Air Pollution Sensing and Causal Modelling

Drive-by air pollution sensing

Enabling cost-efficient collection of granular spatiotemporal pollution data through drive-by sensing

A crucial step in tackling air pollution is to measure air quality at a fine spatiotemporal granularity. Access to quality data is the first step to perform wide-ranging analyses that include — identifying sources of air pollution, monitoring compliance of air quality standards, measuring the efficacy of various interventions, etc. Multiple ‘smart city’ initiatives around the world have touted to solve this problem by having a static deployment of either thousands of low-cost sensors or a few tens of reference-grade expensive monitors. This approach, however, comes with its own challenges – 1) installing these sensors is capital intensive, making it difficult to scale to smaller cities and towns; 2) these static sensors do not capture the spatial variation in pollution within monitored regions.

A promising approach for several smart city projects, called drive-by sensing, has been explored to address these challenges. Drive-by sensing leverages vehicles retrofitted with different sensors (pollution monitors, etc.) to capture the desired spatiotemporal pollution data at a fraction of the cost. Most of the drive-by sensing efforts have also often used fixed-route vehicles such as public transport buses. However, this approach still leaves many spatiotemporal gaps in data collection due to it being limited to specific routes and times.

To address these gaps, we have been exploring an approach leveraging taxis for drive-by sensing. We have developed a system to bootstrap drive-by sensing deployment by taking into consideration a variety of aspects such as spatiotemporal coverage and budget constraints. Our system significantly outperforms the baselines when a fleet comprises of both taxis and fixed-route vehicles such as public transport buses.

We have validated our approach through pilots with our partners, Ola Cabs and Three Wheel United. In Collaboration with Ola Cabs, one of India’s largest cab aggregators, deployed a drive-by sensing pilot in Delhi by retrofitting 20 cabs with sensors. We have also piloted the system with autorickshaws in Bengaluru in collaboration with Three Wheel United. In the pilot, 17 autorickshaw were fitted with sensors and the drivers were incentivized to take specified routes. Through these approaches we were able to cover areas that were either underserved or inaccessible to public transportation, ensuring we had a cost-effective and wider collection of granular spatiotemporal pollution.