About the Practice
Problem Statement:

air pollution: Seven million premature deaths a year caused by exposure to the bad quality of the air we breathe. The data from these devices can also help to create a detailed map for the entire cities which are helpful in figuring out the levels of pollutions in different areas. This can help in planning our activities and preventing exposure to high levels of particulate matter.


Aerogram is devising a network to predict real-time air quality in a local mapped area. The designed device is equipped to monitor multiple pollutants. The startup is aligned with its vision to be the leading provider of data on air quality and be the most preferred air pollution management organization. The immediate aim is the provisioning of real-time local air quality data based on micro-mapping of defined air pollutants to enable masses in taking timely and precise actions to limit exposure. Also, the data is to be leveraged by concerned authorities to help adopt suitable strategies to reduce/remove the sources of pollution. In order to achieve accuracy and efficiency in achieving the mission, Aerogram designs and builds its own low-cost AQM devices which are used to establish a robust network wherein the devices are technically capable of smooth communication amongst each other which allows effective calibration. The accuracy of data achieved via a robust network enables conducting more in-depth analytics to generate reports and information which is shared with the concerned users.

About the Innovator

Knowledge Provider / Innovator: Manoj Sahukar, Faheem Ashraf, Sahil Siwach, Bhaskar Dutt and Surbhi Kumari
Address: Synergy Building, IIT Delhi Hauz Khas, New Delhi - 110016
City: New Delhi
State: Delhi
PIN Code 110016

Email: info@aerogram.in
Contact No: 99337 44862
Website: http://aerogram.in/

Practice Details

Link: – Early maturity (60-70 days); – White, bigger (up to 940g) & compact curds and – High yield (up to175q/ha).
Photo Links:

Problem Scale: Around the World
Blog Link 5:

News Link 1:

GIAN Reference: GIAN/UAL/022

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