To monitor Delhi’s pollution levels, three Delhi students have developed an app that can easily measure the Air Quality Index (AQI) around you.
Tanmay Srivastava, Kanishk Jeet, and Prerna Khanna are the students of Bharti Vidyapeeth College of Engineering. For the app, the US-based Marconi Society has awarded them the cash prize of $1,500 (approximately Rs 1,09,500) under their Celestini Programme.
“The three have developed ‘Air Cognizer’, a portable, real-time air quality analytics application, which is available at Google Play Store to download freely by any smartphone user to measure the air quality in his/her area,” the Marconi Society mentioned in a press release.
Using the app is quite easy. All you need to do is upload an image taken outdoors, with half of it covering the sky region and should not contain any direct source of light. Upload it on the app and it will use processing techniques to extract features and the Machine Learning (ML) model of the app estimates the AQI in the area.
“You can’t know how to counter an issue unless you know the severity of it,” Srivastava told IANS. “Hence, we created Air Cognizer to make residents know the quality of the air they breathe, which is just a click away.”
The Marconi Society aims at the development of key technologies and their application to fix society’s problems. Its Celestini Programme came to India in 2017 and now focuses on working with engineering undergraduates in developing countries to help improve the local economy.
This year three teams of 100 applicants were selected who were asked to work on the problem of air pollution and road safety in New Delhi. While first prize went to students of Bharti Vidyapeeth College, the second prize was for Divyam Madaan and Radhika Dua, a duo from Chandigarh’s University Institute of Engineering and Technology (UIET) who designed a website that forecasts air pollution in Delhi over the next 24 hours.
The third team Sidharth Talia, Nikunj Agarwal, and Samarjeet Kaur also from Bharti Vidyapeeth developed a digital platform for vehicles to automatically talk to each other about road safety conditions.
