Cropguard: AI-driven IOT-based smart farming system

Ke, Joey (2025) Cropguard: AI-driven IOT-based smart farming system. Final Year Project, UTAR.

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Abstract

Protecting crops against wildlife intrusions has become a pressing need as the delicate balance between human livelihoods and wildlife existence is disrupted. Reason behind this is that the encroachment of wildlife habitats caused by the rising socio-economic activities has led to human-wildlife conflict. Therefore, this scenario underscores the critical importance of developing an innovative crop protection system to mitigate the issue of crop raiding faced in agricultural sector. This project proposed an IoT-based smart farming system driven by Artificial Intelligence (AI). In other words, this system is developed in such a way that it builds on the foundation of IoT and AI to expand its system capabilities in protecting the crop against wildlife intrusions intelligently. This system is developed to have a variety of functionalities including detecting the presence of animal, classifying the animals and initiating appropriate actions to repel the threatening animals away. In this project, a Raspberry Pi 4 Model B acts as a central processing unit to process and interpret several data inputs from multiple sensors such as Raspberry Pi Camera Module 2, Passive Infrared (PIR) sensor and buzzer. Besides, machine learning model such as Haar Cascade Classifier is used to empower the system to detect and classify the animals into different categories. The collected data is processed and analysed in real-time. Real-time alert notification will be sent to the farmers upon wildlife intrusions. With this feature, the farmers can be informed immediately, enabling them to execute further actions to the animals and their crops

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