Solar-powered waste classification model

Motivated by a desire to find solutions for sustainable environmental protection, two students, Huynh Nguyen Le Anh Thu and Dao Nguyen Duc Anh, from the 11th grade Physics class at Le Quy Don Gifted High School (Nha Trang City), conducted research on a solar-powered waste classification model. Their research won the first prize at the Provincial Science and Technology Competition for high school students in the 2024-2025 school year.

Huynh Nguyen Le Anh Thu and Dao Nguyen Duc Anh at the Provincial Science and Technology Competition for high school students.

According to Anh Thu, waste and environmental pollution are urgent issues; waste classification is an essential step in the waste management process, helping to reduce the amount of waste that needs to be processed and promote recycling. The group hopes to help improve the classification of waste such as plastic, metal and organic waste at the source.

The new point of the research is the combination of renewable energy technology and waste classification; and the application of advanced technologies such as solar energy, AI cameras, electromagnetic sensors, optical sensors and programmable controllers. In addition, solar-powered waste classification with automatic control is a trending solution for smart cities and the circular economy.

To implement the model, Anh Thu and Duc Anh applied the principles of physics, electrical engineering, automation, and renewable energy to conduct experiments to test the performance of solar panels, and the accuracy of AI cameras in classifying waste, and evaluate the stability and efficiency of the control circuit. The results were measured and analyzed based on scientific standards.

The team designed a solar battery system and calculated the capacity of the reserve tank for the metal can sorting and pressing system. The system runs at full load for 5 hours during the day and stores energy to operate for an additional 2 hours at night; it is capable of classifying materials using a high-resolution AI camera, integrating an AI model to identify materials by colors, shapes, sizes and materials. After image processing, AI will label each type of waste, plastic, metal cans or organic waste, which will be automatically moved into the right trash bins. Metal cans will be compressed before rolling down.

Anh Thu said that the testing of the solar-powered waste classification system showed its efficiency in operation and environmental protection. In the coming time, the group will develop the research by using compressed air to control for more flexibility in speed and adjustment; and upgrade the system for more operation efficiency.

According to Teacher Le Thi Ngoc Hanh,  Le Quy Don Gifted High School, the two students demonstrated excellent teamwork, completing the task effectively and efficiently. The research is of high practicality due to its broad applicability, sustainability, energy and cost savings, as well as its capacity to enhance waste management efficiency and promote recycling. It addresses current environmental and energy challenges while aligning with the future trends of green technology and automation development.

H.N

Translated by N.T