Smart Bin with Level Sensing and Real Time Automation

Traditional waste collection methods follow fixed schedules, often leading to bins being either half-empty when collected or overflowing before collection occurs. Existing smart bin models provide basic fill-level monitoring but still face major limitations such as poor sensor performance in harsh weather, lack of physical overflow prevention, insecure access, and limited use of predictive analytics. These issues result in inefficiencies, unhygienic surroundings, and increased operational costs for municipal bodies. This research proposes a Smart Bin system designed to address these shortcomings through real-time sensing and automation. The bin is equipped with climate-resistant ultrasonic sensors for accurate fill-level detection and an ESP32 microcontroller with Wi-Fi for seamless data transmission. At $90 \%$ capacity, the system alerts garbage collectors through a mobile application that provides fill status, location, and collection time. At $\mathbf{1 0 0 \%}$ capacity, an automatic lid mechanism prevents overflow and unauthorized dumping. Secure passcode-based access ensures only authorized collectors can open the bin. GPS integration supports optimized routing, while predictive analytics use historical data to estimate future fill times and enable proactive scheduling. The proposed system improves collection efficiency, reduces overflow incidents, and enhances accountability, offering a practical, scalable solution for both urban and rural waste management.