Air pollution has created havoc in many metropolitan cities all around the world. The basic cause of air pollution is particulate matter (PM2.5) caused due to increase in industrialization, urbanization. With specific climatic condition during seasons like winter it becomes more menacing and stalls the people even to move around. It is challenging to control air pollution in developing countries, but collectively monitored real-time data on temperature, humidity along with air quality index at various locations would prove essential in providing apt guidance to people in safeguarding them against ill effects. The paper presents a computational solution which involves smart location-aware pollution monitoring and alert system which would provide analytical support to government offices as well as people all around the world. An IoT based framework incorporating gas, humidity-temperature sensors installed at various locations for sensing data and making it available in real-time for location aware smart phone users with map feature for better visualization. This would create awareness and help people as well as organizations to monitor and control air pollution in effective way. Customized decision support information would be provided based on individuals live location. Live location analysis would help in notifying individual which includes updates regarding current pollution as well as climatic conditions with statistical system which can be used to view data over the range of period.Features of Application developed:
1.) Temperature, Humidity and Air Quality Index measured using sensors is logged and can be viewed by user via Android application featuring statistical analysis over a range of period.
2.) In case of sudden changes in any parameters user is immediately notified based on his live location.
3.) Google Maps integration allows user to view data of regions where sensors are installed.
4.) Data collected is immediately logged in google sheets automatically which allows government organizations to perform smart analysis of data using some analytic techniques.
5.) Monitoring conditions becomes easy as data is collected in real-time and made available to location-aware mobile end point users.