WASTE COLLECTION CART ASSISTANT FOR STREET SWEEPERS USING ARDUINO

Abstract

The Waste Collection Cart Assistant aims to address persistent issues in waste management by introducing an automated system powered by Arduino technology and artificial intelligence. Designed to support street sweepers, this innovative device enhances the segregation and transportation of waste, promoting both efficiency and environmental sustainability. It ensures accurate sorting of biodegradable and non-biodegradable waste, helping to minimize the environmental footprint caused by improper disposal. Additionally, the cart’s mobility feature improves accessibility, enabling workers to cover larger areas with less physical effort. Overall, the system seeks to create a cleaner, more sustainable environment while optimizing the performance of local waste management operations. This study utilizes an experimental research design to develop, implement, and assess the effectiveness of the Waste Collection Cart Assistant. The system aims to automate waste segregation processes while enhancing the operational efficiency of street-sweeping activities. By reducing manual effort and increasing the precision of waste classification, the system significantly improves the efficiency of waste collection. Preliminary tests demonstrate that the automated mechanism accurately identifies and separates biodegradable from non-biodegradable waste with consistent reliability. The Waste Collection Cart Assistant is an automated system developed to assist street sweepers in Barangay Sta. Monica, Novaliches, Quezon City. Incorporating Arduino-based technology and artificial intelligence, the cart aims to reduce physical workload, improve waste segregation, and enhance overall waste collection efficiency. Guided by an experimental research design, the study focused on the system’s development and evaluation. Results show improved operational efficiency through reduced manual labor and more accurate segregation. User feedback reported increased productivity, though minor usability issues were identified. Despite its benefits in promoting better waste management and environmental awareness, limitations such as battery dependency and occasional waste classification errors suggest the need for future enhancements, including solar charging and more advanced AI sorting features.