Development of Integrated IoT and Machine Learning based data collection and analysis system for the effective prediction of agricultural residue/ biomass availability to regenerate clean energy
India a country of 1.39 billion population, where use of wood, leaves and other such resources which are obtained from nature are being used as fuel, to cook the food, to light since time unknown. Similarly, in farms and agricultural lands after gathering dry matters from the fields post the harvesting process in the farms, the leftover such as leaves, small branches and other wastes from fields which includes unused manures, mixture of wastes and other kind of residues get collected in large amount and needs to manage properly. But it is observed that mainly these waste and residues are being burnt everywhere and considered as of no use, hence causing air pollution and environmental imbalance. This residual matter can be used efficiently for the regeneration of clean energy. We introduce an integrated system which harnesses the power of artificial intelligence to take the information from Wireless Sensors about the residual availability by collecting the categorized information from the data points in order to determine whether the waste at a substantial level is generated or not, thus incorporating a hierarchical model to collect the waste from all the data points which are locations of collection where the IoT device will be fixed. Thus, a Wireless Sensor Networks based centralized waste collection point where the waste and residues will be sent in order to implement the new techniques to generate clean energy which eventually will be useful for the villages for cooking, virgin wood fiber regeneration, daily chores and even generation of electricity as well.