The food industry is currently moving from its producers around the world through production and distribution chains to their customers or final consumers. These chains are highly vulnerable to contamination, the spread of diseases, or even bioterrorism. This industry represents a massive $5.5 trillion-dollar business today. However, it is facing a crisis of reliability due to the environment, or as a result of inadequate or insufficient practices during the production process. Governments recognize this vulnerability, and because of this, they have developed standards and standards to enforce laws that are enforced. These existing procedures to achieve food security are largely unworkable since the problem lies not in installing new processes in the production chain, but in the lack of robust monitoring systems that can ensure the safety of food from the start of the productive process in the farm, until the end of this process. In the present research, a hybrid methodology is proposed for the development of a Monitoring System of Biological Stability for the Aquaculture Industry, which complies with the most important International Safety Standard, ISO 22000. This methodology integrates one of the most important areas of artificial intelligence, Multi-Agent Systems (SMA), whose programming paradigm goes beyond other paradigms at the level of abstraction and versatility, where each agent is responsible for attending an independent process, thus, the combined behavior of said agents produces an intelligent overall result Another technology that is integrated is Workflow, which studies and automates the operational aspects of work activity: how processes are structured and executed, their order correlated, synchronization and how information flows between them. In addition, ornamental fish is a novel commercial industry, in terms of aquaculture, we seek to optimize spaces because they are small ponds where the ideal conditions should be characterized for a kind of specie and diverse features associated with this type of fish.