Abstract:
The rubber industry in Sri Lanka faces challenges in efficiency and quality due to traditional cultivation practices that rely heavily on manual monitoring. These methods are time-consuming, labor-intensive, and often result in inconsistent growth conditions, directly affecting latex yield and plant health. This research proposes an IoT-based growth monitoring system designed specifically for rubber plants (Hevea Brasiliensis) to address these challenges through real-time environmental monitoring and data-driven decision-making.
The system integrates a mixed-method research approach, combining qualitative insights obtained from expert interviews and surveys with quantitative data collected through IoT-enabled sensors. Key environmental parameters such as soil moisture, temperature, humidity, and light intensity are continuously monitored using sensors connected to ESP32 microcontrollers. The collected data is transmitted to a cloud-based platform for storage and processing, enabling real-time visualization through a user-friendly web dashboard developed using React.js and Firebase.
A prototyping development methodology was adopted, allowing continuous feedback and iterative improvements throughout the project lifecycle. Initial prototype testing demonstrated high accuracy in sensor readings and reliable real-time data transmission, with promising results in detecting optimal growth conditions. Automated alerts provide actionable insights to support timely interventions, helping improve plant health and operational efficiency.
Overall, the proposed system demonstrates strong potential to modernize rubber plantation management by reducing manual labor, enhancing monitoring accuracy, and supporting sustainable agricultural practices. The findings indicate that IoT-driven solutions can significantly improve productivity and decision-making in the rubber cultivation sector.
