Earth, Atmosphere & Environment Sciences, Engineering Sciences


City Air Pollution Monitoring and Prediction System CAMPS


Earth, Atmosphere & Environment Sciences, Engineering Sciences

Focus Area:

Pollution Monitoring

Social Benefits:

Portability and mobility of the system, which can collect sensor generated air pollution records from various locations of an area at different intervals thereby performing a real-time analysis to construct a grid over a map presenting a diverse level of pollution, The device can be mounted over a vehicle and monitor the location based air pollutants in a moving condition sending the data to cloud, Simultaneous deployment of the developed device in multiple vehicles can be carried out to establish the accuracy of profiling, Handy cost effective device that can be fitted in public transport for more accurate and granular information on city pollution, an initiative under Swasth Bharat, Mobile application for pollution information as location based services, under Smart City initiative and Digital India, Cost effective system for centralized monitoring of ambient air pollution adjacent to industrial and mining belt.

Developing Agency:

CSIR-Institute of Minerals and Materials Technology (IMMT), Odisha

Technology Readiness Index:

Lab Validation

Website Link :
Source (more info) :

Brief Description

Description :

The system focuses towards the measurement of air pollutants in a moving node unlike portable static nodes.The System relates to Monitoring of air pollutants in different cities using moving sensor node in GSM network by a software operated air sampling box, which is capable of real time and continuous monitoring of different prevailing parameters of air pollution such as Ozone (O3), Carbon Monoxide (CO), Carbon Dioxide (CO2), Nitrogen Dioxide (NO2) and VOC etc. The data get aggregated in cloud in real time through GPRS and spatially analyzed in a synchronized mode. Instead of static stations it deals with a mobile platform for data acquisition and transmission from dynamically changing sampling points. A bird's eye view of the pollutant spatial distribution has been disseminated through a website for a general awareness. The dataset, thus calculated are of approximation based on the developed validated Geographic Information System (GIS) model for a predictive analysis. Further it uses geo-statistical methods for the absolute prediction of fine-grain air quality to interpolate/estimate the values and its impact for intervening points.The sensors are organized in the devised software controlled air sampling box in a moving van for continuously monitoring of air pollutants. A GPS has been used in the system which specifies about the longitude and latitude of the particular location of measurement with time stamp.

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