🤖 AI Summary
This study addresses the high cost and large size of conventional water monitoring systems, which hinder their deployment in small-scale or educational settings. To overcome these limitations, the authors propose a miniature squid-inspired underwater vehicle that integrates jet-propulsion actuation, buoyancy regulation, and water sampling into a unified, low-cost platform. Built around an ESP32 microcontroller, the system incorporates an IMU, pressure sensor, GPS, and LoRa communication module, with a total hardware cost of approximately $122.50. Field trials in ponds and lakes demonstrate stable attitude control (roll and pitch deviations within ±2° and ±1.5°, respectively), a depth steady-state error of ±0.1 m, and a heading response rise time of about 2 seconds. The vehicle successfully performed autonomous navigation and water sampling, significantly lowering the barrier to entry for practical aquatic monitoring applications.
📝 Abstract
Water quality monitoring is essential for protecting aquatic ecosystems and detecting environmental pollution. This paper presents the design and experimental validation of a bio-inspired miniature submarine for low-cost water quality monitoring. Inspired by the jet propulsion mechanism of squids, the proposed system employs pump-driven water jets for propulsion and steering, combined with a pump-based buoyancy control mechanism that enables both depth regulation and water sampling. The vehicle integrates low-cost, commercially available components including an ESP32 microcontroller, IMU, pressure sensor, GPS receiver, and LoRa communication module. The complete system can be constructed at a hardware cost of approximately $122.5, making it suitable for educational and environmental monitoring applications. Experimental validation was conducted through pool tests and field trials in a lake. During a 360 degrees rotation test, roll and pitch deviations remained within +/-2 degrees and +/-1.5 degrees, respectively, demonstrating stable attitude control. Steering experiments showed a heading step response with approximately 2 s rise time and 5 s settling time. Depth control experiments achieved a target depth of 2.5 m with steady-state error within +/-0.1 m. Field experiments further demonstrated reliable navigation and successful water sampling operations. The results confirm that the proposed platform provides a compact, stable, and cost-effective solution for small-scale aquatic environmental monitoring.