Artificial Intelligence in Agriculture

Abstract: Agriculture plays a significant mode in the economic sector. The population is increasing tremendously and with this increase the demand of food and employment is also increasing. The traditional methods which were used by the farmers were not sufficient enough to fulfill these requirements. The agrochemical application with the conventional sprayers results in the wastage of applied chemicals, which not only increase the economic losses but also pollutes the environment. In order to overcome these drawbacks, an image processing based real-time variable rate chemical spraying system was developed for the precise application of agrochemicals in disease the paddy crop based on crop disease severity information. The developed system comprised of web cameras, laptop, microcontroller, and solenoid valve assisted spraying nozzles. The system further calculated the disease severity level of paddy plants, based on which the solenoid valves remained on for a specific time duration so that the required amount of agrochemical could be sprayed on the diseased paddy plant. Field performance of developed sprayer prototype was evaluated in the variable rate application (VRA) and constant rate application (CRA) modes. The field- testing results showed a minimum 33.88 % reduction in applied chemical while operating in the VRA mode as compared with the CRA mode. Hence, the developed system appears promising and could be used extensively to reduce the cost of pest management as well as to control environmental pollution due to such agrochemicals.