Spatio-temporal Mapping of Green House Gas Emission in Urban Settings using a Vehicle Mounted IoT Enabled Pollution Sensing Modules

This paper represents the spatial variability in the pollution by virtue of industrial and residential areas located in almost all the urban settings located at different places. Hence the pollutant gases data of a few locations cannot give an accurate overall estimate of the pollution index of the city. Hence a Spatio-temporal mapping is required to get a fair idea about the pollution in different areas at different times and would also help in identifying any high pollution zones so that remedial actions can be taken to reduce the effluent emissions. This work focuses on the use of IoT enabled gas sensing nodes which are proposed to be mounted on any public transport vehicle or administration vehicle of the focused city to get a continuous indication of the concentration of various greenhouse gases and to use an open-source database management system for warehousing and retrieval of Spatio-temporal pollution data through web-interface