An IoT-Based Aquaculture Monitoring System Using Firebase

Indonesia is a producer in the fisheries sector,with production reaching 14.8 million tons in 2022.The production potential of the fisheries sector can be optimally optimized through aquaculture management.One of the most important issues in aquaculture management is how to efficiently control the fish pond water conditions.IoT technology can be applied to support a fish pond aquaculture monitoring system,especially for catfish species(Siluriformes),in real-time and remotely.One of the technologies that can provide this convenience is the IoT.The problem of this study is how to integrate IoT devices with Firebase’s cloud data system to provide reliable and precise data,which makes it easy for fish cultivators to monitor fishpond conditions in real time and remotely.The IoT aquaculture fishpond monitoring use 3 parameters:(1)water temperature;(2)pHwater level;and(3)turbidity level of pond water.IoT devices use temperature sensors,pH sensors,and turbidity sensors,which are integrated with a microcontroller and Wi-Fi module.Data from sensor readings are sent to the Firebase cloud via theWi-Fi module so that it can be accessed in real time by end users with an Androidbased mobile app.The findings are(1)the IoT-based aquaculture monitoring system device has a low error rate in measuring temprature,pH,and turbidity with a percentage of 1.75%,1.94% and 9.78%,respectively.Overall,the total average error of the three components is 4.49%;(2)in cost analysis,IoT-based has a cost-effectiveness of 94.21% compared to labor costs.An IoT-based aquaculture monitoring system using Firebase can be effectively used as a technology for monitoring fish pond conditions in real-time and remotely for fish cultivators that contribute to providing an IoT-based aquaculture monitoring system that produces valid data,is precise,is easy to implement,and is a low-cost system.

A compact underwater stereo vision system for measuring fish

contributes for decisions at several production levels.However,taking length measurements is a cumbersome task that,when applied to living individuals,can induce considerable stress,increasing the risk of damage or hindering their growth.Computer vision is one of the most used non-contact tools to overcome this issue,being fast,consistent and repeatable.However,its use in aquatic environments is limited by the high cost,the difficulty of calibrating the system in underwater conditions and the complexity of implementation.This paper proposes a low-cost easy-to-use vision system that can take measurements on live fish in aquatic conditions,without the need for a special calibration or a demanding in-water calibration service.The present work implemented a compact stereo vision system and developed a method that estimates the correct length of fish,based on the variation of the angle of incidence of the light rays in the water.Given some structural conditions such as a short baseline,the system is able to measure fish with an error of less than 1%.The short baseline allows to have a compact system and reduces the effect of water refraction on the 3D reconstruction.A set of experiments were performed with real fish,working robustly for a set of orientations of the fish(even when the caudal fin and snout are on different distances to the cameras).