An Effective Energy and Robust Routing Methods for Air Pollution Data Monitoring in WSN

The world is facing major challenges due to the progress in technology. Usually, science has also both advantages and disadvantages. The emerged technology creates environment monitoring systems that assisted for the detection and verification of harmful objects. The automatic system is also being cause of pollution in several ways. So, the requirements have been increased to introduce a system to control the pollution. AP (Air pollution) is one of the most pivotal issues that is affecting the living souls. The wireless sensor networks have found a great application in the area of air quality monitoring. In simple terms, a WN (wireless network) is a collection of sensor nodes that communicate by radio signals or waves and detects crucial data which is used to detect the pollutants from the air. WSN routing protocols are specifically accessed for this purpose, such as EEUC, LEACH, DESCA and so on. In this paper, the focus is to bring forth the basic concepts of air pollution detection and some relevant data mining techniques that helped to make a successful air pollution detection system. In this paper, define an artificial intelligence field-based energy-efficient and novel protocol method for the network called Energy-Efficient and Robust Routing Method for air pollution monitoring in WSNs. In this method, sensor network is trained a large database comprising almost all scenes to create the system more efficient, reliable and effective in the atmosphere. In this method, works to increase the lifespan of the network and improve the energy consumption parameter. In experimental result shows that it output ELDC and some other routing protocols such as LEACH and E-LEACH etc