This repository contains the complete final year undergraduate research project report for the Farm Intrusion Detection System, designed and implemented specifically for the Federal University of Lafia (FULafia) Garden/Farmland.
Unmonitored human and animal intrusions pose significant threats to agricultural productivity, crop yield, and farm assets within university research gardens and local agricultural plots. Traditional security measures, such as static fencing or manual perimeter patrols, are often resource-intensive and prone to coverage gaps. This project addresses these challenges by engineering an automated, real-time farm surveillance and intrusion detection system.
Key Features & Objectives:
Real-Time Detection: Integrates sensor-based perimeter monitoring to identify unauthorized motion and boundary breaches instantly.
Automated Alerting: Dispatches immediate notifications (e.g., SMS/Email/Dashboard updates) to farm administrators upon detecting an intrusion.
Active Deterrence (If applicable): Triggers local audio/visual alarms or automated deterrents to discourage animal and human intruders.
System Architecture: Combines low-power embedded hardware with a centralized software interface for continuous activity logging and reporting.
Repository Contents:
Full Thesis Document (.pdf): Complete research manuscript including background, system architecture, hardware schematics, software algorithms, testing, and recommendations.
Source Code & Hardware Configurations: (If uploading code files alongside the PDF) Embedded code scripts, algorithm implementations, and dashboard interface scripts.
Degree: B.Sc. Computer Science
Institution: Federal University of Lafia (FULafia), Nasarawa State, Nigeria
Keywords: Internet of Things (IoT), Intrusion Detection System, Smart Agriculture, Farm Security, FULafia Garden, Computer Science