Recent research conducted by EARTHDAY.ORG in 2023 has brought attention to a pressing concern in trash management: a staggering 6.3 billion metric tons of plastic waste is being generated with just 9% of it being successfully recycled. This research paper intends to develop Kiosk-Based Recycle System (KBRS) which incorporates machine learning technology to address the considerable issues of effective waste management. A deep learning algorithm built into the system helps to precisely identify and categorize waste with a focus on enhancing recycling processes and reducing environmental impact. The utilization of YOLOv8 in real-time garbage detection enables effective classification of waste into recyclable and non-recyclable items, hence fostering environmental sustainability. Extensive unit testing and user acceptability testing (UAT), producing satisfactory findings that demonstrate the system’s effectiveness and reliability. This study highlights the capacity to combine technology with environmental conservation initiatives suggesting a scalable method that may be easily used in many metropolitan environments.