Implementing edge computing in iot networks for improved data processing, speed and reliability

Abstract

This project focuses on developing a robust Supervisory Control and Data Acquisition (SCADA) system for real-time monitoring and management of photovoltaic energy. By leveraging the Internet of Things (IoT) and Edge Computing technologies, the system effectively tracks power, current, and voltage generated by a photovoltaic module, ensuring the power dissipation remains below 0.5 W and the data updates on the remote dashboard occurs every 1.5 seconds.

Key components include the IOMod 8AI RTU for precise voltage and current measurements and the ACS723 current sensor for accurate current sensing. The system integrates these components with the Elseta WCC Lite gateway, which ensures reliable data transmission to a cloud-based SCADA HMI for real-time visualization and analysis.

Throughout the project, meticulous planning and execution led to successful implementation of the SCADA system, overcoming challenges such as ensuring stable VCC for sensors and managing data transmission delays. Testing and validation confirmed the system's accuracy and efficiency, with the IOMod achieving voltage readings with up to five decimal points of precision and the ACS723 sensor showing high accuracy in current measurements.

This project significantly contributes to the promotion of renewable energy and optimization of energy management by providing a reliable tool for monitoring solar energy production. Future enhancements could include expanding the measurement range, improving data transmission speed, and integrating advanced data analytics to further optimize system performance and applicability.