Gaussian Distribution Model for Detecting Dangerous Operating Conditions in Industrial Fish Farming

Abstract

The development of better monitoring technologies, the early combat of outbreaks, massive mortality, and promoting sustainability are challenges that the aquaculture industry still faces, and the development of solutions for this is an open problem. In this paper, focusing our attention on monitoring technologies as a promising solution to these issues, we report a Gaussian distribution model for detecting dangerous operating conditions in industrial fish farming. This approach allows us to indicate through a 2D image visualization when fish production is under normal, warning, or dangerous operating conditions. Furthermore, our proposed method has promising possibilities for application in the most varied fields of science, given that the mathematical procedure described allows us to discover the fundamental statistical structure of physical, chemical, and biological systems governed by laws of a probabilistic nature.

Keywords

• data processing
• mathematical models
• probability and statistics
• Gaussian distribution model
• industrial fish farming