Cloud-Enabled Electronic Waste Tracking and Traceability Solutions Using Random Forest Algorithm
Raveendra N Amarnath, V. Vijayabaskar, V. Kannagi, Shanmugam Kolangiammal, M. Muthulekshmi, G. S. Gayathri · 2024
The environmental effect and intricate electronic waste (e-waste) supply chain make its management a significant challenge. Better e-waste management is possible with cloud-enabled monitoring and traceability technologies. To make e-waste tracking and monitoring systems more accurate and efficient, a new method that uses the Random Forest algorithm is proposed. This system allows tracking e-waste at every stage of its lifespan, from collection to disposal, using cloud computing, real-time data gathering, and predictive analytics. The Random Forest algorithm forecasts the location and eventual disposal of e-waste objects depending on ownership, condition, and location. This algorithm is renowned for its sturdiness and capacity to manage massive datasets. It shows that our proposed method optimizes e-waste management procedures, improves resource allocation, and minimizes environmental impact via case studies and simulations. Deploying cloud-enabled e-waste monitoring and traceability systems in real-world settings presents several challenges, including scalability, security, and practical application issues. It helps to develop sustainable waste management procedures.