This study focuses on development of a solar-powered Arduino Mega-driven robotic boat designed for efficient fish feeding in aquaculture. By integrating IoT technology and a mobile app, the project aims to reduce labor costs and improve feeding practices while addressing challenges associated with manual feeding, which previously failed to adequately cover the entire pond area. The research specifically centers on Nile tilapia production. Experimental results show that the robot emulates manual feeding with an average response time of 1.82 s for feeding initiation and 2.17 s for movement initiation. It efficiently distributes feed across a 4000 m² area in 9 min, outperforming the manual method, which takes 32 min. Fish fed by robotic boat exhibit an 18.71 % weight gain compared to those fed by hand. The robotic boat farm consumes a total of 11.480 kg of feed to produce 7.6 kg, while the hand-fed farm required 16.185 kg of feed to produce 6.5 kg. This results in feed conversion ratios of 1.51 and 2.49, respectively. The study finds an overall cost reduction of 46.13 % due to decreased labor hours. We strongly recommend adopting this robotic boat for optimizing tilapia feeding in earthen ponds.

本研究重点开发太阳能驱动的 Arduino Mega 机器人船，专为水产养殖中高效喂鱼而设计。通过集成物联网技术和移动应用程序，该项目旨在降低劳动力成本并改善饲养方法，同时解决与人工饲养相关的挑战，此前人工饲养未能充分覆盖整个池塘区域。该研究特别集中于尼罗罗非鱼的生产。实验结果表明，该机器人模拟人工喂食，开始喂食的平均响应时间为1.82 s，开始运动的平均响应时间为2.17 s。它在 9 分钟内有效地将饲料分配到 4000 平方米的区域，优于需要 32 分钟的手动方法。与人工喂养的鱼相比，机器人船喂养的鱼体重增加了 18.71%。机器人船农场总共消耗 11.480 公斤饲料才能生产 7.6 公斤，而手工喂养农场需要 16.185 公斤饲料才能生产 6.5 公斤。这导致饲料转化率分别为 1.51 和 2.49。研究发现，由于工时减少，总体成本降低了 46.13%。我们强烈建议采用这种机器人船来优化土池中罗非鱼的饲养。