Seminar: [Nov 30] Recent Advanced Technologies in ITS

ITSS_LOGOIEEE Intelligent Transportation Systems Society (ITSS) Workshop 2015 – Recent Advanced Technologies in ITS

Date & Time: Monday 30 November 2015, 2pm
Venue: Franklin at Level 11, Connexis South Tower, 1 Fusionopolis Way, Singapore 138632

IEEE Intelligent Transportation Systems Society (ITSS) Singapore Chapter has the pleasure to invite you to attend the ITSS Workshop 2015 – Recent Advanced Technologies in ITS.

Program
2:00pm – 2:10pm Opening Address Dr. Huaqun GUO
Chair, ITSS Singapore Chapter
2:10pm – 3:00pm Autonomous Vehicle in I2R Mr Boon Siew HAN
Institute for Infocomm Research
3:00pm – 3:50pm Machine Learning for Intelligent Transportation Systems Prof Justin Dauwels
Nanyang Technological University
3:50 pm – 4:40pm Cyber-Physical Secure Electric Vehicle Charging System in Smart Grid Dr. Jianying ZHOU
Institute for Infocomm Research
4:40pm – 5:30pm Positioning in an Urban Environment Dr. Chee Wei ANG
Institute for Infocomm Research
2:00pm – 6:00pm Recruitment of ITSS New Members
6:00pm Dinner

Recruitment of ITSS New Members
All new ITSS members who sign up on the spot or before the workshop from 19 Nov 2015 to 30 Nov 2015 will receive a free ITSS T-shirt or a Thumb Drive. In addition, the new ITSS student members may apply for the sponsorship.

Registration by 25 November 2015
For catering purpose, please kindly register via https://meetings.vtools.ieee.org/meeting_registration/register/37163.

Detail of Program

1. Autonomous Vehicle in I2R
Speaker: Mr Boon Siew HAN, Institute for Infocomm Research

2. Machine learning for intelligent transportation systems
Speaker: Prof Justin Dauwels, School of Electrical & Electronic Engineering (EEE), Nanyang Technological University

Synopsis
Advanced sensing and surveillance technologies can collect traffic information from various sources with high temporal and spatial resolution. Recorded data is essential for many real-time applications related to traffic management systems. However, the volume of the data collected severely limits the scalability of these systems for large networks.

In this talk, we consider the problems of compression, estimation and prediction in the context of large and diverse networks. Although methods such as principal component analysis (PCA) can efficiently compress traffic data sets, the low-dimensional models created by these methods are not readily interpretable. In this study, we propose an alternative approach to compress the recorded data and enhance the scalability of traffic management systems. We compress the network by representing it in terms of a small subset of the road segments present in the network; this is achieved by applying column-based matrix decompositions (a.k.a. CX-decomposition). This formulation allows us to efficiently store collected data in an intuitive way. Furthermore, we utilize the compressed representation to estimate the current state of the network by collecting data from a small subset of road segments. Similarly, we perform traffic prediction for the whole network, by developing prediction models for only the representative subset of road segments. For the analysis, we consider a large network comprising 17,967 road segments in Singapore.

Numerical results show that our method can achieve competitive compression performance compared to PCA. Results further demonstrate significant reduction of the computational complexity of large-scale prediction. This work is in collaboration with Prof. Patrick Jaillet (MIT) and is funded by NRF through the SMART Future Mobility program.

Speaker’s Biography
Justin Dauwels is an Assistant Professor with School of Electrical & Electronic Engineering (EEE) at Nanyang Technological University (NTU). He is also the Deputy Director of ST Engineering-NTU Corporate Lab and the Director of Neuroengineering Program at the School of EEE. His research interests are in Bayesian statistics, machine learning, intelligent transportation systems, and computational neuroscience.

Prior to joining NTU in 2010, Justin was a research scientist during 2008-2010 in the Stochastic Systems Group (SSG) at the Massachusetts Institute of Technology, led by Prof. Alan Willsky. He received postdoctoral training during 2006-2007 under the guidance of Prof. Shun-ichi Amari and Prof. Andrzej Cichocki at the RIKEN Brain Science Institute in Wako-shi, Japan. He obtained his PhD degree in electrical engineering from the Swiss Polytechnical Institute of Technology (ETH) in Zurich in December 2005.

The research of his lab has been featured by BBC Click/World News, Singapore Straits Times, national TV, and numerous technology news websites. Recent outcomes of his lab’s research include real-time algorithms for large-scale urban traffic prediction; real-time algorithms for analysing human social behaviour; real-time noise-resilient algorithms for phase imaging; novel data analytics for biomedical signals; tools for large-scale modelling of extreme events.

3. Cyber-Physical Secure Electric Vehicle Charging System in Smart Grid

Speaker: Dr. Jianying ZHOU, Institute for Infocomm Research

Synopsis
Smart Grid is the modernization of the existing power grid using digital technology in order to derive a number of benefits such as energy efficiency, security and reliability of power supply, and integration of electricity generated from renewable sources. One of the anticipated applications of Smart Grid is the introduction of the plug-in Electric Vehicle (EV). We face two challenges in this application. One is the impact of potential peaks (either accidental or malicious) on Smart Grid caused by connecting so many new and very large appliances to the grid. Another challenge is finding a way to take advantage of these new sources of distributed power storage, such that grid operators can draw upon this new power supply when needed. This requires a secure and reliable communication infrastructure to support monitoring, control and management of the EV charging infrastructure in Smart Grid. In this talk, I will present the cybersecurity challenges for the EV ecosystem in Smart Gird, introduce the EV cybersecurity architecture, and demonstrate a cyber-physical secure EV charging system.

Speaker’s Biography
Dr. Jianying Zhou is the head of Infocomm Security Department at Institute for Infocomm Research. He received PhD in Information Security from Royal Holloway, University of London. His research interests are in applied cryptography, computer and network security, cyber-physical security, mobile and wireless security. He has published over 200 referred papers at international conferences and journals, and received ESORICS’15 best paper award. He is a co-founder and steering committee member of International Conference on Applied Cryptography and Network Security (ACNS). More info at http://icsd.i2r.a-star.edu.sg/staff/jianying/.

4. Positioning in an Urban Environment

Speaker: Dr. Chee Wei ANG, Institute for Infocomm Research

Synopsis
Multi-modal positioning can be used in GNSS-challenged environments such as urban canyons and indoors. Sensors such as accelerometer, gyroscope, magnetometer etc. are becoming inexpensive due to proliferation of smart-phones. By combining the measurements from these sensors with WIFI and cellular measurements, location information can be derived. Multi-modal positioning could thus become a feasible solution in complementing GNSS positioning. In this talk, we will present our work on integrating various sensors found on mobile devices to derive the location of the user.

Speaker’s Biography
Dr Ang Chee Wei has been with the Institute for Infocomm Research, A*STAR since 1996. He is currently a Senior Scientist in the institute. He has taken on many roles throughout the years, from research to operational roles like IT manager heading the IT department of the company. His research interests include wireless mesh networking, high-availability systems and reinforcement-learning (Neuro-Dynamic Programming). Some of the projects which he has served as principal investigator include the Central Remote Monitoring for Public Building Systems (CRMS) project with HDB; and Wireless Data Acquisition for Gas Turbine Engine Testing (WIDAGATE) project with Rolls-Royce. Currently he is running the Multi-Modal Positioning in Urban Environment project with IDA and ST. Besides managing projects, he was also actively contributing to the standardisation of IEEE 802.22 (Working Group on Wireless Regional Area Networks; Enabling Broadband Wireless Access Using Cognitive Radio Technology and Spectrum Sharing in White Spaces) and was awarded the IES Prestigious Engineering Achievement Award in 2007. He graduated from NTU with 1st class honours in Electrical and Electronic Engineering in 1996, and obtained his Masters and PhD from NUS in 1999 and 2009 respectively. He is currently a Senior Member of the IEEE.

 


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Please find more photos of this event here: https://goo.gl/photos/NwfCUEy7TEfHqgWj8