Browsing by Author "Muhammad Ammar Murtaza and Muhammad Amir"

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    Animal tracking system
    (UMT, Lahore, 2024) Muhammad Ammar Murtaza and Muhammad Amir
    This study introduces a novel approach for livestock farm tracking utilizing both RFID technology and IoT solutions. The proposed system aims to address the challenge of efficiently monitoring and managing animal movements within farm environments. By integrating RFID readers and tags with a central microcontroller and employing GPS modules alongside LoRaWAN communication, the system enables comprehensive real-time data collection and processing. RFID readers are strategically placed at entry and exit points, and RFID tags are attached to individual animals, facilitating accurate and timely tracking. The GPS module captures geographical coordinates, which are transmitted via LoRaWAN to a receiver unit and then uploaded to the ThingSpeak IoT platform. A custom-built application uses the ThingSpeak API to display the location data on a map, providing a user-friendly interface for real-time monitoring. Through rigorous testing and implementation, the system demonstrates significant improvements in performance and reliability compared to traditional tracking methods. The results indicate enhanced efficiency, accuracy, and adaptability in livestock management, offering promising prospects for optimizing farm operations. In conclusion, this integrated RFID and IoT-based livestock tracking system presents a viable solution to streamline animal monitoring processes, laying the groundwork for more efficient and sustainable agricultural practices.