Artificial intelligence-powered expert system model for identifying fall armyworm infestation in maize (Zea mays L.)

Maize (Zea mays L) is one of the most saleable cereal crops grown worldwide and a dominant staple food in many developing countries. The severe outbreak fall armyworm maize causes massive yield loss. Modern technologies, including smartphones, can assist detecting recognising infestation maize. objective this study was to develop an automated Artificial Intelligence Powered Expert System (AIPES) for identifying In addition, it put forward deep learning-based model that trained on photographs healthy infested leaves, cobs tassels from dataset furnished application will be using Convolutional Neural Network (CNN) architecture Mobile Net V 2 framework model. developed (AI) based detection system DCNN (Deep Network) support cultivating farmers. executed by accurately plant also classified them vis-c-vis healthier crop. learning models were detect recognise infection more than 11000 images cobs, tassels. created (AIPES maize) CNN detected recognised with 100 per cent training accuracy rate 87 validation accuracy. So, treatment armyworm-infested could lead higher crop yield.