Webinar on Smart Cities

Transcription

1 Webinar on Smart Cities

2 The Smart City Paradigm Carlo Alberto Nucci Department of Electrical, Electronic and Information Engineering Guglielmo Marconi DEI School of Engineering and Architecture University of Bologna

3 Introduction to Smart Cities Cities evolution In the coming years, cities are expected to deal with an increasing number and type of services for their citizens, all having to do with overarching goals such as sustainability environment quality of life energy saving As the population living in urban areas is expected to double by 2050, there is a general consensus that any new process will require more than just an incremental upgrading of the cities organization, infrastructure and the services provided to its citizens. 3

4 Introduction to Smart Cities Need for a multi-disciplinary approach To achieve the challenging goals mentioned above, drastic changes are required that involve a multitude of new technologies relevant to various disciplines e.g. Behavioral science Civil-Architectural engineering Computer Science Economics Electrical, Electronic and Telecommunication engineering Medicine Social science 4

5 5 Introduction to Smart Cities On the adjective smart Such technologies are nowadays labeled with the ubiquitous word smart. Technology has always been smart à this adjective serves to underline the widespread use of Information and Communication Technologies (ICT), sensors and intelligence, e.g. software embedded in the various parts, components and infrastructures forming an urban area. In this picture we label people living in the city or using its facilities as smart as well, in that they own portable smart devices communicating with existing ICT networks, which are instrumental to the accomplishment of such a goal.

6 6 Introduction to Smart Cities Some definitions The Smart Cities Council is a for-profit, Partner-led association for the advancement of the smart city business sector. It promotes smart cities in general and our Partners in particular. Allied Telesis Alstom Grid Bechtel Cisco Cubic Transportation Systems - Enel GE IBM Itron, Inc. MasterCard Mercedes-Benz Microsoft Ooredoo Qualcomm S&C Electric Co. Schneider Electric

7 7 Introduction to Smart Cities Some definitions

8 8 Introduction to Smart Cities The definition of the Proceedings of the IEEE We feel that the emerging prototype for a smart city is an urban environment with a new generation of innovative services for business/commerce culture energy distribution environmental monitoring/preservation emergency response (resiliency) food distribution healthcare social activities water distribution waste management frequently interacting with each other thanks to ICT devices and solutions

9 9 Introduction to Smart Cities IEEE Standards

10 10 Introduction to Smart Cities ISO Standards

11 11 Introduction to Smart Cities Reference Smart City paradigm concerning the Engineering/ Computer Science area: interaction between data and infrastructures, processes and people is depicted.

12 12 Introduction to Smart Cities Functional diagram of the Planning and Operation of Smart City processes as a function of citizens (users) active participation. The roles of the Simulation, Analysis and Control phases with relevant enablers (Modeling and Technologies) are embodied.

13 Introduction to Smart Cities Role of ICT Adapted from O. Andrisano et al. Proceedings of the IEEE, SI on Smart Cities, Volume 106, Issue 4 April 2018 ICT infrastructure and its interaction with some of the core components of a Smart City Waste management; Smart Grid; E-mobility; Security; E-health, Waste management; Building and Urbanization and Tourism through Cloud and Fog infrastructures. 13

14 14 Some projects carried out worldwide University of Bologna Adapted from O. Andrisano et al. Proceedings of the IEEE, SI on Smart Cities, Volume 106, Issue 4 April 2018

15 15 Some projects carried out worldwide Spain - University of Seville Upcoming structure and relationships of power systems in the 21st century. Geographical scope of the Smart City project in the western coastal area of Malaga. Adapted from A. Gòmez-Expòsito et al. Proceedings of the IEEE, SI on Smart Cities, Volume 106, Issue 4 April 2018

16 16 Smart Grids as enablers for Smart Cities Adapted from A. Gòmez-Expòsito et al. Proceedings of the IEEE, SI on Smart Cities, Volume 106, Issue 4 April 2018

17 17 Some projects carried out worldwide University of Bologna Salt loaded masonry wall after 1 month: comparison between the experimental campaign and the simulated water saturation degree Sketch of the multi-scale approach for the analysis of large-scale masonry walls Adapted from O. Andrisano et al. Proceedings of the IEEE, SI on Smart Cities, Volume 106, Issue 4 April 2018

18 18 Some projects carried out worldwide University of Bologna Adapted from O. Andrisano et al. Proceedings of the IEEE, SI on Smart Cities, Volume 106, Issue 4 April 2018 Mobility of citizens between points of interest automatically evaluated from mobility traces obtained through the ParticipAct app in (a) Bologna and (b) Florianopolis. (a) (b) Mobil Crowd Sensing (MCS) process model and deployment over Smart Cities.

19 Some projects carried out worldwide Boston - MIT Adapted from T.J. Matarazzo et al. Proceedings of the IEEE, SI on Smart Cities, Volume 106, Issue 4 April (a) Plan and Elevation views of a segment (Spans 13 19) of the Harvard 380 Bridge with fixed sensor network layout; (b) Photograph of the fixed sensors on the East side 381 of the Harvard Bridge; (c) Photograph of the reference sensor and smartphones on a vehicle 382 dashboard

20 20 Introduction to Smart Cities Concluding Remarks The SC paradigm represents probably the most promising approach to tackle the challenges posed by modern urban areas, whose population is expected to double by On the other hand, rigorously speaking, there is no single generally acceptable definition for a Smart City. All the available ones have however one feature in common: the multidimensional and multidisciplinary nature of what a Smart City represents. The number of disciplines involved can vary from case to case, as well as the nature of the models and algorithms used; this applies also to the data processing and optimization techniques. Smart Grids represent a major enabler for the implementation of the concept of Smart City

21 21 Introduction to Smart Cities Concluding Remarks Few research areas other than SC require a close cooperation among researchers with different, complementary interests. The case of e- mobility, for instance, calls for technical skills in the areas of ICT, electric power networks/smart grids, electric vehicles, storage systems, and computer co-simulation tools for the integrated representation of systems belongings to heterogeneous domains. Academics with different background not only need to cooperate with each other and with industrial players more than for any other technical challenge, but they also need to interact and cooperate with local municipality governances and regional communities. The development of relevant standards and business models is of utmost importance.

22 Presenters Gilles Betis has been chairing the IEEE Smart Cities Initiative (smartcities.ieee.org) since He is an independent consultant for Smart Cities. Previously he was Open Data Project Director at the Transdev Digital factory, he lead the Digital Cities action line of EIT Digital ( and held positions of product line manager, marketing manager, solution leader and head of advanced engineering in Thales. Since the end of the eighties, he has been constantly involved with prospective, innovation and design of complex systems. Having an extensive industrial experience in Intelligent Transportation Systems and Smart Cities, he always linked up emerging behaviours and societal needs to innovative technological solutions, allowing smooth adoption by final users. Gilles Betis was graduated in 1987 as an Engineer from Ecole Supérieure d Electricité in France.

23 Presenters Christos G. Cassandras is Distinguished Professor of Engineering at Boston University. He is Head of the Division of Systems Engineering, Professor of Electrical and Computer Engineering, and cofounder of Boston University s Center for Information and Systems Engineering (CISE). He received degrees from Yale University (B.S., 1977), Stanford University (M.S.E.E., 1978), and Harvard University (S.M., 1979; Ph.D., 1982). In he was with ITP Boston, Inc. where he worked on the design of automated manufacturing systems. In he was a faculty member at the Department of Electrical and Computer Engineering, University of Massachusetts/Amherst. He specializes in the areas of discrete event and hybrid systems, cooperative control, stochastic optimization, and computer simulation, with applications to computer and sensor networks, manufacturing systems, and transportation systems. He has published over 400 refereed papers in these areas, and six books. He has guest-edited several technical journal issues and serves on several journal Editorial Boards. In addition to his academic activities, he has worked extensively with industrial organizations on various systems integration projects and the development of decision-support software. He has most recently collaborated with The MathWorks, Inc. in the development of the discrete event and hybrid system simulator SimEvents. Dr. Cassandras was Editor-in-Chief of the IEEE Transactions on Automatic Control from 1998 through 2009 and has also served as Editor for Technical Notes and Correspondence and Associate Editor. He is currently an Editor of Automatica. He was the 2012 President of the IEEE Control Systems Society (CSS). He has also served as Vice President for Publications and on the Board of Governors of the CSS, as well as on several IEEE committees, and has chaired several conferences. He has been a plenary/keynote speaker at numerous international conferences, including the American Control Conference in 2001 and the IEEE Conference on Decision and Control in 2002 and 2016, and the IFAC World Congress in 2017 and has also been an IEEE Distinguished Lecturer.

24 Presenters Carlo Alberto Nucci is full professor and head of the Power Systems Laboratory of the Department of Electrical, Electronic and Information Engineering Guglielmo Marconi of the University of Bologna. He is author or co-author of over 370 scientific papers published on peerreviewed journals or on proceedings of international conferences, of six book chapters edited by IEE, IET (two), Kluwer, Rumanian Academy of Science and WIT press and of a couple of IEEE Standards and some CIGRE technical brochures. He is a Fellow of the IEEE and of CIGRE and has received some best paper/technical international awards, including the CIGRE Technical Committee Award and the ICLP Golde Award. From January 2006 to September 2012 he has served as Chairman of Cigré Study Committee C4 System Technical Performance. Since January 2010 he is serving as Editor in Chief of the Electric Power Systems Research journal, Elsevier. Prof. Nucci is doctor honoris causa of the University Politehnica of Bucharest and member of the Bologna Science Academy. He has served as president of the Italian Group of University Professors of Electrical Power Systems (GUSEE) from 2012 to He is an advisor of the Global Resource Management Program of Doshisha University, Kyoto, supported by the Japanese Ministry of Education and Science. He has represented PES in the IEEE Smart City Initiatives Program since 2014.

25 Smart, Participative, Inclusive And Frugal Cities Gilles Betis OrbiCité, IEEE Smart City Initiative Founding Chair 17 th July 2018

26 China, India and Nigeria are projected to account for 37% of the increase of nearly 2.5 billion people in the urban population by 2050 Seven other countries, the Democratic Republic of Congo, Ethiopia, the United Republic of Tanzania, Bangladesh, Indonesia and Pakistan, and the United States of America, will constitute together another 20% of the total increase in urban population

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31 «The nineteenth century was the century of empires, the twentieth that of nation-states and the twenty-first century will be that of cities» said Wellington Webb, Mayor of Denver, then president of the U.S. Conference of Mayors

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33 Citizen Engagement City Hall Civic Tech Citizens Citizen Participation Citizen Collaboration

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36 Creating and Sharing Value

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38 Positive ecological sustainability Urban settlements should have a deeper and more integrated relationship with nature 1. With energy generated renewably 2. With waterways returned, as much as possible, to their presettlement condition 3. With natural spaces conserved and connected ECOLOGY 4. With urban growth managed and contained 5. With transport oriented to walking, bikes and public systems 6. With food production localized 7. With waste reutilized Positive political governance Urban settlements should have an enhanced emphasis on engaged and negotiated civic involvement 1. With deep deliberative democratic processes 2. With legislation enacted for socially just land-tenure 3. With public support for public non-profit communication services and media POLITICS 4. With political participation going deeper than electoral engagement 5. With basic security afforded to all people 6. With reconciliation between settlers and Indigenous peoples 7. With ongoing ethical debates concerning how we are to live Positive economic prosperity Urban settlements should be based on an economy organized around the social needs of all its citizens (including entrepreneurs) 1. With production organized around local needs 2. With strong financial governance, including participatory budgeting 3. With regulation negotiated publicly 4. With consumption substantially reduced ECONOMICS 5. With workplaces brought closer to residential areas 6. With technology used primarily as a tool for good living 7. With the institution of positive re-distributive processes Positive cultural engagement Urban settlements should actively develop ongoing processes for dealing with the uncomfortable intersections of identity and difference CULTURE 1. With careful public recognition of the complex layers of community-based identity 2. With the development of consolidated cultural activity zones 3. With cultural institutions and public spaces dedicated to projecting crosscutting cultural histories 4. With locally relevant fundamental beliefs woven into the urban fabric 5. With conditions for gender equality pursued in all aspects of social life 6. With the possibilities for facilitated enquiry and learning available to all from birth to old age 7. With public spaces and buildings designed to enhance emotional wellbeing

39 Profile Circle Process Circle

40 Autonomous Collaborative Street Lighting SHSPL System using Bin Packing algorithm in rural areas in Off-Grid environment

41 E-CO DAR For Human Centered Eco Transition E- stands for a smart affordable home using IoT and data analysis to achieve optimal use of its components. Co is for Collaborative multidisciplinary design aiming at taking into account several parameters including households Energy Usage profiling using smart hub and mobiles apps we have developed. DAR is referring to The main idea is to create a contemporary vanguard version of the Moroccan traditional house. One that offers an environment that fulfils the criteria of an autonomous, smart, social, ecological, and energy-efficient construction, while preserving its spirit, basic principles and architectural functionalities.

42 E-douar / Smart Village Living Lab New vision for socio-economic development and citizens empowerment in rural areas with INDH A concept for an open, inclusive and innovative rural world

43 Alphabetization for development in rural areas of Morocco Collaboration UH2C-GreenTIC Morocco/ Avinashlingham University India

44 Thank you for your kind attention

45 SMART CITIES AS CYBER-PHYSICAL SYSTEMS C. G. Cassandras Division of Systems Engineering, Dept. of Electrical and Computer Engineering, Center for Information and Systems Engineering Boston University

46 SMART CITY AS A CYBER-PHYSICAL SYSTEM Privacy Data collection SENSOR NETWORKS Security Control and Optimization Actions Information Processing BIG DATA Safety Decision Making Energy Management Christos G. Cassandras CISE - CODES Lab. - Boston University

47 SMART CITY AS A CYBER-PHYSICAL SYSTEM PHYSICAL Data collection CYBER Control and Optimization Actions Information Processing CYBER Model x(t) Model x x(t) f ( x, u, t) t Decision Making PHYSICAL Christos G. Cassandras CISE - CODES Lab. - Boston University

48 WHAT IS REALLY SMART? COLLECTING DATA IS NOT SMART INFO - JUST A NECESSARY STEP TO BEING SMART PROCESSING DATA TO MAKE GOOD DECISIONS IS SMART ACTION INFO Christos G. Cassandras CISE - CODES Lab. - Boston University

49 SMART CITY PROJECTS - URBAN MOBILITY SMART PARKING Finds optimal parking space for driver + reserves it ELECTRIC VEHICLE (EV) ROUTING AND RECHARGING Optimally routes EVs to minimize travel times + finds optimal charging station + reserves it Christos G. Cassandras CISE - CODES Lab. - Boston University

50 SMART CITY PROJECTS - URBAN MOBILITY TRAFFIC CONTROL Exploit connected vehicles technology: from (selfish) driver optimal to (social) system optimal traffic control TRAFFIC LIGHT CONTROL Real-time, data-driven dynamic traffic light control: Alleviate congestion Reduce pollution and fuel waste Christos G. Cassandras CISE - CODES Lab. - Boston University

51 SMART CITY PROJECTS - URBAN MOBILITY STREET BUMP Detect roadway bumps + classify them + prioritize and dispatch crews Used in Boston SMART AUTONOMOUS CARS NEXTCAR project : Self-driving autonomous cars for minimizing energy consumption: integrate Vehicle Dynamics with Powertrain Control Vehicle control architecture concept Christos G. Cassandras CISE - CODES Lab. - Boston University

52 SMART PARKING iphone app

53 SMART PARKING GUIDANCE-BASED PARKING DRAWBACKS Drivers: May not find a vacant space May miss better space Processing info while driving 30% of vehicles on the road in the downtowns of major cities are cruising for a parking spot. It takes the average driver 7.8 minutes to find a parking spot in the downtown core of a major city. R. Arnott, T.Rave, R.Schob, Alleviating Urban Traffic Congestion City: Imbalanced parking utilization May create ADDED CONGESTION (as multiple drivers converge to where a space exists) Searching for parking Competing for parking Christos G. Cassandras CISE - CODES Lab. - Boston University

54 SMART PARKING BEST PARKING SPOT LEAST DISTANCE from A + LEAST COST + RESERVE IT [Geng and Cassandras, IEEE Trans. on Intelligent Transportation Systems, 2013] Christos G. Cassandras CISE - CODES Lab. - Boston University it

55 SMART PARKING IMPLEMENTATION Parking space availability detection Standard sensors (e.g., magnetic, cameras) Wireless sensor networking Vehicle localization GPS System-Driver communication Smartphone Vehicle navigation system Parking reservation Red/Green/Yellow light system Christos G. Cassandras CISE - CODES Lab. - Boston University

56 SIMULATION CASE STUDY On-street parking spaces Off-street parking spaces Points of interest Christos G. Cassandras CODES Lab. - Boston University

57 KEY CONCLUSIONS % higher parking utilization HIGHER REVENUE, LOWER CONGESTION 2. % drivers searching for parking (wandering) < 2% HIGHER REVENUE, LOWER CONGESTION 3. 50% reduction in parking time under heavy traffic LOWER CONGESTION, LESS FUEL, DRIVER COMFORT Christos G. Cassandras CODES Lab. - Boston University

58 STREET BUMP: DETECTING BUMPS THROUGH SMARTPHONES + DATA ANALYTICS iphone app 2014 IBM/IEEE Smarter Planet Challenge prize

59 STREET BUMP PROCESSING BIG DATA Detect obstacles using iphone accelerometer and GPS no infrastructure needed Send to central server through Street Bump app Process data to classify obstacles: Anomaly detection and clustering algorithms, similar to cybersecurity problems Detect actionable obstacles Prioritize and dispatch Smart City crews to fix problems: DATA-DRIVEN DYNAMIC RESOURCE ALLOCATION Christos G. Cassandras CISE - CODES Lab. - Boston University

60 STREET BUMP PROCESSING BIG DATA Methodologies used: Anomaly detection, Machine Learning algorithms Bump signal signature analysis: REGULARITY METRIC Bump signal randomness content: ENTROPY METRIC NON-ACTIONABLE (Flat Casting) ACTIONABLE (Pothole) Christos G. Cassandras CISE - CODES Lab. - Boston University

61 STREET BUMP ANOMALY INDEX RANKED LIST TOP-10 ACTIONABLE OBSTACLES Christos G. Cassandras CISE - CODES Lab. - Boston University

62 ADAPTIVE TRAFFIC LIGHT CONTROL

63 NETWORK-WIDE TRAFFIC LIGHT CONTROL Automatically adapt red/green light cycles based on observed data Predict and alleviate congestion over entire urban network Reduce waiting times, congestion Reduce pollution and fuel waste Christos G. Cassandras CISE - CODES Lab. - Boston University

64 TRAFFIC CONTROL The BU Bridge mess, Boston, MA (simulation using VISSIM)

65 WHY CAN T WE IMPROVE TRAFFIC EVEN IF WE KNOW THE ACHIEVABLE OPTIMUM IN A TRAFFIC NETWORK??? Because: Not enough controls (traffic lights, tolls, speed fines) No chance to unleash the power of feedback! Not knowing other drivers behavior leads to poor decisions (a simple game-theoretic fact) Drivers seek individual (selfish) optimum, not system-wide (social) optimum PRICE OF ANARCHY (POA) Christos G. Cassandras CISE - CODES Lab. - Boston University

66 GAME-CHANGING OPPORTUNITY: CONNECTED AUTONOMOUS VEHICLES (CAVs) FROM (SELFISH) DRIVER OPTIMAL TO (SOCIAL) SYSTEM OPTIMAL TRAFFIC CONTROL THE INTERNET OF CARS NO TRAFFIC LIGHTS, NEVER STOP [Zhang et al, Proceedings of the IEEE, Special Issue on Smart Cities, 2018] Christos G. Cassandras CISE - CODES Lab. - Boston University

67 WHO NEEDS TRAFFIC LIGHTS? With traffic lights With decentralized control of CAVs One of the worst-designed double intersections ever (BU Bridge Commonwealth Ave, Boston, MA) Christos G. Cassandras CISE - CODES Lab. - Boston University