Plastic waste in rivers is an environmental problem that can disrupt aquatic
ecosystems and obstruct river flows. This research aims to design and develop an
integrated river waste cleaning system based on renewable energy that is capable
of automatically transporting waste and monitoring system performance in real
time. The research employs a quantitative method with an experimental approach
and prototype design. The system consists of a conveyor, BLDC motor, ESP32,
camera, a 200 Wp photovoltaic (PV) system with a LiFePO₄ battery, and Internet
of Things (IoT) technology. Testing was conducted at conveyor inclination angles
of 30°, 35°, 40°, and 45° with loads of up to 5 kg. The theoretical calculation results
indicate that a 30° inclination angle provides the best performance, with a
theoretical transport capacity of 1,200 kg/hour and a specific power consumption
of 7.49 W/kg. Transportation tests involving six types of waste showed success rates
of 60% for plastic bottles, 100% for plastic, 0% for paper, 100% for sandals, 75%
for wooden branches, and 60% for dry leaves. The PV system generated an average
energy of 733.3 Wh/day, compared with the motor energy requirement of 335.04
Wh/day, resulting in an energy sufficiency ratio of 218.9%. The IoT monitoring
system achieved an average accuracy of 95.6% with a 3-second delay, while image
transmission from the camera had a 5-second delay. Overall, the system is capable
of automatically transporting waste by utilizing renewable energy and IoT
technology.
Keywords: River Waste Cleaning, Automatic Conveyor, Solar Power Plant (PLTS),
ESP32, Renewable Energy, Internet of Things.