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EcoX: An Autonomous IoT-Enabled Underwater Robot for Real-Time Microplastic Detection and Monitoring
Summary
An autonomous IoT-enabled underwater robot integrating turbidity, optical particle, pH, UV, and temperature sensors enables real-time detection and monitoring of microplastic particles in rivers and ponds, with data encrypted and streamed to a cloud dashboard. Scalable robotic monitoring platforms could overcome the labor-intensity and spatial limitations of traditional microplastic sampling methods.
The tenacious rise in microplastic contamination across water bodies threatens aquatic ecosystem and human body. Traditional methods for monitoring such pollutions are often limited, sporadic and labor intensive, making them inadequate for timely and scalable environmental response. This proposed model will introduce an autonomus IoT-enabled underwater robot specially patented for autonomously detecting, monitoring and analyzing microplastic particles in real-time. The system integrates sensors such as turbidity sensor, optical particle sensor, pH sensor, Ultrasonic sensor, turbidity sensor, UV sensor and temperature sensors. The ESP32 serves as an edge device for real-time data processing. Data is transmitted through GSM or Wi-Fi protocols, secured with AES-256 encryption. This ensures seamless and secure communication between the local server and the system. The underwater robot autonomously performs action by detecting the presence of microplastic in different places in a river or pond. Users can control the robot using a remote control if the autonomous system faces any sensor malfunctions, navigation error or power depletion. The robot can then be safely guided to a predefined recovery point or instructed to resume operations after troubleshooting. The system is powered by a hybrid solution using solar energy and rechargeable batteries, promoting sustainability. By using Ubidots the data will visualize that are collected from the local server. The Robo-Driven architecture will offer autonomous and a cost-effective solution to monitor microplastic pollution. By combining sensor driven intelligence, autonomous navigation, secured communications and real-time monitoring, this proposed model enables precise environmental assessment and proactive pollution mitigation.