Examining the effect of aquaculture using sensor-based technology with machine learning algorithm

This article envisages a new flanged technique for monitoring the aquaculture. Since a new conservative method is needed for monitoring the feed of fish, this article introduces an Internet of Things (IoT)-based system with integration of improved decision machine learning algorithm (IDMLA). The advancement in system on chip technologies has been emerging as a platform for monitoring the important parameters like quality of water, range, velocity and flow of water pumps. All the parameters if monitored correctly will increase the lifetime of fish. Therefore, a sensor-based technology has been used for monitoring the necessary parameters which is easily connected in low cost. The IDMLA has been tested with the information in database system by using an online monitoring system, and the results are plotted using MATLAB where the efficiency of IDMLA is more efficient when compared with other techniques.