Rawls College 2014 Symposium on Big Data, April 25, 2014 Co-organized by CAC & College of Engineering & FJU

1. Rawls College 2014 Symposium on Big Data, April 25, 2014 Co-organized by CAC & College of Engineering & FJUT & Coordinated by CAABI Theme: Innovate Research and Business with Big Data Examples of ITS in Finland andResearch opportunities under ISSUE-TM – the International Research Forum on Intelligent Sensing and Services in Urban Environment for Traffic and MobilityMatti Hämäläinen, DIGILE & Aalto UniversityJyrkiNummenmaa, University of Tampere JukkaRiekki, University of Oulu DIGILE- The Finnish Strategic Centre for Science, Technology and Innovation in Digital BusinessCoordinator of the China-Finland ICT Alliance

2. Introductions Dr. Matti Hämäläinen, Director, China cooperation, DIGILE - The Finnish Strategic Centre for Science, Technology and Innovation in Digital Business, Coordinator of the China-Finland ICT Alliance and a Visiting Professor, Aalto University, Department of Computer Science and Engineering / SoberIT. Matti facilitates Finland’s international R&D&I cooperation in digital technologies and services with focus on China. The work covers both technology and applications in areas such as urbanization (including “city-on-demand” concepts and intelligent traffic and mobility in urban environment), ageing society, health and wellbeing, environmental and energy monitoring, financial services, future media, and education solutions. Accordingly, his research is related to service concepts, business models and technical enablers in “Everyday Sensing” and “Design Embedded in Life” with applications in wellbeing (“smart life”), ageing society services and intelligent home. Since 1994, he has been active in China cooperation including preparing one of the first EU-China joint projects in Internet-based education and e-services. He has been an entrepreneur in the early stage of e-learning, mobile data collection and mobile games with over 60 international operator and media companies as customers. Mr. Hämäläinen has PhD in information systems form The University of Texas at Austin in 1996. Prof. JyrkiNummenmaareceived his PhD in Computer Science in 1995, and he has served as professor computer science at the University of Tampere since 1997 (fixed term, tenure since 2003). His research experience includes algorithms, software development, and data management and analysis, with traffic data as the latest application area. Currently he is the head of the Center for Research on Information and Systems at the School of Information Sciences at the University of Tampere. He has 57 peer-reviewed scientific publications. His administrational experience includes 8 years as a Department Head, 2 years as Dean, and 3 years as University Board member in the new Finnish University administration system. At present he is the chair of University Collegium (a new administrational body which, e.g., nominates the external University Board memebers). He has visited e.g. University of Edinburgh for 1 year, University of Chile for 2 months, and made several visits from 1 to 4 weeks to Sichuan University and Shanghai Jiao Tong University. Prof. Nummenmaa leads a group that does traffic data research in collaboration with Tampere University of Technology, University of Oulu, and the City of Tampere, and he coordinates Digile’sInternational Research Forum on Intelligent Sensing and Services in Urban Environment for Traffic and Mobility (ISSUE-TM) Prof. JukkaRiekkiis Professor in the Department of Computer Science and Engineering and Dean at the Faculty of Information Technology and Electrical Engineering, University of Oulu, Finland. He has over 170 peer-reviewed articles. His main research interests are in interactive, context-aware systems serving people in their everyday environment. He leads the Interactive Spaces research group (www.oulu.fi/cse/ispaces). The group studies in several projects physical user interfaces, sensor networks, and Internet of Things. Current work on physical user interfaces focuses on NFC and learning applications. IoT research concentrates on lightweight software architectures and knowledge representations connecting even the smallest IoT nodes to the Cloud and Semantic Web. The work on sensor networks focuses on collecting rich sensor data from the City of Oulu and on analyzing interesting phenomena from this data, the current focus is on traffic applications. The research group collaborates actively with many Finnish and international companies and universities.

3. Notes on European and Finnish perspective for ITS • The world’s first intelligent transport strategy was published in Finland in 2009 • The second generation strategy was published in 2013 http://www.lvm.fi/publication/4149649/towards-a-new-transport-policy-intelligence-in-transport-and-wisdom-in-mobility-finland-s-second-generation-intelligent-strategy-for-transport • In Finland, environmental strategy for traffic, 2013-2020 (published 2013): • Includes the central targets for environmental work, an update for the ministry’s climate politics program (ILPO) and management policies for all modes of transportation • European action plan on Urban Mobility (2009) • Proposes measures, for example, improving the collection and the availability of comparable, relevant and timely data for each transport mode, to encourage and help local, regional and national authorities in achieving their goals for sustainable urban mobilityhttp://ec.europa.eu/transport/themes/urban/urban_mobility/action_plan_en.htm • Finland ITS networks: ITS Factory (Tampere), ITS Finland, Fintrip, TransSmart, etc. • The next ITS European congress will be held in Finland in June, 16-19, 2014 • http://its-finland.fi/index.php/fi/tapahtumat/10th-its-european-congress.html

4. City of Tampere and University of TampereProject examples

5. Public Transportation • City of Tampere • Position of each bus every second • Other cities do not have the same quality yet. • Small city: 850 MBs of daily ”raw” data unwrapped fromXML -> goes easilydown to 300 MBs of numericvalues. • The City of Tampere data is open – thereareAppsusingit and itcanbestoredby ”anyone” Data warehousing, cleaning, analysing, and distributing the data that is opening.

6. Analysis Targets • Analysing the history data to providepredictivemodels of the traffic • E.g. intersectionmodelingmodules for trafficsituationawareness • Implementingtools for identifyinginefficiencies in currenttrafficsystem • Trafficsignalledintersectionsthatneedtuning • Public transportationlinesthatcan’tkeepschedules • Road segmentsthatarecrowdedand slow

7. Example: where and when the busesaremostdelayed on workingdays? 8 AM – 9 AM 3PM – 4 PM 5 PM – 6 PM 4 PM – 5 PM

8. Example: Wheredoesline 29 getdelayedwhenheading West? In addition to the center of the city, therearethreeintersectionsthataremostlikely to causedelays.

9. Example: Street of Hämeenkatu Line 29, heading West Line 28, heading West (until Keskustori) Line 25, heading West

10. Example: The effect of rushhours on busschedules Medians of timesspentbetweenthesetwostops at differenttimes of workingdays (medianstakenoverobservations of ~30 working days/6 weeks)

11. Example: Busconnectionsuccessbased on history data • Based on priorknowledge, • Will the busconnectionproposedby the routeplannersucceed? • If the latterbus is known to belate, couldyourisk and take a laterdeparture of the firstline?

12. Traffic • City of Oulu (and later Tampere) • Merging data frommultiplesources • Analysis of trafficsituation • Further traffic data being and becomingavailable: • Trafficweather data • Taxi traffic data • Maintenance data (maintenance vehicles are tracked e.g. clearing snow from the roads. • Parking data (roadside parking plus on some level also • Identification of bicycles and pedestrians • Traffic light data: • Data from sensors identifying cars passing by • Data showing signal status Data warehousing, cleaning, analysing, and distributing the data that is opening

13. Mobility Why, when, howpeoplemove? AND Makingpeopleaware of the choices and options. Mobile and /or connected citizens • Data on: • People’s mobility • Crowdsourcing for traffic data • Understanding mobility (based on above) • Mobility routes and schedules • Understandingmobility as a whole • Services: • Betterpublictransportation • Tripchaining • Services / marketing for mobile citizens. Data warehousing, cleaning, analysing, and distributing the data.

14. Smart City Citizens’ activeparticipation. Secure, economical,efficient city wherecitizensparticipateactively. Mobile and /or connected citizens • Data on: • Social media • eDemocracy / services • Enivironmental data / sensor data • Services: • Smart, integratedservices, e.g. lightning,.. Data warehousing, cleaning, analysing, and distributing the data

15. City of Oulu and University of OuluProject examples:Data to Intelligence D2I Research Program of DIGILEEveryday Sensing Project of China-Finland ICT Alliance Phase IIJukkaRiekki, Dean, ProfessorInteractive Spaces/Dept. Computer Science and EngineeringFaculty of Information Technology and Electrical EngineeringUniversity of Oulu

16. D2I Traffic & Data to Intelligence • D2I Traffic research project focuses on • Data-intensive traffic-related services • Specifically on data cleaning, fusion and refinement realized in real-world pilots • D2I Traffic is building Oulu Traffic Pilot to collect rich data sets and to develop and test advanced ITS services in a realistic environment • The project is part of DIGILE's Data to Intelligence research programme (www.datatointelligence.fi) • DIGILE is one of the Finland’s Strategic Centres for Science, Technology and Innovation • In 2013, over 30 Finnish partners: companies, unversities, research organizations

17. Removing the silos • The emphasis is shifting from individual small-scale applications • To cover safety, eco-friendly and economical issues • To fully-fledged, large-scale services related to these themes • The traditional Data provider - Service provider silo structures need to be removed Service SERVICE FOR FLEET MANAGER SERVICE FOR AUTHORITY NOVEL SERVICE FOR DRIVERS: BRAKING DISTANCE ESTIMATOR Data Processing DETECT ROAD WEATHER DETECT SPEED DETECT DISTANCE BETWEEN VEHICLES, DETECT SPEED DETERMINE ROAD FRICTION Data, sensors WEATHERSTATION LASER DISTANCE SENSOR Data fusion

18. Oulu Traffic Pilot • Actual streaming urban data from several sources • Dedicated companies and true business opportunities • Interesting research questions for streaming data processing • Recovery from failure and data preprocessing • Data fusion and prediction: Sensornetwork data + open data sources(e.g. weather & digiroad) + Social Network Services analysis (sentiment etc.)

19. TrafficSense – Energy Efficient Traffic with CrowdsensingAalto University City of Helsinki Metropolitan region http://cse.aalto.fi/en/research/groups/distributed_systems/projects/trafficsense/

20. TrafficSense – Energy Efficient Traffic with Crowdsensing • Traffic accounts for about ¼ of peoples’ total energy consumption. • TrafficSense studies how to save energy by advising users on better travel options based on the real-time traffic information collected from mobile devices and traffic-related information sources. • In addition, the information gathered can, in the longer term, also enable more energy efficient transportation services and business models.

21. TrafficSense – Energy Efficient Traffic with Crowdsensing:Consortium is composed of six research groups within the Aalto University: • Department Information and Service Management, School of Business (BIZ) • Information and Service Management (ISM) • Helsinki Institute for Information Technology (HIIT) • Parsimonious Modelling Group (PM) • Department of Computer Science and Engineering, School of Science (SCI) • Distributed Systems Group (DSG) • IS and Service Engineering Group (ISSEG) • Intelligent Traffic Systems Group (ITSRG) • Department of Civil and Environmental Engineering, School of Engineering (ENG) • Transportation Engineering (TE)

22. TrafficSense – Energy Efficient Traffic with Crowdsensing:The Research topics in TrafficSenseproject (in red) • The improving sensing capabilities and the increasing penetration of smart phones has recently made this kind of service a practical opportunity. • Other enablers to TrafficSense are the changes in the transportation environment at Helsinki Region - the demand responsive transportation system (Kutsuplus), the remote parking arrangements, and ridesharing systems - and the availability of new traffic-related information sources: maps, journey planners (Reittiopas), traffic incident reporting (Digitraffic), & bus tracking of HSL.

23. China-Finland ICT Alliance has launched an International Research Forum on Intelligent Sensing and Services in Urban Environment for Traffic and Mobility (ISSUE-TM)Open forum for interested partners to join based on joint interests and contributions

24. An International Research Forum on Intelligent Sensing and Services in Urban Environment for Traffic and Mobility (ISSUE-TM) Background and motivation: • China-Finland Strategic ICT Alliance was established to facilitate joint Research, Development and Innovation (R&D&I) in ICT and in digital services by combining the complementary capabilities of China and Finland. • ICT Alliance also promotes implementationof pilots for large scale real-life experimentation. In addition to providing relevant experiences and data theyalso provide context for studying viable business models and for examining opportunities for commercial cooperation. • Sensing, social media and data analysis are among focus areas being studied for creating innovative solutions and new business opportunities e.g. in traffic and urban mobility services, and there are several projects already active in China-Finland cooperation or planning to establish such cooperation. Objectives: To boost research collaboration in this area an International Research Forum on Intelligent Sensing and Services in Urban Environment for Traffic and Mobility (ISSUE-TM) has been launched in February 2014 by ICT Alliance. It aims at making better use of synergies and enabling sharing of data and results by: • Devising jointly agreed common “core” principles , data items and formats for data collection and data sharing, and agreeing on sharing of experiences from different experimentation approaches for making best use of the complementary data available in Finland /Europe and in China respectively. • Sharing access to data sets and/or analysis results of pilots in Finland and in China, such as City of Oulu and City of Tampere, and the data sets being collected by the Chinese Academy of Sciences, and in Fuzhou and Beijing. • Preparing for applying for a cooperative EU project in 2014 (e.g. Horizon 2020) • Arranging  co-located ISSUE-TM Forum events in Finland and in China and setting up online collaboration (e.g. a WeChat Forum). The events will be organized both in the context ICT Alliance events and to take place around key events such as The 10th ITS European Congress in Helsinki, 16-19 June 2014. • Arranging visiting expert talks as well as involving PhD level exchange researchers in the Forum activities.

25. ITS is a focalarea in China-Finland Alliance Phase II jointprojects*half of the projectsarerelatedto IntelligentSensing and Services in Urban Environment for Traffic and Mobility EverydaySensing (Cloud, Iot, Data analysis, and social media)University of Oulu, Aalto University, University of Helsinki, Shanghai Jiaotong University, Tsinghua University, BUPT, and Huazhong University of Science and Technology Sensing City Traffic Aalto University and Chinese Academy of Sciences Energy-Efficient Wireless Networks and Connectivity of Devices – Densification Tampere University of Technology, University of Oulu, VTT, Aalto University, BUPT, Southeast University (SEU), WICO, University of Electronic Science and Technology (UESTC), Huazhong University of Science and Technology (HUST), University of Science and Technology of China (USTC), and Harbin Institute of Technology (HIT) Energy-Efficient Wireless Networks and Connectivity of Devices – Systems Aalto University, Tampere University of Technology, BUPT, Southeast University (SEU), WICO, University of Electronic Science and Technology (UESTC), Huazhong University of Science and Technology (HUST), University of Science and Technology of China (USTC), and Harbin Institute of Technology (HIT) Finland’s Enhanced Navigation using COMPASS/Beidou Signals Geodetic Institute, GNSS Research Center (GRC) at Wuhan University, and Chinese Antarctic Center of Surveying and Mapping (CACSM) Finnish-Chinese Green ICT R&D&I Living Lab for Energy Efficient, Clean and Safe Environments VTT, Tampere University of Technology, Tsinghua University, Dalian University of Technology, Chongqing University, Xi'an University of Architecture & Technology, and Shenyang Jianzhu University “Green Campus” *Phase II is fundingfrom the Finnish side includes, Tekes “Finland-ChinaResearch Call” on ICT & Smart City pilots (approx. 2,4 MEUR). In addition to universitiesthe projectsinvolveseveralindustrypartners in Finland.

26. Contacts for the ISSUE-TM Research Forum Prof. JyrkiNummenmaa, University of Tampere,jyrki.nummenmaa(at)uta.fi Coordinator of the “City of Tampere Intelligent Traffic” researchprojects Prof. JukkaRiekki, University of Oulu, jukka.riekki(at)oulu.fi Coordinator of the EverydaySensingproject and D2I resreachprogramtrafficproject Dr. Timo Nyberg, Aalto University, timo.nyberg(at)aalto.fi Coordinator of the Sensing City Trafficproject Coordinator of the China - Finland ICT Alliance: Matti Hämäläinen, Director, DIGILE, and Prof. at Aalto University matti.hamalainen(at)digile.fi Contacts for Chinese activities in ISSUE-TM: Prof. Zhangxi Lin, TTU and SWUFE Prof. FuminZou, Fujian University of Technology, fuminzou(at)ngi.fj.cn Coordinator of the FujianTrafficproject Thank You!