# Real-Time Farm Surveillance Using IoT and YOLOv8 for Animal Intrusion Detection
## 1 Introduction  
Agriculture, sometimes known as the \"lifeblood of sustenance\", is critical to renewing the food supply. However, just creating these resources is insufficient, because they can be destroyed before they can be used, which wastes not only time and money but also valuable raw materials. As a result, protecting agricultural assets and farmlands is critical, especially given the rising issue of animal encroachment. This threat, posed by wild boars, macaques, porcupines, deer, monkeys, and bears, has not only proven to be extremelyharmful, but has even resulted in human deaths on occasion. Local farmers face the brunt of this situation, including losses of up to 50% of their crops, exacerbated by their unwillingness to resort to severe measures due to rigorous wildlife rules. Figure 1 depicts animals invading agricultural regions. The most common expression of this conflict is human-elephant conflicts, which account for a significant amount of the damage seen in many locations [1]. Agriculture is the backbone behind both meeting the population's food demands and delivering key raw materials to industry. Animal interference, on the other hand, results in massive crop losses in agricultural sectors. Crop devastation by marauding wild animals has recently become a major source of worry. Notably, the predation of these animals has caused significant damage, occasionally resulting in human mortality. The negative impact on agricultural output is especially obvious in the case of basic crops grown in rural regions, such as potatoes and wheat, with small-scale farmers suffering the brunt of these losses, which can amount to 40% to 50% of their overall yield. Unfortunately, due to strict wildlife preservation rules, these farmers are prevented from taking more active action. The increasing cases of human-elephant conflict, notably in India, highlight the critical need for a technology that can quickly repel these trespassing animals upon their discovery [2]. This paper presents the Smart Farm Surveillance System (SFSS), an innovative approach developed to protect agricultural lands from wildlife intrusion through real-time monitoring and detection utilizing IoT and AI technologies. The fundamental goal of the SFSS is to provide proactive, real-time monitoring of agricultural and crucial areas through the expert use of cutting-edge object detection algorithms. By seamlessly combining cloud technology with AI-powered camera systems, this new approach promises the rapid identification and mitigation of possible threats. The expanding agricultural industry, along with the need for strong security measures, is part of the growing demand for modern surveillance systems. The adoption of cutting-edge technologies, such as the SFSS, is essential, given the shortcomings of traditional monitoring systems in recognizing and responding to real-time threats. This system effectively addresses the difficulty of timely threat detection on farms by ensuring the early detection of intruders, animals, or unauthorised activity. Furthermore, through interactions with cloud-based services, its smooth data processing provides farmers with timely notifications and improves all their crop management skills. Figure 1: Animal intrusion in agricultural fields. The SFSS is based on cutting-edge object identification algorithms that use machine learning and deep learning techniques to recognize a wide range of things, from human intrusions to specific animal species. To avert possible risks, it provides proactive and real-time surveillance, prompting alarms for suspicious activities such as wildlife encroachment or intruders. The integration of cloud technology enables remote access to surveillance feeds as well as safe data storage for analysis. It is adaptable, accommodating various farm sizes, and encourages humane security measures while delivering data-driven insights for crop management.