Leveraging CNN and IoT for Effective E-Waste Management
This addresses environmental and health risks from improper e-waste disposal for recycling industries, but it is incremental as it combines existing technologies like CNN and IoT.
The paper tackles the problem of electronic waste management by proposing an IoT-enabled system with a lightweight CNN for classifying e-waste materials, resulting in improved identification and routing for recycling workflows.
The increasing proliferation of electronic devices in the modern era has led to a significant surge in electronic waste (e-waste). Improper disposal and insufficient recycling of e-waste pose serious environmental and health risks. This paper proposes an IoT-enabled system combined with a lightweight CNN-based classification pipeline to enhance the identification, categorization, and routing of e-waste materials. By integrating a camera system and a digital weighing scale, the framework automates the classification of electronic items based on visual and weight-based attributes. The system demonstrates how real-time detection of e-waste components such as circuit boards, sensors, and wires can facilitate smart recycling workflows and improve overall waste processing efficiency.