I am currently part of a Senior Design team working on developing a wireless mesh network using ESP32 microcontrollers and interdigitated electrodes (IDEs) to monitor pesticide distribution within a field of crops when they are sprayed. This project addresses the critical need for increased agricultural yield to meet future global food demands. By using measuring nodes with IDEs positioned on a pole at three levels of a corn canopy, we aim to capture accurate pesticide saturation measurements to assess pesticide spray coverage across different application techniques, like drone or boom spraying. Each node in the mesh network measures pesticide distribution data, which it will send through a wireless network back to a central node, which can then be retrieved as a .txt file for analysis.
Simplified High-Level Sketch
As a member of the Software Team for this project, I focus on designing and implementing software solutions that enable the ESP32 microcontroller to function effectively within the mesh network. My role involves research of Espressif documentation to ensure that I’m leveraging the full capabilities of the ESP32, including its wireless communication protocols and device features, which are crucial for data collection in field applications. I write code in C to handle data acquisition, processing, and transmission, ensuring that each ESP32 node can reliably measure resistance values from interdigitated electrodes (IDEs) and communicate this data within the network. Additionally, I maintain our Git repository, organizing and managing code updates to ensure seamless collaboration across the team. This role requires careful attention to detail in both coding and documentation, as well as the ability to troubleshoot and optimize microcontroller performance to meet the specific constraints of the project.
This project makes a significant contribution to precision agriculture by providing an innovative solution to monitor and optimize pesticide distribution across crop canopies. By developing a wireless mesh network using ESP32 microcontrollers and interdigitated electrodes, the project enables accurate, automated measurement of pesticide coverage at multiple canopy levels, ensuring more effective and targeted pesticide application. This data-driven approach helps improve pesticide stewardship, reduce waste, and minimize environmental impact. The ability to analyze spray techniques across different application methods (e.g., drone, boom, airplane) also supports more sustainable agricultural practices, ultimately contributing to increased crop yields and food security as global demands grow.
Sensor Node Pole Structure Diagram
Network Structure Diagram
Through my work on this project, I have developed valuable skills in embedded systems programming, specifically working with the ESP32 microcontroller. I’ve gained hands-on experience in coding with C for hardware integration, including configuring and utilizing components like SD cards for data storage and the ADC for sensor readings. Managing our Git repository has enhanced my version control and collaborative coding skills, enabling smooth teamwork and consistent project organization. Additionally, I’ve deepened my understanding of wireless communication protocols and microcontroller documentation, as well as troubleshooting and optimizing code for efficient, low-power operation. These skills have strengthened my ability to create reliable, scalable solutions for real-world applications in IoT and embedded systems.
Check out the webpage for our project for team information and to check out all of the documentation