STM Journals Peer-reviewed research from Consortium e-Learning Network

Journal of Polymer & Composites Original Research Special issue

A Low-Cost Multi-Sensor IoT System for Real-Time Segregation of Polymer Waste

  1. Pankaj Mudholkar Faculty of Computer Applications, Marwadi University, Rajkot
  2. Megha Mudholkar Department of Computer Engineering, Marwadi University, Rajkot

Abstract

Segregation of solid waste is a critical aspect of waste management, especially in settings where technical and financial constraints limit the adoption of sophisticated technologies. The proposed low cost, sensor-driven smart waste sorting system combines a variety of sensing technologies with an integrated decision-making system. The system employs an inductive sensor, moisture sensor and capacitive sensor to measure the physical properties of waste items, allowing segregation into metal, wet and dry polymer classifications. On the other hand, a rule-based decision system was created in Arduino to interpret the sensor data in real time, avoiding complicated ML approaches. A simple data pre-processing technique using sensor readings averaging was also introduced to enhance accuracy. The waste bins were also monitored through an IoT-based remote monitoring system. The system performed satisfactorily under different environmental conditions with 90 different samples with a 96.7% accuracy for metal, 90% for wet waste, and 86.7% for dry polymer waste. The average processing time was 1.5 to 2 s per item which means that it is fast enough to be usable. The research proves the feasibility of real-time waste separation with no complicated algorithm in a cost-effective way. The multi-sensor system achieves a good compromise between accuracy, simplicity, and scalability, suitable for deployment on a small, low-scale and low-cost.

Keywords

References (32)

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