Integration of IoT and DNN Model to Support the Precision Crop - Sasikala, C.; Srilatha, P.; Khaleelullah, Shaik; Ravindra, Ch.; Kadam, Anup; Gupta, K. Gurnadha (International Journal of Intelligent Systems and Applications in Engineering, 2024)
Agriculture filed is the major source of living for humans in many countries. As the population is increasing there was no proportionate growth in in agriculture productions which may leads to the harm to the societies. Most of the cases we depended on natural resources for cultivation, due to geological disasters many times there may be damage of the fields. Our main focus is to suggest precision crop based on climatical situations. We integrated IoT with ML algorithms for this purpose for enabling precision crop. Combining IoT with DNN (Deep Neural Networks) for making various aspects of test such as soil, temperature, humidity, pH values generating from various sources can be decided which crop is suitable the conditions. This paper gives the usage of IoT sensors for decision making for crop fields, optimizing the usage of resources and directs various farming methods. The comparative study proved our results are better than the many existed works.