Optimization Of Portable Floating Net Cages Based On Internet Of Things And Robot Operating System For Smart Navigation And Water Quality Monitoring

A portable floating net cage system is developed in this project to support aquaculture monitoring by integrating the Internet of Things (IoT) with the Robot Operating System (ROS 2). The system is designed to measure water quality parameters while autonomously navigating within the aquaculture area. To perform environmental monitoring, the device utilizes several sensors, including a pH sensor, a DS18B20 temperature sensor, and a turbidity sensor. These sensors are connected to an ESP32 microcontroller that processes the collected data and transmits it using the MQTT communication protocol. The navigation capability of the system is managed by a Pixhawk flight controller integrated with a GPS module, enabling automatic movement across designated locations. System control and monitoring are carried out through Mission Planner and QGroundControl. For power supply, the device relies on a renewable energy system consisting of a 20 Wp solar panel, a Solar Charge Controller (SCC), and a 12V 7.5Ah Li-ion battery, allowing the platform to operate independently in open-water environments. System evaluation is conducted by testing sensor accuracy using standard calibration solutions, followed by the implementation of a Kalman Filter to enhance the stability and reliability of the measurement data. The automatic navigation testing is conducted based on GPS coordinates to assess the accuracy of the device’s movement in the field. The results show that the sensor accuracy reaches 98.2%, with pH error ranging from 0.2% to 5%, DS18B20 temperature sensor error ranging from 0.25% to 0.50%, and turbidity error ranging from 2% to 3.5%.