Design and Development of a Low-Cost Crop Protection System Using the Internet of Things and Machine Learning

Agriculture is considered one of the most basic occupations in many territories and is essential for humankind to survive. Hence, it is necessary to ensure initiatives that protect agricultural fields from all the possible threats to field production. Thus, surveillance of the farmlands is requisite to do away with these threats. One such initiative is our proposed system which focuses on smartly surveilling the farm. Our proposed method has designed to monitor and safeguard agricultural farms against wildlife. The features included are generating an irritative alarm buzzer that keeps them away from the field and reporting to the farmers and concerned forest officials. Our proposed system uses one of the booming technologies, i.e., Convolutional Neural Network's YOLO (You Only Look Once) v3 real-time object detection and the Internet of Things, to monitor the animal's entry into the field fence. Thus, this system ensures the complete safety of farmers' farmlands from Wildlife attacks.