Development of an IoT-Based Renewable Energy Potential Monitoring System in the Coastal Area of &#8203-&#8203-Bengkulu as a Source of Locally Based Science Learning
Dedy Hamdani

Physics Education Study Program,
Faculty of Teacher Training and Education, University of Bengkulu, Indonesia

Abstract

This study aims to develop an Internet of Things (IoT)-based environmental monitoring system to identify renewable energy potential in the coastal areas of Bengkulu and assess its potential as a source of science learning based on local context. The study uses an engineering design approach that includes the stages of design, development, implementation, and system testing. The developed system integrates an ESP32 microcontroller with a BH1750 sensor, a DHT22 sensor, and a cup anemometer to monitor sunlight intensity, air temperature, air humidity, and wind speed in real-time. Environmental data is transmitted via a WiFi network and visualized using the Blynk IoT platform. The results show that sunlight intensity increases significantly during the daytime period and reaches a maximum value of around 35,000 lux, indicating the potential for medium-sized solar energy in coastal areas. Wind speeds range from around 2.5-4.5 m/s and tend to increase during the day, indicating the influence of coastal atmospheric dynamics and the potential for small-scale wind energy utilization. Air temperature and humidity patterns also demonstrate the characteristics of a dynamic tropical coastal environment. The developed system successfully performed real-time environmental monitoring and provided baseline data for estimating solar and wind energy potential based on field data. In addition to its technical contribution, this research also demonstrated that environmental monitoring data can be utilized as a resource for locally context-based science learning. Real-time environmental data from coastal areas can support contextual science learning, STEM, and project-based learning in renewable energy, weather, climate, and environmental sustainability. Therefore, the developed system has the potential to support the development of renewable energy monitoring, along with digital technology-based science learning and the development of 21st-century skills.

Keywords: Internet of Things, renewable energy, environmental monitoring, local context-based science learning, STEM education

Topic: Physics Education