Design and Implementation of an IoT-Based System for Monitoring Endangered Beaches

Abstract

Beach pollution is an escalating global issue, posing a significant threat to marine ecosystems and human health. Plastic waste, originating from commercial activities, fishing, and improper waste management, is prevalent on beaches worldwide. This debris is transported by rivers and waterways, leading to widespread contamination. Additionally, climate change and pollution are expected to result in the loss of many sandy beaches, altering ecosystems and diminishing natural recreational areas. For this reason, an IoT-based system has been developed that, using low-cost autonomous cleaning robots on different beaches, can collect data and detect garbage using the new YOLO V10 architecture. As a result, the system was successfully implemented to store and alert users when a beach has a high level of pollution. It efficiently collects and saves data from multiple beaches in a safe NoSQL Database using multiple robots simultaneously. Additionally, the highest performance predictive model achieved an accuracy of 77.69%, a recall of 71.63%, and an F1 score of 74.53%.