Advanced E-Waste Facility Locator: Harnessing Convolutional Neural Networks for Sustainable Environmental Impact and Recycling Solutions

This research paper focuses on addressing the environmental harm caused by the increasing number of electronic devices in the modern world. As technology advances, the usage of electronic devices such as smartphones, tablets, and laptops has surged. While some of these devices can be repaired when damaged, many are either left unused at home or discarded in regular waste bins, leading to significant environmental hazards in the coming years. Although e-waste facility centres are available, users are often reluctant to visit these locations. To tackle this issue, we propose a solution in the form of an application that utilizes an API to connect users with vendors located in specific areas. The key features of this application include user interaction, mapping, and a reward system. This will be beneficial for both the user and the vendor who are present at that location, and it will also reduce the impact on the environment.