TSB IoT Showcase Presentations from the 10 pilot projects taking part in the TSB Internet of Things Convergence Programme.

1. 27 June 2012 © 100%Open 2010 1
TSB IoT Convergence Showcase
27th June 2012

2. 27 June 2012 2
CCR
CCR
(Consumer Convergent Retail)

3. CCR – Consumer Convergent Retail
3
Explored the convergent scenarios within retail environments combing
online and offline experiences and data

4. CCR Explored these questions
• What are the appropriate convergent user scenarios
that will increase multi channel behavior?
• How will the creation of new data from people &
objects impact on these scenarios?
• How can this data be shared to enable the creation of
3rd party converged services?
• What is the role of Emotional Intelligence within these
scenarios and how can exploiting this data affect the
retail environment?

5. Responsive Retail - Principles
• Consumers are Internet things/ objects. Consumers
carry rich metadata profiles ‘Personal Data Passport’
• Emotional intelligence (EI). Exploring environments that
respond appropriately to people’s explicit and implicit
interactions; mirroring and supporting natural behaviour
• Data Relationships. Products have complex data
relationships with each other (food makes a recipe,
clothes an outfit or loud speakers match amplifiers etc).
• External Influencers. Personal and global social world
can provide real time recommendations, predictions
and trends.

7. Responsive Retail – Consumer benefits
• Convenience and Saving Consumers time. Product
Identification, fit, match current shopping preferences,
verified though social recommendation.
• Enhancing appeal of particular products through
personalisation and incentives.
• Increasing confidence in products. Enabling virtual try,
providing real time social connections and personally
relevant considerations
• Providing an appealing/ rewarding experience.
Identifying consumer (VIP), Entice and Tease
(emotional environments), Play & reward.

8. Responsive Retail - Challenges
• Misunderstanding and/or lack of expertise across retailers on
consumer digital behaviour and a lack of consumer
feedback.
• Disparate nature of consumer data and a growing
disillusionment from consumers in regards to how their data is
used.
• Lack of standards for identification of people and the sharing
of personal data. ‘Personal Data Passport’
• Disconnect between product data and external trends.
• Lack of a Digital integrated Omni-channel platform,
disconnect between existing in store technologies between
themselves, the environment and mobile devices.

9. Responsive Retail - Strategies
• Brokerage. Building trusted relationships with industry in order
to relieve the burden of innovation and to relay needs and
insights.
• Don’t reinvent. Work with organisations in this space who can
provide, technology, data harmonisation, analytics and
human behaviour insights.
• IOT Developer Toolkit. Harmonised Data, Omni-Chanel
platform, payment mechanisms. Personal Data Passport.
• Real world user testing. Products and services created are
tested in store in order to rapidly identify successful models
• Investment Eco-system. Successful products are funded
through various mechanisms in order to meet opportunity
window.

11. 27 June 2012 11
City of Things
City of Things

12. http://cityofthings.com

13. Overview
• Urban built environment
• Centred around Manchester
• How to enable and apply IoT

14. Barriers
• Investment and risk
• Governing use of personal or commercial data

15. Opportunities
• New business models from lower transaction
costs
• Improved management of city environment
• Micro-provision of services
• New applications thanks to shared platform
• New applications exploiting new data

16. Challenges
• Privacy and control of data use
• Funding a shared pervasive wireless network
• Practical issues around data collection
• Data management and distribution

17. Strategies
• „Standard labels‟ for data governance
• Choose standards for devices and comms
• Use Linked Data and APIs for data distribution

18. Demonstrator
• Should be in a specific place
• Should support and (part) fund a portfolio of
projects and applications
• Should provide shared infrastructure: wireless
network and data handling infrastructure
• Should test solutions to data governance
issues

19. 27 June 2012 19
Cross Domain IoT Interchange Broker
Cross Domain IoT
Interchange Broker

20. Our project partners Our assets
Data owners/users representing;
• Health & Telemedicine -Docobo Ltd.
• Building Control / Metering -Horstmann /
Secure Controls UK
• Environmental Sensing -SciSys
Academic and policy input;
• Personal Information Broker-
Development Ltd
• University of Bath – Department of
BathCube Computer Science
Telecoms & Innovation • Technical
Consultancy
• User behaviour
Industrial Infrastructure/computing;
• Horstmann / Secure Controls UK
• SciSys
• University of Bath – Department of
Computer Science
Project Management;
© 2012 Cambridge Wireless
• BathCube Ltd

21. Town Hall
Hospital
GP
Chemist
Grocer
Severe Weather
Scenario Overview

22. Q1: Barriers to convergent scenario, potential identified etc
Barriers Economic Potential
• Separate „silo‟ data chains • IoT services we foresee
● Technical between health/energy/LA
● Corporate behaviour entities do have major
potential given that;
• End to end connectivity ● Heavy snow in Dec 2010
cost NHS extra £42m.
• Data confidentiality / Legal ● 15 to 24% rise in Chronic
Obstructive Pulmonary
• Addressing formats Disorder admissions with low
temperatures.
• Lack of incentive (financial or ● 27,000 excess winter deaths
otherwise) to share data ● Coldest housing quarter
3* higher rate than
• Regulatory warmest quarter.
● Increasing energy supply
• User behaviour variability requires IoT
enabled smart grids.
© 2012 Cambridge Wireless 27/06/2012

23. Q2: Applications and services, enablers, use cases etc
• Systems that could become enablers of useful new services are present
but in silos (Utility Metering, Alarms and Communications, Heating and
Energy Control). During a severe weather incident they can improve:-
Preparation Warning Incident Recovery
• Identify at risk • Cascade early • Monitors at risk • Use of improved
individuals warnings to individuals remotely situational
professionals • Schedules awareness to direct
• Adapt processes • Care chain predicts resources to most
resources based on
to IoT data likely needs and actual needs arising affected locations
availability fulfils • e.g. Remote • Communicates to
• Set up visibility & • Tailored advice intervention to individuals of
control of data • Food, Oxygen, ensure heating is changes to routine
set to best level for until normality is
• Distribute care Prescriptions
restored
health
equipment to • Crowd sourced data
vulnerable • e.g. Proactive
welfare telephone improves
• Identify and call if normal awareness
insulate poor routine deviated
thermal from
performance
houses
Barriers : Inertia, Lack of abstraction, Human Factors, Trust,
Reward, Security, Lack of suitable brokers.
© 2012 Cambridge Wireless 27/06/2012

24. Q3: Organisational challenges to allow shared IoT based services.
• Multiple issues including;
● Data Ownership- who owns data collected about you?, Medical data challenges
● Legislation- Data Protection Act, Privacy, Liabilities for service failure.
● Technical-No available brokers, universal interoperable WAN/HANs, formats.
● Commercial- Independent provision, no shared priorities, how to identify value.
● Personal Freedom- Are you a person or managed object, Big Brother watching.
● Education- How to make people aware of shared data and sharing techniques.
● Data Confidence- If you don‟t trust it you won‟t buy it.
• Of which identifying and returning the additional value from services is key;
● Local Authority- what is the incentive to be better prepared if today‟s state is
adequate?
● Health Authority- Sees a statistical fall in cases compared to expectation but
running costs are unchanged- treat the next in the queue.
● Keeping power on for a few vulnerable individuals costs more than penalties on
utilities for not keeping it on.
Little incentive to spend £x to save £nX in today’s delivery chains
© 2012 Cambridge Wireless 27/06/2012

25. Q4: Strategies to move to converged scenario.
• Provision of a Broker Eco-
structure;
● Individual selects an „information
broker‟ (IB) from a managed
market.
● IB provides SSO, transaction
based permissions for
transmission of personal data
between counterparties. e.g.
Individual „A‟ uses smart-phone „B‟
to access his account „C‟ to route
IoT data from fitness monitor „D‟
to Health Insurer „E‟.
• Introduction to first application and sector by sector expansion;
● For the enhanced cares scenario Govt. intervention may be required to
incentivise smart metering and buildings to have functionality needed in
later life to reduce care costs arising from ageing demographic.
● Other sectors such as Higher Education or Energy Management may be
better initial sectors.
© 2012 Cambridge Wireless 27/06/2012

26. Q5: Practical suggestions relating to an IoT demonstrator
• The demonstrator requires;
Supportive, Creative, Rapid
● Technology investment in 2 or more
Business Development
interoperable broker systems;
Environment
● minimum functionality to support new
broker enabled services spanning 2 or
more business sectors. Development Projects & Trials
● Community and Engagement- A business
development environment to bring data set P1 P2 P3 .... Pn
owners, innovators, developers together to
build initial viable services. Technical Infrastructure
● A well defined technical architecture before (network of brokers)
tenders for development are invited.
● Use of „Open Innovation‟ practices within Demonstrator Target
CDEC to successfully engage both large
and small organisations .
• Transitioning to commercial operation requires;
• Careful selection of the initial service sectors and then spreading sector by sector-
admitting additional data ontologies and minimum necessary API additions.
• Initial hosting a government service on the system is desirable.
© 2012 Cambridge Wireless 27/06/2012

27. 27 June 2012 27
Smart Home Data & Systems
How can Smart Home Data &
Systems Improve Assisted
Living Services

28. How Can Smart Home Data & Systems
Improve Assisted Living Services
Adrian Coe, WattBox Ltd
27th June 2012

29. Project Overview
• Two specific Assisted Living convergence scenarios were developed:
– Ada – elderly lady living in a remote location with health issues
– Fred & Gina – younger couple with learning and health difficulties
• These were used to assess the general market space and look at the
suitability of existing and emerging technology products and services
• Industry Expert Group and User Focus Group engaged to test potential
issues and emerging ideas
• Reviewed overall market space for smart home and assistive technology
• The Technology envisaged to be offered would include:
– Smart Meter
– Smart TV
– Smart Heating Controls
– Smart Fridge
• Through connectivity and internet services can we foresee useful assisted
living applications & businesses using such lifestyle technology

30. What is Preventing Scenario from Happening?
• Technology Averse Customer Base
• Concerns about data security and Big Brother watching
– Capacity to consent
– Anonymous data versus personalised data
• Particularly where user attitudes are liberal on data sharing the duty of care
lies with the service provider
• Cost of technology versus value of data
– Technology tends to offset care costs but hard to value the benefits
• Active market development happening and creating new data silos to
protect their service offerings and business

31. Applications and Services that Could Develop
Fall
Detectio
• Many services exist or are n
Home Memory
emerging already in isolation Budget Jogger
but full benefits and cost
effectiveness not being
Applianc
realised e Mis-
Use
Retail
• Potential for tailored solution
mix to each individual Public
Ada Activity
Transpor
Monitor
t
• We can do something useful
with frivolous consumer
technology like smart TV‟s and Care & Smart TV
GP Rehab
Services
Smart Fridges and make smart
meters useful Prescript Hypothe
ions rmia

32. Actual Challenges Faced by Organisations
• Direct and perceived obligations under the Data Protection Act
• Finding a way to monetise service offerings
• Technical issues relating to diverse range of communication protocols
• Little perceived incentive to develop open standards and hardware within
existing tele-health and tele-care businesses
• Where should data be aggregated and how/when should it be anonymised?
– Who owns the data and the rights to use it?

33. Practical Strategies to Move Forwards
• Using familiar technologies such as the TV as the basis of user interface
– Pill reminders to pop up between programmes based on EPG data
– Easy integration of webcam and Skype can ease communication with family,
care providers or GP
• Focus on most useful initial applications to generate the consumer need
– Lifestyle profiling for Epilepsy or other health tracking
– Hypothermia Risk Reduction
• Push data ownership clearly down to the individuals in order to tackle data
security issues openly
– User works with a single trusted body to agree who has access to data
• Use standard consumer hardware and target useful lifestyle solutions at the
mass market rather than assistive niches
• Ensure that all technology programmes in the Assisted Living sector are
conducted with open data access and IOTC as implicit elements
• Extend programmes such as “Bridging the Digital Divide” to establish
community champions

34. What UK Demonstration Would Help ?
• Establish an open data repository with clearly defined access rules and
criteria
– Needs to become a trusted host for personal and anonymous data
– Companies and individuals able to sign up on standard terms and conditions to
upload and utilise data
• Encourage or mandate that all UK Government funded development
projects to utilise this data repository
– Similar basis to EST Database established for Retrofit for the Future
– Quickly builds a carefully protected data set to be used by application developers
• Fund numerous small projects to encourage SME‟s to utilise the data set
and develop applications across a wide range of market sectors

35. 27 June 2012 35
ICT-i
Intelligent City Transportation
Infrastructure (ICT-i)

36. Intelligent City Transportation -
Infrastructure (ICT-i)
IoT Convergence Showcase 26th June
Professor Dennis F Kehoe AIMES IoT Presentation

37. Background – Urban Transport
Data providers External systems
Core ICT-i open service platform
Intelligent
Traffic data Intelligent Prospective intelligent
transport
information user access transport systems
routing
Data API
aggregation gateway
Intelligent
Intelligent
Transport information transport In-vehicle transport
user
centres service systems
connectivity
management
Legacy transport Independent transport
systems systems developer
... ...
£ revenue £ revenue £ revenue £ revenue
Bus/Train/Ferry Consumer
Traffic control Wi-Fi Hotspot
services smartphone apps
Users
Denholm Logistics
Professor Dennis F Kehoe AIMES IoT Presentation

38. The ICT-i Scenario
Value Chain Service Cost Models Service Revenue Models
Aggregated
service data
set 2
Improved
Common data Online user
Data Providers API‟s community
service
performance
Aggregated
service data
set 1
Infrastructure Cloud-based Platform Connectivity
Providers services SLA‟s services services
Application Apps store Applications
Providers development downloads
User register User
Users for apps consumes
apps
Denholm Logistics
Professor Dennis F Kehoe AIMES IoT Presentation

39. The ICT-i Applications and Services
• Public transport – real time transport data,
crowd source disruption data, increased passenger
engagement
• Private transport – collaborative traffic
management, integration of GPS and traffic data,
route/congestion optimisation
• Freight transport – Port scheduling, vehicle
prioritisation and monitoring
Denholm Logistics
Professor Dennis F Kehoe AIMES IoT Presentation

40. The ICT-i Challenges
• The infrastructure requirements in terms of the
resilience, availability and scalability to support an
IoT Demonstrator in urban transport
• The requirements for data interoperability to
create an open data store for transport data
including both on-board vehicle data and traffic
system data
• The business models which would emerge from
a transport IoT and the viability and sustainability
of such business models
Denholm Logistics
Professor Dennis F Kehoe AIMES IoT Presentation

41. The ICT-i Opportunity
Denholm Logistics
Professor Dennis F Kehoe AIMES IoT Presentation

42. The ICT-i Demonstrator
• Public Transport
• Private Transport
• Freight Transport
• Data Store
• Apps Community
•Six Stage Process
•Campus Focus
•Scalable
•Orchestrated
•Political Leadership
Denholm Logistics
Professor Dennis F Kehoe AIMES IoT Presentation

43. 27 June 2012 43
Housing, Care and Health
Internet of Things Convergence
For Housing, Care and Health

44. Internet of Things for
Housing, Health and
Care
Consortium:
Housing 21
IBM UK
IVHM Centre
Technology Strategy
Board
Cranfield University
27th of June 2012

45. Internet of Things
for
Housing, Health
Care
and Care records
Overall goal: develop a strategy and plan to enable
Health Financial
Housing 21 to access and share information about
relevant “things” regardless of location or information
records
repository,
and deliver it to the right people at the right place and
time in order to directly benefit the health and wellbeing
of its clients.
Tenancy Data from
agreements “Things”

46. Question 1. What‟s
preventing the scenario
from actually
happening…
Key Challenges Faced by the Care Industry
Opportunities
Potential Benefits
Inefficient
Financial and
Need Difficulties dataRecognised
Improvements
Implications to collating Increased
desire data (data
in clients
ImprovedDifficulties exchange need Security,
and
competition
due to Reduced and
deploy „smart‟ service measuring
Quality of Life
increasing about Increased demand forand
provision and load and problems
between a
privacy
and physical,
needs of of care
case Quality ofefficiency suppliers and
way an people client
mental and developing data burden Life client choiceissues
leveraging centred
legal
for
ageing engagement large
provision and
social health dementia)
population amounts of dataconsumers
management data approach
46

47. Question 2: Applications and Services that
can be used in the Scenario…
Value Network Map
Scenario Model
Marie, living at Housing 21 extra care home
The Converged
Scenarios
47

48. Question 3: Challenges
faced by H21 and its
peers…
The scale of the problem and associated costs
Lack of specialist expertise and resources within the
relevant organisations
Lack of trust, willingness and incentives to share data;
lack of openness and transparency
Security issues
Confidentiality, privacy and ethical Issues
Stakeholder perception and resistance to deployment
Poor flexibility to the external environment

49. Question 4: Practical
strategies to move towards
the scenario…
- Clearly defined business case
- Road mapping
- Training
- Strategic partnerships with technology providers
Opening up data and adoption of intermediary measures
Stronger authentication measures
Further in depth studies involving a cross section of stakeholders
- Adaptable interfaces
- Research on the adoption of innovation in the sector
Change management and business process re- engineering

50. Q5: The
demonstrator…

51. 27 June 2012 51
Transport and Logistics
IoT Enabled Converged and
Open Services for Transport
and Logistics

52. IoT Enabled Converged and Open Services
for Transport and Logistics
Alistair Duke - BT Research and Technology

53. Project Overview
City
Congestion Information,
Road speeds, etc.
Port
Open Logistics Information
Local
Attraction
Hub Schools
Events
information
Local Unforecast
Authority Highways County Forecast Weather
Events Agency Council Weather Event
© British Telecommunications plc
Events Events Events

54. Q1: What is preventing the scenario from
happening?
Commercial Technical Legal
© British Telecommunications plc

55. Q2: What are the applications and services that
could be developed?
Journey Time
Planning
© British Telecommunications plc
Incident Management

56. Q3: What challenges are faced by the
organisations involved?
Recognising
data as a
digital asset
Business
model innovation
Understanding
the value chain
© British Telecommunications plc

57. Q4: What practical strategies can be employed to
move towards the converged scenario?
Information
Hub
Market Maker Incentives for
new entrants
© British Telecommunications plc

58. Q5: What UK demonstration facilities would help to
experiment?
• Develop an open information hub
• Provide capabilities / enablers
• Populate the hub with cross domain data
• Develop exemplar applications
• Widen involvement via partnerships
• Enabling experimentation with value chains and business
models
© British Telecommunications plc

59. 27 June 2012 59
MyHealthTrainer
MyHealthTrainer

60. MyHealthTrainer
Final workshop presentation
27 June 2012

61. Everyone is a Self Hacker...
... but some tools
would make us
better at it.

62. Q1: 24 Hours
Self Hacking System

63. Q2: Apps and Services
• Self Hacking / Behaviour Change Applications
– well-being { weight-loss, fitness, stress}
– optimised travelling {link to public data}
– energy saving
– improved commerce (VRM)
• Enablers
– GB smart meter roll out
– Smart phones / pedometers , APIs for data access
– Map reduce technology

64. Q3: Challenges
• Personal data locked in CRM Silos / No Ecosystem
– E.g. supermarket loyalty cards
– Data Protection Act Request for personal data - £10 for a snail-mail printout.
– Our experience: hard to get retailers to share personal data
• Data Literacy (of Individuals and some organisations)
– Excessive disclosure on Facebook
– Surprise that smart meter analysis leads to family disputes
– But this is improving.... E.g. Quantified Self movement
• Behaviour Change
– Information => motivation,
– But motivation not enough => smart phone triggers.

65. Q4: Strategies Towards Scenario
1. The Standard’s Approach (API’s data formats)
2. Linux Approach
– Open source (storage, analysis, and wordpress style dev kits).
3. Apple app store
– Core features funded by large organisations
4. Retailer approach
– Similar to 3. Then sell services through retail channel.
5. Bootstrap
– New company slowly builds its own channel to market and
brand (e.g. FitBit).
3, 4, 5 too early just means more silos and not convergence.

66. Q5: Demonstrator Recommendations
Fig.1 Value Chains
Technology Strategy
Brands Board
£
£ services
£
£
SME(s) Apps/
apps
Demonstrator Co. services
Users
(App store)
Public
Infrastructure Personal
Data Data

67. 27 June 2012 67
MyHealthTrainer
Smart Streets

68. Smart Streets
Richard Boswell-Challand,
In Touch Ltd

69. Summary
The Smart Streets Project has explored the
potential for connecting highways street assets
to the Internet of Things
Investigated how creating virtual
representations of these „things‟ enables radical
changes in the the way we maintain our
infrastructure and enables new applications in
areas such as flood management, highways
planning and travel information
Identified clear opportunity for rapid national
rollout and use.

70. Q1: The Scenario
Why Smart Street Streets ?
- typically publically owned
- ubiquitous
- the connection points between buildings and cities
The Smart Streets converged scenario is of an integrated,
connected infrastructure that encompasses notions of
intelligent transport and smart street furniture, acting as an
integration point for a variety of sensor-based smart systems
(a system of systems) and providing a key component of the
future smart city or smart region.

71. Q2: Apps & Services
Enables a wide range of
applications and services:
- SmartGully
- SmartGrit
- Enhanced maintenance

72. Q3: Challenges
We conducted a series of user-engagement exercises
including “an innovation workshop” and interviews to
understand challenges.
Many challenges centred around the competitive and
relatively short term nature of business.
Technical challenges focus on combining need for standards
with the required level of agility.
Few ethical or legal issues.

73. Q4: Moving Forwards
The highways maintenance domain is potentially one of the
most amenable to high-speed adoption of IoT technologies.
Contracts used to outsource maintenance are subject,
ultimately, to government control. By imposing conditions
relating to IoT standards compliance on sub-contractors
bidding for work, the Smart Streets scenario can actually be
achieved by fairly short-term changes, as contracts tend to
be issued on a five-year cycle.
A converged IoT scenario could be realised on a national
scale within a surprisingly short time-scale (around five
years).

74. Q5: The Demonstrator
A regional walled garden with knowledge hubs to support a
range of activities.
Fast fail model to facilitate rapid, cheap innovation.
Investment in data feeds.
Ability to grow to a national scale within 5 years.

75. 27 June 2012 75
VIB
Value chain analysis of the
Internet of Things for the
Brewing Industry (VIB)

76. Value chain analysis of the Internet of
things for the Brewing industry (VIB)
Tom Hare / Howard Stone

77. Project Summary

78. What is preventing our scenario from
happening ?
• Technology Adoption
• Set Down of the overall “open Loop”
infrastructure
• Completion of a commercially viable end to
end demonstrator
• No first-mover advantage

79. Applications and services that could be
developed in our scenario
• Data Provider
• Infrastructure Servicing
• Consumer engagement Apps
• Tracking Apps
• Sensor Networks
• Feedback for consumption – partly have the
information as a revenue stream – self fund

80. Challenges faced by those involved
• Costs for the technology providers
– how to generate revenues
– How to drive down unit costs of technology
• Process change in retail
– Incent/persuade staff and owners – show them the return
• Process change for logistics and product
providers
– Show the savings potential
• Consumer Privacy Concerns

81. Strategies to moving towards the
converged scenario
• Picking up learnings from other scenario
projects
• Build out awareness of converged IoT
• Heavy and continued communications plan
• Show the savings
• Continue to develop Pilot Trial as a Showcase
• Expand to the Smart High Street – engage
more forward thinking co-partners

82. Recommendation for the demonstrator
• Something people can engage with
• Results that can be seen
• Use of existing thoughts/processes/data
sources
• Consumer Engagement
• Walled Garden
– Manageable Scope
– Based on geographic location
• -> Smart High Street

83. 27 June 2012 © 100%Open 2012 83
Project contacts
Roland Harwood and David Simoes-Brown
Co-Founders & Partners
100%Open | Somerset House | South Building | London | WC2R 1LA
Phone: +44 (0)20 78133 1006 | +44 (0)7811 761 435
Email: roland@100Open.com | david@100open.com
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