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April 22, 20260 citationsOpen Access

Research on Real Time Tractor Monitoring and Operational Visualization

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PCProf A. U. ChaudhariNLNinad Dhananjay LadDNDanish Ahemad Shaikh Nasir

Key Points

  • The aim is to develop a smart embedded software system for real-time tractor monitoring to enhance precision agriculture.
  • Developed a prototype using ESP8266, ESP32 camera, and L298 motor driver.
  • Implemented color-based navigation using image processing to guide the tractor.
  • Created a notification system that alerts users of any deviations from the assigned path.
  • Demonstrated successful autonomous navigation along predefined paths.
  • Achieved real-time monitoring and notifications through the web application.
  • Shown potential for significant reductions in labor costs and operational errors.

Abstract

Agriculture is undergoing a major transformation with the integration of automation, IoT, and smart monitoring systems. Conventional tractor operations often demand continuous human supervision, leading to increased labor costs, inefficiency, and errors in field operations. With the advent of embedded systems and intelligent software platforms, there is now a growing need for solutions that can automate routine tasks, provide real-time monitoring, and deliver actionable insights to farmers. The proposed paper, Real Time Tractor Monitoring and Operational Visualization System, is designed as a smart embedded software integration model to support precision agriculture. The hardware prototype is developed using an ESP8266 microcontroller, ESP32 camera module, L298 motor driver, and 4 BO motors with wheels, enabling the vehicle to autonomously navigate along a path. A color-based navigation mechanism is implemented, where a fixed color (e.g., red) is detected using image processing to guide the tractor from one point to another. If the tractor deviates from its assigned path, a notification is immediately sent to the user through a Firebase database and displayed on the web application.

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Cite This Study

Chaudhari et al. (2026) studied this question.

synapsesocial.com/papers/69e866ad6e0dea528ddeafd6https://doi.org/10.5281/zenodo.19667281
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