Industrial 5.0 Aquaponics System Using Machine Learning Techniques

Due to the advancements in digital technology, the fifth industrial revolution, also known as aquaponics, has brought changes in the traditional manufacturing and industrial processes. The primary objective of the industry 5.0 initiative is to encourage customization and innovation while simultaneously increasing the productivity, efficiency, and adaptability of manufacturing processes. The industry's coming to terms with the 5.0 vision is underpinned by machine learning. It makes it possible for machines and systems to see patterns in data, make decisions based on that data, and learn without having to be explicitly programmed. Algorithms that learn from machines are able to analyze vast amounts of data collected from sensors, machines, and other sources in order to make predictions, improve processes, and acquire insights. This capacity has applications in a variety of domains, including quality control, predictive maintenance, supply chain optimization, process optimization, and autonomous robots. Machine learning-based predictive maintenance reduces downtime and optimizes maintenance schedules by detecting industrial equipment faults. Machine learning-powered quality control systems monitor manufacturing, identify errors, and ensure product quality. U sing machine learning algorithms on supply chain data improves inventory management, logistics, and efficiency. Process optimization uses machine learning to find trends in production data to improve efficiency and energy use. Machine learning-enabled autonomous robots and intelligent decision- making systems help humans complete complicated tasks safely and efficiently. Aquaponics is a major step toward a more connected, intelligent, and data-driven industrial landscape.