Sensor Based Quality and Safety Ensured Agriculture Followed by Neural Network Based Plant Disease Management

Abstract

Agriculture is the essential source of raw materials required by various manufacturing industries like cotton, sugar, jute and oil industries. Agriculture being science and art of growing plants attracts the researchers to work towards attaining substantial agriculture. When agriculture gets degraded in quality of its yields then it will reflect severely on the financial development of our country. To increase the agricultural outcome and to improve the efficiency of the harvests, smart agriculture based on IoT technology is adopted. To prevent the crops from cattle intervention smart techniques based on sensors for monitoring and ensuring safety is required. Despite of environmental conditions, animal intervention crop handling is still a challenging task. The proposed system is comprised of sensor module to handle the challenge of monitoring cattle intervention in the field as well as moisture level of soil so as to avoid the draught condition and over drain of water in the farm as well. Controlling those parameters are through any remote device or internet services and the operations are completed by means of interfacing sensors, with microcontroller. This work also includes the implementation of artificial neural networks in predicting the plant disease so overcome the loss in crop yield.