Abstract:
The increasing demand for sustainable aquaculture has highlighted critical challenges in
maintaining water quality and managing surface debris in fish ponds.The aquaculture
industry has raised significant challenges in maintaining water quality in fish ponds and
managing surface debris. Maintaining optimal water quality and keeping pond surfaces
clean creates a favorable environment for fish farming, which is crucial for fish growth
to reducing stress label and disease on the aquaculture.Traditional manual methods of
water quality monitoring and pond cleaning are labor-intensive and inefficient. With the
increasing adoption of automation and AI-powered technologies, we are aimed development
of an autonomous boat designed to optimize fish farm management. The boat is equipped
with sensors to monitor important water quality parameters and a garbage collection
system to ensure clean pond surfaces, contributing to a healthier fish farming environment.
The primary objective is to monitor water quality using sensors and analyze the data
with machine learning for accurate predictions and automatically collects debris using
a camera-based detection process and operates sustainably with solar energy. A userfriendly interface ensures ease of use, making it ideal for remote areas.The integration of
water quality sensors, a garbage collection system, and solar-powered energy makes the
boat a valuable tool for fish farmers seeking to optimize their operations.The design and
implementation of this autonomous boat aims to make fish farming more sustainable and
productive by reducing manual labor and operational costs but also supports the long-term
sustainability of fish farming practices and increasing precision in pond maintenance.
