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Assignment 2- Smart City

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1 de Jul de 2019
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Assignment 2- Smart City

  1. SMART CITY ESP Assignment 2 Truong Quang Tung (m5222101) Nguyen Hoang Anh (m5222110) Manoj Poudel (m5212201)
  2. CONTENT ❖ Introduction to Smart City • Definition with concept mapping • Why Smart City is interesting ❖ Main components of Smart City • Internet of Things • Big Data ❖ Technology: Video analytics towards Vision zero ❖ Challenges and Difficulties ❖ Future Smart City ❖ Conclusion ❖ References
  3. INTRODUCTION TO SMART CITY Definition • Smart City - incorporates information and communication technologies. • To enhance the quality and performance of urban services. • Such as energy, transportation and utilities - to reduce resource consumption, wastage and overall costs. • Smart city – are hyper-connected cities - Internet of things (IoT)- using sensors - to collect homogeneous data. • Coordinating data collection and analysis across systems and sectors. • Technologically equipped to improve the lives of their residents.
  4. Concept mapping https://www.mindmeister.com
  5. Smart City for the general public • Characteristics: uses Information Technologies to: • More efficiently use physical infrastructure • Effectively engage with people in local governance • Learn, adapt and innovate • What is the main purpose of smart cities? Improving the life of their citizens. INTRODUCTION TO SMART CITY (cont)
  6. Reduces Environmental Footprint Improves Transportations Increases Digital Equality More economic development opportunities Upgrades Infrastructure Enhances Public Security Smart City for the general public • Benefits of Smart City INTRODUCTION TO SMART CITY (cont)
  7. Smart City for computer science/engineering students • Some common goals among students? • Expand knowledge and training. • Improve work performance. • Attain a higher job role. • For computer science/engineering students? • Interested in new, innovating technologies. • Wants job opportunities that deals with using and making new applications. INTRODUCTION TO SMART CITY (cont)
  8. • Designs infrastructure, protocol • Manages applications • Gives job opportunities • Offers professional workplace/infrastructure Needs: • Stable jobs • Good facilities • Innovations Needs smart people with IoT knowledge Relationship between Smart City and computer scientists/engineers INTRODUCTION TO SMART CITY (cont)
  9. IOT IN SMART CITY • What is IoT? • A system of computing devices, mechanical and digital machines, objects, animals or people that: • Has an unique identifier (UID) • Has the ability to transfer data over a network without requiring human help. • Fundamental characteristic of smart cities: Collect and analyze data to efficiently manage resources → IoT is the solution
  10. Control Flow Data Flow IOT IN SMART CITY (cont) Outline of an IoT System
  11. * Image source: https://www.scnsoft.com/blog/iot-systems-classification Data is taken using sensors: Surveillance camera, thermal sensor, etc. → Assesses performance of equipment → Proactive maintenance → Uncovers new patterns and tendencies → identifies the problems before the damage is done IOT IN SMART CITY (cont)
  12. BIG DATA IN SMART CITY Big Data helps uncover patterns and extract valuable information from data collected by IoT * Image source: https://dzone.com/articles/how-big-data-has-the-biggest-impact-in-smart-citie
  13. BIG DATA IN SMART CITY (cont.) Sharing data while maintaining privacy is the key in Big Data management * Image source: https://digitalguardian.com/blog/tackling-gdpr-challenge-4-privacy-design-and-default , http://veterinaryleadershipinstitute.org/balance- is-key/ , http://beyondplm.com/2011/07/14/top-3-reasons-why-data-sharing-is-important-for-plm/
  14. TECHNOLOGY: VIDEO ANALYTICS TOWARD VISION ZERO Road traffic injuries is among top 10 leading causes of death * Image source: https://www.psrc.org/sites/default/files/peer1707-pres-videoanalytics.pdf
  15. TECHNOLOGY: VIDEO ANALYTICS TOWARD VISION ZERO (cont) • Traditional crash reporting process is ineffective in preventing accidents * Image source: https://www.psrc.org/sites/default/files/peer1707-pres-videoanalytics.pdf
  16. * Image source: https://www.psrc.org/sites/default/files/peer1707-pres-videoanalytics.pdf Reduce minor conflicts Significant fall in serious accidents Don’t wait for crashes to happen! TECHNOLOGY: VIDEO ANALYTICS TOWARD VISION ZERO (cont)
  17. Leverage city’s traffic camera system to: ➢ monitor counts and travel speed of all road user groups (vehicle, pedestrian, and bicycle) ➢ Document the directional volume of all road user groups in an intersection ➢ Assess unsafe “near miss” trajectories and interactions between all road user groups. * Image source: https://www.psrc.org/sites/default/files/peer1707-pres-videoanalytics.pdf TECHNOLOGY: VIDEO ANALYTICS TOWARD VISION ZERO (cont)
  18. * Image source: https://www.psrc.org/sites/default/files/peer1707-pres-videoanalytics.pdf • Captured videos are sent to cloud server for analysis TECHNOLOGY: VIDEO ANALYTICS TOWARD VISION ZERO (cont)
  19. * Image source: https://www.psrc.org/sites/default/files/peer1707-pres-videoanalytics.pdf Object detection by Deep Neural Networks TECHNOLOGY: VIDEO ANALYTICS TOWARD VISION ZERO (cont)
  20. * Image source: https://www.psrc.org/sites/default/files/peer1707-pres-videoanalytics.pdf Trajectory detection and turning movement counts TECHNOLOGY: VIDEO ANALYTICS TOWARD VISION ZERO (cont)
  21. * Image source: https://www.psrc.org/sites/default/files/peer1707-pres-videoanalytics.pdf Near-miss event detection TECHNOLOGY: VIDEO ANALYTICS TOWARD VISION ZERO (cont)
  22. * Image source: https://www.psrc.org/sites/default/files/peer1707-pres-videoanalytics.pdf • Accomplishment1: Vision technologies achieve high performance in the sample traffic videos Table 1: Object classification accuracy Table 2: Turning movement count accuracy TECHNOLOGY: VIDEO ANALYTICS TOWARD VISION ZERO (cont)
  23. * Image source: https://www.psrc.org/sites/default/files/peer1707-pres-videoanalytics.pdf • Accomplishment 2: A prototype end-to-end system is built and able to operate at real-time • Accomplishment 3: Pilot deployment of end-to-end system (running on servers provided by Microsoft) in the City of Bellevue traffic control center. The system will run off of a live feed. TECHNOLOGY: VIDEO ANALYTICS TOWARD VISION ZERO (cont)
  24. TECHNOLOGY: VIDEO ANALYTICS TOWARD VISION ZERO (cont) https://www.youtube.com/watch?v=rTAOwvU6Yj8
  25. CHALLENGES AND DIFFICULTIES • Existing Infrastructure • Digital Security • Privacy Concerns • Educating and engaging the community • Technology challenge with coverage and capacity • Funding and Business models
  26. FUTURE SMART CITY • Smart Data • Beating heart of the smart city • Collecting data from residents, vehicles, infrastructure etc.
  27. FUTURE SMART CITY (cont) • Smart Transportation • Fully automated vehicles • Capable of understanding their surrounding environment to make decision
  28. FUTURE SMART CITY (cont) • Smart Energy • Clean energy sources to power its city • Convert street lights with LEDs to reduce energy
  29. FUTURE SMART CITY (cont) • Smart Infrastructure • With the data collected, city planners and architects could create buildings that are optimized for people based on previous data. • Tested on citizens to ensure that they truly benefit
  30. * Image source: http://www.alivio.me/ FUTURE SMART CITY (cont) • Smart IoT with Artificial Intelligence (AI) • The device that bring everything together with help of AI. • Cloud Computing: The Future of IoT • Digital intelligence making life safer and more efficient • Predictive Maintenance Boost up by IoT
  31. CONCLUSION • Smart City – future of urban cities • IoT and Big Data play an important role in Smart City • IoT: connect devices and collect data • Big Data: extract useful information from data • Technology: Video Analytics towards Vision Zero • Smart system analyzing traffic videos to prevent traffic accidents • Already installed in Bellevue city with promising results • Many challenges and difficulties remain • Many future works to accomplish Smart City
  32. REFERENCES • https://www.microsoft.com/en-us/research/wp- content/uploads/2017/05/ITE_Journal_March_2017_Cover-VAVZ.pdf • https://medium.com/dataseries/big-data-and-smart-cities-why-we-need-them-now-a194b2498fb1 • https://blogs.unity3d.com/2018/01/23/designing-safer-cities-through-simulations/ • https://en.wikipedia.org/wiki/Accident_triangle • www.scnsoft.com/blog/iot-systems-classification • https://medium.com/datadriveninvestor/4-stages-of-iot-architecture-explained-in-simple-words- b2ea8b4f777f • https://www.masterstudies.com/article/Why-Smart-Cities-and-Engineers-are-a-Perfect-Fit/
  33. THANK YOU FOR YOUR ATTENTION
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