An IoT-Based Solution for Intelligent Farming.

Area of Science:

• Agricultural Technology
• Internet of Things (IoT)
• Wireless Sensor Networks (WSN)

Background:

• Intelligent farming applications, including automated livestock management, present unique communication challenges.
• Existing Internet Protocol (IP)-based solutions are often unsuitable for the specific constraints of agricultural environments.
• The SheepIT project requires a robust system to control grazing sheep in vineyards without damaging crops.

Purpose of the Study:

• To develop and review a customized communication stack for intelligent farming applications.
• To address the specific requirements of the SheepIT project, focusing on Machine-to-Machine (M2M) communication.
• To design, deploy, and evaluate a gateway for enhanced IoT/M2M interaction in agricultural settings.

Main Methods:

• Development of a tailored communication stack from the physical to the application layer.
• Design and deployment of an M2M gateway to meet SheepIT project service requirements.
• Performance evaluation of the gateway in a real-world agricultural scenario.

Main Results:

• A customized communication stack was successfully developed to meet rigid requirements for WSN and M2M communications.
• A functional gateway was designed, deployed, and tested, demonstrating feasibility for the SheepIT project.
• The gateway's performance, feasibility, and scalability were validated in a practical farming environment.

Conclusions:

• The developed communication stack and gateway are suitable for intelligent farming applications, particularly those with stringent communication needs.
• The solution offers a viable alternative to IP-based systems in challenging agricultural environments.
• The findings support the scalability and applicability of the system for broader intelligent farming use cases.