Agricultural land is the support of the Indian economy, but it is under danger from wild animals and unauthorized people, and it incurs massive losses to crops. In today's era, artificial intelligence (AI), deep learning, computer vision, and smart hardware enabled the creation of solid, real-time detection and warning systems to safeguard agricultural land. These technologies enabled protection systems to become much more powerful than what they used to be. This review article provides an examination of fifteen cutting-edge studies that combined models like YOLO (v3–v8), and MobileNet SSD with IoT devices like Raspberry Pi, microcontrollers, and sensors. The solutions from the reviewed studies have worked effectively in precise detection, real-time warnings, and automation. But these systems are expensive, environmental perturbations can degrade their operation, and in some instances the boundaries thus drawn may be detrimental to birds and animals. Results show that AI-based and IoT-based smart protection systems can reduce substantially human-wildlife conflict, improve agricultural yield security, and augment farmer situational awareness and hence represent a promising and scalable solution for modern precision agriculture.
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Yogesh Golhar
Shreyash R. Wadibhasme
Rohan K. Ingle
International Journal of Innovative Research in Computer and Communication Engineering
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Golhar et al. (Mon,) studied this question.
synapsesocial.com/papers/68d4724f31b076d99fa6abb8 — DOI: https://doi.org/10.15680/ijircce.2025.1309018