IoT-Based Ghost Net Shredder Monitoring System

Abstract

Abandoned, lost, and discarded fishing gear (ALDFG), commonly known as ghost nets, presents significant environmental and socio-economic challenges by causing marine entanglement, coral reef degradation, and microplastic pollution. One of the initiatives to mitigate this problem is the introduction of the shredder machine at the Eco House, Waste Collection Centre, Pulau Besar, Mersing, Johor. However, the operation requires close monitoring to ensure efficiency and to prevent motor overheating that may result from overuse. Relying on manual monitoring is inefficient, especially in island communities where both manpower and technical resources are limited. This study presents the design and development of an Internet of Things (IoT)-based monitoring system for the ghost net shredders using the ESP32 microcontroller. The system integrated temperature and vibration sensors with an ESP32 microcontroller and relay control. Data were displayed locally on an LCD and transmitted to the Blynk mobile application for real-time remote visualization and notifications. A prototype was deployed and tested at Pulau Besar, demonstrating reliable sensor performance and stable wireless communication without operational interruptions. The system successfully enhanced predictive maintenance and maintained continuous operation even when powered by the photovoltaic (PV) system. The findings confirm the feasibility of combining IoT monitoring with renewable energy to promote safer, more sustainable ghost net recycling, offering a scalable model for coastal and island communities.