Hyderabad: The Indian Institute of Technology-Hyderabad (IIT-H) has launched an ‘M2Smart Project’ Testbed to develop low-carbon models for Indian transportation. The Testbed will generate a practical ‘handbook’ on low carbon urban transportation for developing countries based on big data of Indian transportation and create traffic flow models from the data analysis.
The field testbed system has been deployed on the IIT-H campus and along a 30 km stretch of NH-65. The system includes key components such as real-time traffic monitoring using cameras, Bluetooth and Wi-Fi sensors, speed detection, safety, conflict warning using traffic signal lights and remote environment gas sensing.
The traffic monitoring is not just being done in Hyderabad city but also in Ahmedabad. The IIT-H researchers established traffic monitoring cameras at one major junction in Ahmedabad to monitor and compare the difference between Hyderabad and Ahmedabad traffic conditions in real-time.
The project was launched recently in the presence of IIT-H and Japanese researchers along with the officials from Greater Hyderabad Municipal Corporation, Traffic Police and Ministry of Education, Culture, Sports, Science and Technology, and Japan Science and Technology Agency (JST).
Speaking about the importance of the research, Prof UB Desai, Director, IIT-Hyd said, “Reducing carbon footprint is the need of the hour. India has diverse modes of transportation and we need to understand this diverse mobility much better. The Testbed under the M2Smart project is aimed at this fundamental objective. We will be able to have a better understanding of multi-modal transportation in the country with the data acquired using the Testbed. It will also be able to provide solutions to reduce the carbon footprint.”
Key outcomes of the research include developing state-of-art heterogeneous vehicle-sensing technologies for all types of vehicles that ply on Indian roads using various kinds of sensors (CCTVs, LIDAR, Wi-Fi/Bluetooth/Cellular).
The Testbed will also be used for developing micro traffic simulation models on the basis of collected and aggregated traffic data from several sensing devices using big data analysis.