong Privacy Guarantees

There can be privacy issues in dealing with personal data, and the HAT contracts to obey. We expect the HAT has no incentive to cheat because:

  1. The user can switch HATs as there may be millions of HAT providers (at least 100s per country – by analogy, there are 300 ISPs in the UK and changing ISP is trivial).
  2. The HATDeX contracts with all the HATs – if a given HAT breaks the rules, then the HATDeX can evict them.
  3. The HAT provider is remunerated by the user and may be paid for additional services by the HATDeX as well – they already make money, so greed is counter-productive.
  4. The HATs are certified – they can choose different technologies to implement privacy and other service policy rules, as innovation happens in that space (e.g. differential privacy might be replaced by zero-knowledge computations, which might get updated to use homomorphic encryption, as advances are made). Standards allow interworking betweenIoT silos, open IoT platforms and HATs and between HATs and the HATDeX.

The key to this is that the HAT project defines interfaces, APIs and schemas, as well as rights and obligations in terms of contracts, not detailed mechanism, so that developers can improve various aspects of the systems over time, without changing the relationships between stakeholders.

Of course, there could be data leakage. However, by distributing users over many HATs, which may be quite heterogenous in terms of hardware, software, location/jurisdiction, etc, the risk of massive data leakage is massively reduced. The incentive alignment design also means that the mission creep that is sometimes called “honest but curious” is not present, and the certification makes sure to reduce accidental or deliberate back doors.

This won’t prevent every problem. In particular, in a very large-scale data collection system like this, different HATs might not easily be able to detect someone carrying out queries across them to do re-linking. However, it isn’t clear why someone (outside of law enforcement) would do this, since they can do commercial cases for re-linking subject to rules through the HATDeX anyhow, and running arbitrage on an optimal market is (allegedly), a seriously losing proposition.

 

The Future of Cloud

New cloud technology is coming onstream that decreases the footprint of a VM (Virtual Machine) by about two orders of magnitude, allowing clouds to run on very small devices (home hubs, set-top boxes, as in the User Centric Networking (UCN, see) project) or even a phone or in very large numbers in traditional data centres, or both.

Cloud data can be mirrored for high availability between home, mobile, and data centre, also covering device theft or disaster recovery (similar to theapproach). The cost of running a cloud at this scale is cents – rather than dollars – per month. Who pays depends on the service model the user picks. It might cost a little eyeball time, or a little less privacy, or it might be bundled in a particular IoT sector’s price; if the user chooses to be part of a HAT that sells data (in a privacy-preserving way) on the HATDeX, then the resource payments are covered by profit.

The HAT project is forging a new social contract for users and business in the context of the IoT. By respecting privacy and the ownership of personal data, we can see new ways to create markets from new services which have hitherto been blocked by the walled gardens of Cloud Services in the Internet today. Instead, open innovation can be enabled by careful definition of the relationships between stakeholders in this brave new cyber-physical world.

For more on how the tech of the HAT works, read thewhich is currently open for consultation.

 

About the author:

Jon Crowcroft

Jon Crowcroft FRS is Marconi Professor of Communications Systems at the Cambridge Computer Laboratory, University of Cambridge. He has worked in the area of Internet support for multimedia communications for over 30 years.

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]]> Me, Inc. (as a HAT) /blog/me-inc-as-a-hat/ Mon, 03 Aug 2015 09:13:43 +0000 http://206.189.16.4/?p=1515 Original article published onHub of All Things. Today’s corporations use IT to be incredibly efficient...

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]]> Original article published on.

Today’s corporations use IT to be incredibly efficient and effective. There are IT systems for finance, accounting, inventory management, supply chains, material and enterprise resource planning. All the tools necessary for the corporation be viable and profitable amid constraints of regulation. Corporations hold vast amounts of data to achieve this; data about production, materials, inventory, data about customers. In fact, nothing can be achieved within the modern corporation today without data and information. The corporation is also able to buy digital services of all sorts to analyse, process and make decisions from the data, be it to sort out accounting systems to managing HR. Indeed, many corporations outsource and buy in capabilities that are not core to their competencies.

Today’s individuals also use IT to be efficient and effective. Aided by the Internet, www and our smartphones, we can organise our lives and our families, work from home, have information access at our fingertips. But in terms of computational capability, data and our ability to buy digital services, we are very far behind the corporation. Where they have data on inventory, we barely know what is in our cupboards and fridges. Where they can buy services that augment their abilities, we can just about buy a translator, maps, currency exchange. Where corporations can be omniscient through their devices and sensors, we can just about put up a camera to check on our house remotely.

 

BigDataImage: Jorge Cham,

The market doesn’t seem to work in our favour as individuals. More firms are coming into the digital space to share our data amongst one another, asking us for our permission to do so but the revenue models are usually ad-driven or worse, they sell our data, albeit anonymised, to other firms. We are starting to use our Facebook or Twitter identity data to sign on to other digital services and allowing Whatsapp or LinkedIn to tap into our contact list. Essentially, as more digital applications proliferate, the more we are being harvested for our data and the more we are being sold advertising. Two factors contribute to this:

  • First, we often place little value on our own data, and are prepared to sign it away for the simplest service e.g. the way we give away browser cookies to peruse a website. It is as though the corporations out there consider our data precious but because we don’t have any use of the data for ourselves, we have little regard for it.
  • Second, we also don’t have the computational or system capability to use our data. We don’t have a software platform that enables better wellbeing as well as integrating different data in the way that corporations do. Firms can buy software platforms for enterprise planning, organising and coordinating but we can’t. In addition, human beings use data quite differently from corporations. We cluster data and usage of objects according to our day-to day-contexts. Data from Tesco shopping, car journeys and school pickup are bundled together more meaningfully as a “mummy run” context compared to considering the data in the grocery, automotive and education vertical sectors.

So how do we square this?

 

The HAT Elevator Pitch

The Hub-of-All-Things (HAT) is a new kind of online data exchange, with you in control. HAT helps you easily capture and generate value from your data. It enables the collection and exchange of digital information, location and personal preferences, for work and leisure activities for example, for the mutual benefit of individuals, families, communities and organisations.

HAT creates a secure personal profile on the Internet, supported by a code of practice and regulated trust framework that enable control of data exploitation in a way that maximises its value to the individual. It saves you time and money by tailoring existing products and services based individual identity.

HAT providers are managed by , a consortium of public sector, academic research and industry partners, formed to champion the adoption and regulation of HAT technology.

 

Making Corporations Out Of Everyone

If corporations have so much computational powers and the ability to buy services, use data effectively and have rights to keep their own data private, then why don’t we just make a corporation out of everyone? Why can’t each person have a server identity, much like an online shop is a server? If our relationship with our host provider is the same type of relationship between Tesco and their server hosting provider, it would certainly be more equitable, as I assume that the host provider would not have a right to poke around Tesco’s data. More importantly, if I decide to change hosts, I can move all my data to a different host. Essentially, I can be my own ‘corporation’ with my own ‘personal resource planning’ platform with inventory of my stuff, data about my health, wellbeing, etc. In fact, HAT Platform Providers (HPPs) are already creating easy ways to buy apps to view, analyse, and organise my data.

As we begin the public release of the HAT in September, through HPPs, to experimental groups of users and later on to a wider community, I am mindful of the implications. We are essentially looking at potentially half a billion people being ‘corporatised’ in a way when they sign on to get their own HATs. And as they do so, they will be empowered to store, analyse and manage their data like they have never been able to do so before. More importantly, they will be able to speak to corporations ‘server-to-server’, API to API, leveraging on a legal framework that binds firm-to-firm relationships in far more equitable way than firm-to-consumer relationships. Some individuals may decide to bring emails back to their own server, since the ontology of the HAT schema flattens data and therefore can help combine email data with other data for better planning, searching and organising. It feels terribly powerful to have your own server, even if what you have to organise is only your own data. The platform will certainly be attractive to developers who can create better applications to help us view, analyse, track and organise our own data that could be combined with third party datasets for better matching or recommendation services.

The amazing thing about the HAT is that as a server, you can also share your data in a “peer-to-peer” manner. This means I can share my location on a realtime basis (e.g. My iPhone location data) with my husband so that when he opens his HAT enables applications, he can see my location that is shared with him and it’s no one’s business except ours. And the apps I buy to view, analyse and organise my data don’t have access to the data itself; it is akin to me buying a piece of software in the old days and installing it on a PC not connected to the Internet. But if I do want to share it, I can just create a data debit (which is the way all HAT data leaves the HAT) and share it with whomever I please. Such is the HAT. A personal resource planning system for the individual. Finally.

 

A Level Playing Field

Even as we release the HAT over the next six months, I have not missed the irony that the way we have engineered the personal data ecosystem to give control and empowerment back to the individual is to make us look like firms. Turning ourselves into a mirror image of the firm’s digital presence might finally get us respect and fair treatment, within the prevailing legal framework governing business-to-business relationships rather than being treated as passive consumers being harvested for our data. Perhaps. Wouldn’t it be funny to have Amazon concerned about their data being harvested when they come to the HAT platform to provide buying recommendations? But it’s ok. It’s all API to API, so everyone would share exactly what they are willing to share. Such is the equitability of a B2B system.

I believe we have one chance, and the timing is now, at the cusp when the two major industries of manufacturing is colliding with the Internet through the Internet-of-Things. It is now that we can jump in and introduce a system that brings back control to the individual, in a way that is innovation and economy-friendly. With HAT, firms, government and individuals can all work to reimagine the way we own and control our data to their mutual benefit.

What of democracy then? When HAT servers augment and amplify us are we able to interact with governments and firms on a more level playing field? Can we finally get more collective power as a society through better coordination, better collaborative consumption through a standardised platform that enablesours technology to interact whilst remaining uniquely personal to us as individuals with our own data? We wait to see. I have spent more than 20 years helping firms with value, worth, service and their business/economic models to generate more profits. Seems helping individuals to be ‘firm’-like could be a win-win for all with better control for individuals whilst helping create more jobs and greater opportunities in the digital economy.

Finally, I am also mindful of the divide between those who can afford an augmented and amplified self through a server and those who cannot, which could potentially create a bigger divide between the haves and have-nots. As such, the HAT will be available free of charge, up to a degree of storage and depending on who you choose as your HAT host, much like the www is free. Yet, the asset of our own HAT is to have more of our own data in it so that it can be leveraged for services and exchanges. If the wellbeing of society is at stake, then it is in our interest to ensure that everyone, young or old, rich or poor, be given a HAT. Fortunately, the entire ontology, schema and database of the HAT is open-sourced and free for anyone to innovate on. Although if you are a user and do not want to build your own software, you might prefer to just get it off a HAT platform host. In the UK, this would be through Enable iD and in Singapore, through . More HAT platform hosts are coming soon in other countries so do look out for them. And watch this space out for the HAT white paper on “Why Everyone Should Have a HAT: Implications for Government, Industry and Society”, soon to be released.

 

About the author:

Irene Ng, Professor of Marketing and Service Systems, WMG, University of Warwick

irenecropped2-208x300Irene is also the Director of the International Institute of Product and Service Innovation (IIPSI), and leads the Service Systems research group at WMG. Prior to joining academia in 2002, she was an entrepreneur for 16 years, and was Professor of Marketing at University of Exeter Business School before leaving for WMG in 2011. Specialising in new and disruptive methods of economic and business model innovation, Irene has written over 22 publications in top international journals in the area of value, service systems and new business models. An IO economist by training, her books includeĢý and Revenue Management of Services, Value and Worth: Creating New Markets in the Digital EconomyandComplex Engineering Service Systems. Irene has developed several mathematical algorithms leading to the successful commercialisation of products such as AXIOS (a service requirement software for customer perception of business model/contract attributes) purchased by Rolls-Royce and context pricing models within other business applications. She is an ESRC/AIM Services Fellow, ESRC/NIHR Placement Fellow, and a College Research Associate at Wolfson College, Cambridge with considerable experience in leading trans-disciplinary projects (involving more than £5m worth of both EPSRC and ESRC projects).

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]]> Does Context Matter? /blog/does-context-matter/ Tue, 30 Jun 2015 15:56:15 +0000 http://206.189.16.4/?p=1475 Using Big Data To Predict Consumer Choice: Consumer data is a valuable asset in the...

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]]> Using Big Data To Predict Consumer Choice:

Consumer data is a valuable asset in the current age of data with “smart things” (sensors) delivering large amounts of information to consumers and businesses. According to, in 2012 more than 2.5 exabytes (2.5 billion gigabytes) of data was generated daily.By 2015 this number has grown and, according to forecasts, will continue to grow to. Under these circumstances, businesses develop innovative techniques to extract and analyse data “on the fly” in order to create quick value propositions for the consumers. The availability of large masses of data catalyses the rise of the domain of data-driven business models (DDBM) which looks at how the data can be used in order to develop new and improve existing business modelling mechanisms.

Yet, the creation of meaningful analytical tools for DDBM is complicated not only because of the volume of the data but also because of the complexity of human decision processes and the way these processes are reflected in the data. Particularly, household consumption data shows that people who shop in the same store may opt for different products and/or brands of products. For example, when making grocery purchases, consumers often tend to alternate brands of products they choose. This is one of the reasons why current online systems developed by some providers such as, e.g., Amazon, which suggest products and services to users and which are intended tousers to purchase suggested services and goods, have not gained much popularity.

One of the main disadvantages of the currently available purchasing data is that even though it allows analysts to observe consumer choices as well as providing them with useful demographic information about consumers; it is hard to tell whether observed choices are a result of consumertruepreferences or merely a product of noise in these preferences. Analytics is particularly complicated for cases when consumers opt for products and services from different brands in different environments. Under these circumstances, it is important to not only pay attention to the models which help us analyse the data generated by consumer choices, but also to the types of data used for the analysis.

Not All Data Is The Same

Recent literature on servitization and business models provides some insights into this issue. Particularly, researchers tell us thatmaking a distinction betweencontent dataandmetadata. In consumer choice content data provides an account of decisions made by the users with regard to purchasing products or services. However, this data does not containinformation about the context in which these decisions were made. Content data includes Big Data and Connected Internet-of-Things (henceforth, IoT) Data as we know it. At the same time, metadata refers to the data which contains specific references to the context and gives an opportunity to understand how decision architecture (features of the decision environment) affects choices made by users. While content data is used to create technology-based servitization mechanisms, metadata places an individual consumer in the centre of the provision system where data is used as a service.

Predicting Brand Loyalty Using Content Data Versus Metadata

My recentlooks into how content and metadata can be used to predict brand loyalty and finds that information about contexts can provide important clues into consumer decision making. It turns out thatmetadata can generate better (more accurate) predictions of consumption behaviour than content data.

Using decision-theory, we can apply concepts of precise, noisy and imprecise preferences to brand choice and propose a simple mechanism which establishes the link between the preference type and brand loyalty.

Preference-Brand Loyalty Mechanism

Preference-brand Loyalty Mechanism

According to this mechanism, various offerings (products and services) can be divided into three categories:Green items;Yellow itemsandRed items.

Red itemsinclude offerings for which an individual has strong precise preference: if these are available, an individual would always prefer these offerings to any other offerings. This means that for these offerings an individual would have high brand loyalty. Figure below shows consumption pattern for the use of shampoo for 74 days of observation from behaviour of an actual consumer. The vertical axes shows remaining weight of the shower gel while the horizontal axes depicts the day of observation from 0 (first day of observation) to 73 (last day of observation). On the horizontal axes the data is arranged by week, where the first week of the study runs from 0 to 6 (7 days).

Yellow itemsinclude offerings for which an individual has strong preference but this preference may be in some contexts distorted by noise: an individual would have chosen these offerings over others every time they were available, but, due to fatigue, tremble error or more sophisticated mistakes, this individual may choose other options over the offerings he or she prefers. This means that an individual would often choose the same brand but choice of other brands may also be observed as in the example of the toothpaste consumption below:

Finally,Green itemsare a product of imprecise preferences: an individual will purchase offerings from different suppliers and the brand loyalty will be low. For example, shower gel consumption pattern below is consistent with theGreen item.

Using a case study, I tested the Preference-Brand Loyalty mechanism and found that metadata allows predicting brand loyalty better than content data. Using the “Beauty Box” sensor device, the data about weight of all shower products after each use was recorded in a household with two adults. In addition, study participants were also asked to write a detailed diary recording their purchasing behavior.

“Beauty Box” Prototype developed by Helen Oliver for the HAT project (Oliver, 2015)
“” Prototype developed byfor the

While sensor data provided content data, when combined with the diary records, we were able to generate metadata about consumption.

Why Does Metadata Allow Us To Generate Better Predictions?

Consider the following example from my study. Assume that we only observe content data from shower gel, shampoo and toothpaste consumption which looks like this over 74 days of observation (brand data is recorded using a bar code scanner embedded into the “Beauty Box”) :

Shower gel
Shower Gel
Shampoo
Shampoo
Toothpaste
Toothpaste

 

Shower gel:The figure above shows that the consumer in our example alternated between different brands of shower gel changing 6 brands during 74 day (12 weeks) of the study. Using content data, we can conclude that a new bottle of shower gel is purchased every 12-13 days; and brands of shower gel are alternated without repetition which allows us to put shower gel in theGreen itemscategory according to the Preference-Brand Loyalty mechanism.

Metadata provides more information about the choices of shower gel brands but, in this case, does not allow us to formulate better predictions about the future consumption compared with the content data. Specifically, analysis of the consumer purchasing diary reveals that all shower gels were bought at different locations/shops. The analysis of content and metadata on the shower gel consumption in this example allow us to place shower gel underGreen itemscategory.In this case, both content data and metadata would make the same prediction: in the future we can expect to observe low brand loyalty for shower gel brands (i.e., this consumer will continue alternating brands in the future).

Shampoo:Content data shows that shampoo consumption pattern is more complex: consumer chooses Brand B twice and Brand C once during the observation period (shampoo of Brand B is replaced after 8 weeks and shampoo of Brand C is replaced after 1.5 weeks). Content data allows us to classify shampoo as Yellow item.

However, metadata reveals additional information which changes this classification. Specifically, consumer stated that they always bought Brand B, and Brand C was purchased because the pharmacy where the consumer was shopping for Brand B did not have Brand B in stock. Therefore, a much smaller bottle of shampoo of Brand C was purchased in a hope that it would soon be replaced by Brand B. Therefore, for this consumer, shampoo should not be classified as Yellow item. Rather it should be classified as a Red item.

In this case, both content data and metadata would make different predictions: content data would predict that every once in a while consumer would prefer to buy a different shampoo brand to Brand B while metadata would predict that consumer would prefer to always buy shampoo of Brand B (which is a more accurate prediction).

Toothpaste:Using content data we can make the following conclusions from the observed patterns: consumer needs to replace toothpaste every 2 weeks if they use Brand C and every week if they use Brand D; and toothpaste can be classified as a Yellow item because consumer mostly uses one brand of toothpaste (Brand C). However, consumer occasionally deviates from their preferred choice in favour of other brands (Brand D).

Metadata, however, reveals that the picture is more complex than that depicted by the content data. Specifically, the purchasing diary revealed that consumer always buys toothpaste of Brand C. Yet, Brand D was used for 3 weeks during the observation period because it was prescribed by the dentist. Therefore, Brand D was not purchased because consumer really preferred to buy Brand D. Instead, it was purchased on doctors’ instructions. Therefore, taking into account metadata, we should classify toothpaste Red item rather than Yellow item.

In this case, both content data and metadata would make different predictions: content data would predict that every once in a while consumer would prefer to buy a different toothpaste brand to Brand C while metadata would predict that consumer would prefer to always buy toothpaste of Brand C (which is a more accurate prediction).

Comparison between content data and metadata is summarized below

Shower gel Shampoo Toothpaste
Content data Green Yellow Yellow
Metadata Green Red Red

What conclusions can we make from this example? Overall, metadata allow to significantly reduce noise in the data even when we have few observations. Content data may be able to produce the same results as metadata, however, in order to reach the same conclusions content dataset has to include more data and over a longer time period to establish robust behavioural patterns. If consumer data is available over a relatively short time period, metadata is the way to go as it would produce more accurate predictions about future consumption. Therefore, it is important to develop markets and technology which would encourage and incentivize consumers to collect context-dependent data within their households (e.g., see theproject). If we are able to predict consumption patterns better, we will also be able to develop better (more optimal) business models and create more personalized goods/services in the future.

 

About the Author:

Ganna Pogrebna

3798791880957e5ffb98e1cb49a795caDr Ganna Pogrebna is a co-investigator in the HARRIET project. Ganna is Associate Professor of Decision Science and Service Systems at WMG. She is a decision theorist/behavioural economist and empirical econometrician with particular interest in decision making in a digital domain, IoT and behavioural aspects of platform choice. She also works on behavioural aspects of digitisation and business models in application to individual and household choice as well as smart cities where her areas of expertise include quantitative modelling, data analysis, and new business models. In 2011-2012 Ganna received a Leverhulme Early Career Fellowship in behavioural science. She has published in high quality peer-refereed economics and business journals. Within HARRIET, Ganna is particularly interested in the influence on the digital technology on individual decision making within the household and in the workplace. Her tasks include analysis of sensor data and derivation of HAT/HARRIET Algorithms for new products/services and business models.

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]]> Thinking and Designing In The Meta /blog/thinking-and-designing-in-the-meta/ Sat, 31 Jan 2015 11:57:54 +0000 http://206.189.16.4/?p=1201 Originally published on Hub of All Things. (Img.Igor Bulgarin,Shutterstock) It’s 0527am and I’m awake. And...

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]]> Originally published on . (Img.,Shutterstock)

It’s 0527am and I’m awake. And exhausted. The mind has been working all night trying to come up with solutions for the design of views on the HAT that would help a user to be creative with his/her own data. A long meeting with the tech team yesterday has basically got some of the technical stuff down, so that the data that comes onto the HAT has the greatest agility to be shaped into different uses.

Too abstract? Ok, so let me rewind. We are now in the world where data sits as a consequence of a service provided. So your calendar’s data is part of Google Calendar service. Your photos are part of the service of a phone, your social interactions’ data sits on Facebook as part of their service. There are two consequences of this.

One is what we have already talked about –Which is why we’re building the HAT, so that we can acquire all these data (through open APIs) back into our own HAT so that we can make use of it. The second consequence is our mental models and structures. We are now trapped in a world where data makes sense only through the vertical services rendered. It’s like a house makes sense if there are rooms – dining room, living room, kitchen – because activities happen in those rooms and the house makes sense. If suddenly, I give you a blank house without rooms and say: let’s reorganise and recompartmentalise because technology now offers new ways to act and interact, you might not know where to start (for those interested, you can read up on).

So it is with data. We are used to data sitting in verticals, so we organise our lives around this (often not very efficiently). But when the HAT comes along, it would not just let you acquire your data into a space; it liberates it from its vertical structures. Imagine every photo, every message, every transaction, every data collected about you is now in one space and you can mash them up in completely new ways. You can create a whole new symphony of data with mashups that helps you make better decisions, gives you better recall (). And when you run out of ideas, you can buy new apps or widgets for your own data so literally you can crowdsource creative uses of your own data. Nice, right?

So, you can now read my first paragraph again and see where I am. Technically, we have designed the HAT database schema to be able to mash things up. Data points are tagged by time, location and user so that you can mash up locations with different times and users that your HAT is connected to, mash up data and users in the same time and location …… You get the picture.

It took us some time to get to this point but I’ll spare you the gory details. We got here. My challenge now, is to think of views. Screen views, on phones, iPads or computers. Ways to view this data that can spur creativity. Viewing your data so that you can generate new ways of using it is no easy feat. I showed my daughter one view of mashup data that I had designed, and she thought of something and said: “You need to create a reminder, a prompt, coz when I see that, I suddenly remember something.”So views can trigger different responses, so we should build in the possibility of creating nudges and prompts in the views. Views can clearly do more creatively especially when the data is mashed up, and I’ve been spending days applying some of the thinking inhere. The challenge is to design views without a purpose except to broaden the mind for new possibilities to co-create value with our own mashup data. I.e. Designing views for new views. Very meta.:)

It’s really exciting to see data being liberated this way though, and I can’t wait for the HAT roll-out later this year (). To see ‘my day in data’ from the music I listened to (Spotify), the interactions I had (Facebook) in different locations (phone) and my pulse rate (Fitbit) all mashed up in one view is like creating art with data. Now I just need it to amplify my capability. Where are those HAT new business models and innovation then….:)

The work continues……and do come for a discussion on personal data economy in Venice at our. See you in Venice!

 

About the author:

Irene Ng, Professor of Marketing and Service Systems, WMG, University of Warwick

irenecropped2-208x300Irene is also the Director of the International Institute of Product and Service Innovation (IIPSI), and leads the Service Systems research group at WMG. Prior to joining academia in 2002, she was an entrepreneur for 16 years, and was Professor of Marketing at University of Exeter Business School before leaving for WMG in 2011. Specialising in new and disruptive methods of economic and business model innovation, Irene has written over 22 publications in top international journals in the area of value, service systems and new business models. An IO economist by training, her books includeĢý and Revenue Management of Services, Value and Worth: Creating New Markets in the Digital EconomyandComplex Engineering Service Systems. Irene has developed several mathematical algorithms leading to the successful commercialisation of products such as AXIOS (a service requirement software for customer perception of business model/contract attributes) purchased by Rolls-Royce and context pricing models within other business applications. She is an ESRC/AIM Services Fellow, ESRC/NIHR Placement Fellow, and a College Research Associate at Wolfson College, Cambridge with considerable experience in leading trans-disciplinary projects (involving more than £5m worth of both EPSRC and ESRC projects).

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