Computer Sciences and Information Technology
Title : | Scalable Spatio-Temporal Measurement and Analysis of Air Pollution Data for Delhi-NCR using Vehicle-Mounted Sensors |
Area of research : | Computer Sciences and Information Technology, Earth, Atmosphere & Environment Sciences |
Focus area : | Mitigation of air pollution |
Principal Investigator : | Dr Rijurekha Sen, Assistant Professor, Indian Institute of Technology (IIT) Delhi |
Timeline Start Year : | 2019 |
Contact info : | sen.ria@gmail.com ; arnabb@iitk.ac.in ; arnabb@cse.iitk.ac.in |
Details
Executive Summary : | Air pollution is a bane for modern civilization, especially the big cities. Delhi-NCR, being one of the largest and most densely populated urban centers in the whole world, is no exception. Mitigating pollution needs accurate measurements and identification of pollution sources. The current setups have covered only about 30-35 air pollution measurement centers in Delhi-NCR, which are thoroughly inadequate to cover the vast geography. In this proposal, Investigators aim to fundamentally alter this paradigm using mobile air pollution sensors to augment the static sensors. The key idea is to deploy sensors in vehicles that ply through the city. Even if a small fraction of the fleets of vehicles is augmented with pollution sensors, a lot of fine-grained spatio-temporal pollution data can be collected over an extended time period. Analytics with this new dataset from hitherto unmeasured geographical regions can potentially give new insights for pollution sources, eventually aiding more data-driven mitigation policies. The plan is to piggyback sensors onto buses, auto-rickshaws, ride-sharing services such as Ola cabs and courier service vehicles, which by the very nature of their job of picking up and dropping passengers and goods, will criss-cross the city. The sensors mounted on the vehicles will (live) stream data back to the servers. The main server will have a data storage and management engine, augmented with a querying system to enquire about the data, an analytics layer to compute correlations between pollution and other auxiliary data, and a visualization interface to see trends, etc. The deliverables will include a robust deployment of mobile sensors and an efficient data storage system having the capabilities of querying, analytics and visualization. This will not be a one-time survey of pollution values at certain regions but a live IoT framework backed by analytics to augment the government’s pollution curbing efforts. The success of this pilot project at Delhi-NCR may lead to its adaptation to other cities of India. |
Co-PI: | Dr Pravesh Biyani, Associate Professor, Indraprastha Institute of Information Technology (IIIT), Delhi, Dr Arnab Bhattacharya, Professor, Indian Institute of Technology (IIT) Kanpur, Dr Sayan Ranu, Associate Professor, Indian Institute of Technology (IIT) Delhi |
Total Budget (INR): | 1,27,46,800 |
Organizations involved
