UoM Smart Cities Open Meeting #1

Thursday 23rd February 2017 11:00 - 13:00

University of Manchester Innovation Centre

@Man_Inf @UoMUrban

Carmel Dickinson Programme Manager, Manchester Informatics

Introduction to the Smart Cities Theme & the CityVerve

Project

@Man_Inf @UoMUrban

UoM Smart Cities Initiative

• Manchester Informatics & Manchester Urban Institute: Smart Cities

– Community-Building events

– Collaboration Workshops

– External Engagement Events

– Further ideas welcomed!

– Putting People @ the Centre of Data event 13th March

UoM Smart Cities Research

• Long tradition – Smart sustainable cities

– Collaboration with city-region and industry

• Living labs (SEED)

• Triangulum (EEE & AMBS)

• Smart, sustainable cities (AMBS MIoIR)

• Smart, healthy cities (FBMH)

• CityVerve (AMBS, CS, EEE, SEAES, FBMH)

CityVerve IoT cities demonstrator

• 2 Year programme

• IUK funded

• £16M total investment

• 20 delivery partners – public and private sectors

• 2km2 Oxford Road Corridor

• Open innovation

CityVerve IoT Cities Demonstrator

2 Year programme

£16M investment

An innovative project

2km2 Innovation corridor

A collaborative project

20 delivery partners – public and private sectors

6

Feb-17 Project No:

102561

Q1 Overview - WP1 partners

Transportation use cases

Feb-17 Project No:

102561

Talkative Bus stop City Concierge

Sensing Trams

ebike Sharing

Road Safety

Energy & Environment use cases

Feb-17 Project No:

102561

Next-Gen BMS

Air Quality Smart Place

Lighting Smart Parking

Compliance Cost Reduction

Enforcement Support

Building Retrofit Energy Reduction

Health & Social Care use cases

Feb-17 Project No:

102561

Chronic Condition Management

Community Wellness Neighbourhood Team Support

UoM role • Energy & Environment

• smart buildings • air quality

• Health and social care • managing long term conditions • increasing physical activity for wellbeing

• Data management and analytics • Evaluation of the project, business models and the

approach to data

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Air Quality Monitoring

• Monitoring air quality at traffic intersections for traffic management (e.g. diverting traffic)

• Providing air quality information to improve health and wellbeing (e.g alerting vulnerable people)

• UoM advising on accuracy and sensitivity of available low -cost environmental and air quality sensors world-wide

• Mixed system of sensors deployed • UoM comparing the capabilities of available sensors and • Providing benchmark comparisons with high precision

research-grade instrumentation

Ian Cotton Director, Manchester Energy

Improving Energy Use

@Man_Inf @UoMUrban

Energy & Environment - Drivers • How can we make use of the existing infrastructure

supplying energy into a city?

• How can we support the increased electrification of energy for transport & heat?

• How do we balance the (potentially) competing needs of the city and the nation as a whole?

Energy & Environment Analytics

Analysing and utilising the data derived from the sensors (e.g., occupancy, energy, environment) to reduce energy use and increase environmental comfort for occupants:

• Data sourced from buildings across the University estate

• Energy consumption analytics

– Linked factors such as occupancy patterns for space utilisation and energy efficiency in building

• Analysis and assessment of a model-based advanced control strategy – important locally / nationally

Energy Efficient Buildings

Systematic frameworks are needed to effectively manage all energy resources (e.g. climate change mitigation, better comfort, better utilization of existing infrastructure).

Buildings integrate not just loads but also storage systems (passive / active) and renewable energy sources.

Control Scheme for Energy Efficiency

Stochastic Model Predictive Control (SMPC)

A.Parisio, D. Varagnolo, M. Molinari, K.H. Johansson

Tjeerd Van-Staa Professor, Health eResearch Centre

Improving COPD Care

@Man_Inf @UoMUrban

Desired Outcomes

• Acceptability of technology • Improved mobility • Improved adherence to medication and exercise • Improved patient activation (PAM) score • Increased confidence in self-management

Measure Outcomes

• level of satisfaction with technology • how much exercise • what medication and when • level of PAM score • level of confidence in self-management

Technology Outcome

Smart inhaler Improved adherence to medication

Location services Improved mobility

Increased confidence in self-management

Activity tracking Improved adherence to pulmonary rehabilitation

(exercise)

App for patients Increased confidence in self-management

App for care team Improved patient activation (PAM) score/ increased

confidence in self-management

Secure platform for integrating all data Acceptability of the IoT intervention

Data analytics Improved patient activation (PAM) score/ increased

confidence in self-management

Essential Technologies

Technology Outcome

Weather Improved mobility

Improved patient activation (PAM) score/ increased

confidence in self-management

Home sensors Improved mobility

Home environment Improved mobility

Improved patient activation (PAM) score/ increased

confidence in self-management

Use of public transport Improved mobility App for family and friends Improved patient activation (PAM) score

Extended app for care team Learning health system (but this is not a measurable outcome)

Desirable Technologies

Crucial Questions In live monitoring of digital health data we may have a false positive signal.

Some questions that need to be answered are: When does it happen? How often does it happen? What do we use to determine if it is valid or not? (threshold?) How do we decide the signal makes sense? How do we make sense of this messy data? How do we react? What statistical approach can we use?

Charlotte-Stockton Powdrell Senior Project Manager, Division of Psychology &

Mental Health

Get Manchester Exercising

@Man_Inf @UoMUrban

Community Wellness Use Case: City Motivators

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Health & Social Care

• Increase physical activity by engaging with people who work and study in the Oxford Road Corridor e.g. CMFT, UoM, MMU, MSP, MCC, schools

• Encourage competition between employees or students to increase activity levels towards a target or goal, e.g. steps taken, calories burned, distance travelled

Community Wellness Use Case: City Motivators

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Health & Social Care

• Change behaviour by using contextual nudges to encourage more activity e.g. location, weather, transport, air quality

• Rewards for increased activity to ‘spend’ on healthy

activities, snacks etc

Ann Gledson Research Associate, School of Computer Science

Fresh Insights from Data

@Man_Inf @UoMUrban

Tasks / Deliverables

• Task 18.2

• Cross-Thematic Data Analytics. Interplay of CityVerve datasets and other linked datasets to draw cross-thematic insights to inform policymaking and service design.

• Linking vertical themes

• Deliverable 18.2

• CityVerve Data Dashboard

• Target users: Data Analysts

D18.1: Data Dashboard

Time Series Database

Vertical Themes: • Health and Social Care • Transport • Energy and Environment Example: Car Parking Data • Current parking Levels • Car park profile • Weather data • Event data

Data Mining Software: R, Weka, Orange, etc

IoT / Sensor data

John Rigby Senior Research Fellow, Alliance Manchester Business

School

Evaluation of CityVerve

@Man_Inf @UoMUrban

CityVerve – a demonstrator

CityVerve has been established as a demonstrator with two main aims:

• providing evidence of benefit from the use of IOT technologies in certain impact areas, and

• demonstrating that such benefits can be achieved in other contexts, i.e. that its impacts are replicable in the sense of being transferred in whole or in part to other locations.

Evaluation Requirements

CityVerve Impact

Impact Category

Cross-thematic Project Level

Replicability

Evaluation Activities

• Evaluation – Project KPIs (Task 18.1)

• Cross-Thematic Data Analytics (Task 18.2)

• IoT Access Technologies Review (Task 18.3).

• Use Case Impact Assessments (Task 18.4, which will use KPI measurements to assess the impact of cases).

• Performance-in-Use Assessment (Task 18.5). (Future Cities Catapult)

• Business Model Innovations & Assessment (Task 18.6).

Evaluation WP18.1

Impact types measured by KPIs:

• Economic

• Technical

• Social

• Environmental

• Community Engagement (FutureEverything)

KPI Parameters

KPI

Parameter

For each KPI Evaluation Aspect

1 Indicate precisely the information that will be collected

and the existing entity to which it applies

Target Setting

2 Indicate whether comparison of the KPI (the baseline) will

be

a) internal, i.e. with another use case activity

b) temporal – over time

c) external – and therefore which comparator is to be

used (e.g. road safety statistics in other geographical

areas)

Target Setting

3 Indicate the presence of any plan for pre-collection to

develop historic data series for comparison

Target Setting

4 Indicate the source of information Management

5 Identify the cost of the information, if any Management

6 Designate a responsible person for collection and the

safe recording

Management

7 Identify the frequency of collection – ideally KPIs need to

be available monthly

Target Setting

8 State the point in time when data will become available

– how long after the start of operation of the use case

Target Setting

9 Identify any legal or ethical barriers to the collection of

data and the steps which the use case users will take to

deal with them

Management

Use Cases

Use Case Use Case Owner

T1 “Talkative” bus stops Andy Beechener, Republic of Things

T2 City Concierge Sparta vijay.n@spartadigital.co.uk (Vijay)

T3 Road Safety Stuart Millward, SatSafe

T4 Sensing Trams William Wu, Cisco

T5 eBike Sharing BT sandra.stincic@bt.com (Sandra)

EE1 Building Retrofit Energy Reduction Michael Grant, Asset Mapping

EE2 Compliance Cost Reduction Paul Collins, Spica

EE3 Next-gen BMS Tom O'Reilly, Siemens

EE4 Air quality monitoring Cisco - William Wu

EE5 Smart Place Lighting John Lewis, Telensa

EE6 Smart Parking John Lewis, Telensa

EE7 Enforcement Support Paul Morrison, PrismTech

HSC1 Chronic condition management Julie Harrison, CMFT

HSC2 Personal Wellness Platform Adrian Slatcher a.slatcher@manchester.gov.uk

MCC

HSC3 Neighbourhood Team Support UHSM - ilan Lieberman ilanlieberman@mac.com

HSC4 Nursing Home Care Merged with HSC3 – 2nd level plan is updated

CityVerve – impact timescales

Measuring and Monitoring – When will Impacts be Known?

Impact Year 1 2 3 4

Impact Month 6 12 18 24 30 36 42 48

Economic /

Cost Based

Cost saving major functions

Environmental effects ≈ reduced pollution

Abstract

Extendible

Scalable

Replicable

Imitation (beyond control)

Rule /

Dispositional

(Behavioural)

Behavioural additionality

Regulatory change

Dispositional / habitus

• KPIs for impact and monitoring – immediate collection • KPIs for replicability – towards project end

20100930 www.fireball4smartcities.eu

From InfoCities and Intelligent Cities to Digital Cities and Smart Cities: 30 years of digital innovation

Dave Carter Honorary Knowledge Exchange Fellow, Planning & Environmental

Management and Manchester Urban Institute

Head, Manchester Digital Development Agency (MDDA),

City of Manchester (2004-14)

Chair, European Connected Smart Cities Network (2010-15)

Interdoc and new global networking

The Velletri Agreement 1. Statement of Purpose • A wide range of NGOs met in Velletri, Italy, from 2 to 7 October 1984 to discuss specific

follow–up activity to the Documentation for Change meeting held in Lisbon Portugal in January 1982. The Velletri meeting focused on the recommendation “to establish a network of groups exploring the use of new information technologies for the exchange of feasibility studies, and experiences and findings.”

• The Velletri group was composed of representatives of grass–roots development action related information and documentation centers working at national and international level throughout the world.

See: “Interdoc: The first international non-governmental computer network”, Brian Martin Murphy, 2005. http://firstmonday.org/ojs/index.php/fm/article/view/1239/1159%20Interdoc

First global meeting of digital activists (probably …) 1984 in Velletri, Italy

Innovation, Creativity and Diversity “Technology, Talent and Tolerance” Richard Florida.

• Digital activism influencing the City’s Economic Development Strategy from 1989 onwards:

• Manchester Host, Electronic Village Halls, Community Information Network, Digital Arts Projects

• 1990s – convergent creative, cultural & digital agendas

• 2000s - Open networks, open source, open data

• Opening up the city • generating globally relevant skills and jobs locally

• creating pathways to employment for local people

• creating an ecosystem for open innovation

• Living Labs

20100930 www.fireball4smartcities.eu

Policy drivers: Smart City Agendas • UN Agenda 21 – ’smart growth’ 1992 • Telecities (part of Eurocities) set up in 1993 • European Inter-Regional Information Society Initiative (IRISI) 1994 • UK Digital Strategy 2005 – Digital Agenda for Europe 2010 • Smart, inclusive & sustainable growth • Green & Digital • Transformational services • e-Government to Smart Government • Future Internet enabled services in Smart Cities

• Internet of Things + Cloud + Open Data + 3D printing + nano.........

Poptel, GeoNet, APC, GreenNet, LaborNet

“The City as public good” http://www.cityofsound.com/blog/2013/02/on-the-smart-city-a-call-for-smart-citizens-instead.html

New collaborations • City as catalyst and enabler

• New institutions and autonomous spaces

New Creative Spaces and Innovation Ecosystems

MadLab - Manchester Digital Lab

Stimulating: • new ideas

• new business

• new skills

• new jobs

http://madlab.org.uk/

Hackspace Manchester

DATA STORIES •MORE STORIES

•

YO

L’Ateneu de fabricació – Barcelona Atheneums of Fabrication – Fab Labs to Fab Cities

First year: 200+ activities with 6,000+ people http://ateneusdefabricacio.barcelona.cat/

User generated models for innovation and change: • Pop up factories - http://solidcon.com/internet-of-things-2015/public/content/popup-factory

• Why Bio is the new Digital – Joi Ito (MIT) - http://solidcon.com/internet-of-things-

2015/public/schedule/detail/42570

• ‘DIY-Bio’ - http://diybio.org/

• Sustainable, Programmable Bottom-up Manufacturing http://www.oreilly.com/iot/free/bottom-up-manufacturing.csp

• Craft + Technology = “Cottage Industry 4.0”

http://thethingsnetwork.org/

IERC

Networking the networks • Connected Smart Cities Network – Open &

Agile Smart Cities (OASC) www.connectedsmartcities.eu - http://oascities.org/

• Future Internet

EUROCITIES, European Network of Living Labs (ENoLL), Future Internet Assembly (FIA), FI-PPP, Digital Agenda for Europe

• www.eurocities.eu

• www.openlivinglabs.eu

• www.future-internet.eu

• www.fi-ppp.eu

• http://ec.europa.eu/information_society/digital-agenda/index_en.htm

• Smart Cities & Communities • http://ec.europa.eu/energy/technology/initiatives/smart_

cities_en.htm

A Digital Strategy for a Northern Powerhouse [with soul] • Digital production and new makerspaces

• Devolved open networks & new local utilities

• Importance of creative skills and cultural talent

• Libraries+ for digital access & training

• Investment to grow internet infrastructure, e.g. hosting centres and digital exchanges

• Funding for digital talent not just advice

• Digital innovation in mainstream services (health, social care, education, transport)

Thank You!

dave.carter@manchester.ac.uk http://www.mui.manchester.ac.uk/research/themes/smart-cities-and-transitions/