Environmental monitoring through Vehicular Ad Hoc Network: A productive application for smart cities

SummaryIndustrial growth, technological development, and increased human activities for comfort and luxurious life increase different environmental parameters like temperature, humidity, carbon monoxide, methane, and smoke. The value of these parameters are increasing steadily which has adverse effects on human life and human health and is also the cause of various disease like cancers and lung disease. It is now essential to monitor the environmental parameters of a region frequently. For the automatic continuous monitoring of environmental parameters of any location, this paper proposes to use vehicular ad hoc network (VANET), which is one of the promising subclasses of mobile ad hoc network (MANET). Automatic monitoring of environmental parameters of any location includes measurement of environmental parameters of a location, transmission of environmental parameters from the measured location to the observation center, and analysis of the parameters at the observation center. Two aspects are discussed for the transmission of parameters from the location of measurement to the observation center: first by vehicular communication and second by vehicular cloud. The analysis of the environmental parameters at the observation center is done using probabilistic neural network (PNN). Apart from this, different generic network parameters like end‐to‐end delay, number of hops, and network gaps for the proposed work are computed for the transmission of different environmental parameters and is compared with different VANET routing protocols like geographic source routing (GSR), anchor‐based street and traffic‐aware routing (A‐STAR), and peripheral node‐based geographic distance routing (P‐GEDIR). Vehicular motion is created using Simulation of Urban MObility (SUMO), and the network parameter values, like end‐to‐end delay and number of hops, are obtained using OMNET++. A testbed experiment is conducted for the classification of sensor data which is adoptable in practice.