Cite this Article

Gopika P, Gayathri S, Dhanapriya K, 2025. "Self-Healing AI Systems in Industrial IoT Environments", International Journal of Research in Artificial Intelligence and Data Science(IJRAIDS)1(2): 48-61.

The International Journal of Research in Artificial Intelligence and Data Science (IJRAIDS)
© 2025 by IJRAIDS
Volume 1 Issue 2
Year of Publication : 2025
Authors : Gopika P, Gayathri S, Dhanapriya K
Doi : XXXX XXXX XXXX

Keywords

Self-Healing Systems, Industrial IoT, Artificial Intelligence, Fault Detection, Predictive Maintenance, Autonomous Recovery, Edge Computing, Real-Time Monitoring.

Abstract

AI and the Industrial Internet of Things (IIoT) have teamed up to build a new sort of self-healing technology that can cure itself. These systems find faults, figure out what caused them, and fix them right away. This cuts down on the time individuals have to wait and the necessity for them to get up and move. More and more organisations need strong, self-sustaining infrastructures as they rely on linked devices and data-driven processes. Self-healing AI uses machine learning, predictive analytics, and the ability to make decisions on its own to deal with the many different ways that things in modern factories depend on one other. Not only can systems handle mistakes, but they can also learn from them and adjust so that they don't happen again.

AI systems that can fix themselves work in a loop: they check the system's health, figure out what went wrong by modelling the data, find the best fix, and then learn from each time it happens to make future replies better. Federated learning, which lets models be trained in a decentralised way while keeping data private, and edge computing, which helps choices be made closer to the data source, are two important aspects that make this possible. These technologies work together to make systems that can respond rapidly and get better as the work gets harder.

These forms of technology also help with bigger goals, like making operations more efficient and better for the environment. Longer-lasting assets, lower maintenance costs, and safer workplaces are good for many businesses, such shipping, manufacturing, and energy. AI that can fix itself saves time and money by making systems less likely to crash and operate better. It also helps the system keep up and running, which is mandated by law.

Self-healing AI systems are a huge step forward in technology and change how we think about reliability and maintenance. The earlier ways of handling maintenance were planned and reactive. Now, adaptable, data-driven methods are taking their place. This not only does the system work better, but it also frees people from doing the same things over and over so they can focus on strategic positions that demand new ideas and critical thinking.

There is a lot of promise in self-healing AI, but it is not straightforward to apply on a large scale. There will always be issues with data quality and integration, cybersecurity, and the need for AI that can be explained to keep things open. Another significant area of research is figuring out how to construct models that work effectively with many different tools and in many different situations. Still, AI researchers, experts in some fields, and industrial engineers are working together to come up with long-lasting solutions.

This paper examines the theoretical underpinnings and practical applications of self-healing AI inside IIoT environments. It looks at existing designs, the roles of different AI methods, and examples from top companies that are leading this change. Next, the conversation turns to problems and how more research could enable AI systems that can fix themselves become more common. AI will be able to build smart, powerful industrial ecosystems that don't need much aid from people to stay healthy as it grows better. With the Industrial Internet of Things (IIoT) and Artificial Intelligence (AI) become more integrated, systems might be able to discover, diagnose, and correct problems on their own, without any aid from individuals. This article talks about the new idea of AI systems in factories that can fix themselves. It speaks a lot about architectures, techniques, real-time case studies, and places where further study could be done in the future. The goal is to show how self-healing AI may help major industrial applications stay up and running, save money, and be more stable.

Introduction

The fourth industrial revolution, often known as Industry 4.0, is altering how businesses work by bringing together new technologies including the Internet of Things (IoT), cyber-physical systems, and Artificial Intelligence (AI). Utility networks, energy grids, industrial floors, and logistical hubs are all going online and becoming digital more and more. This makes them harder to use and more likely to break, get hacked, or not work at all. A lot of people are talking about self-healing AI systems right now because they could be a game-changing method to make Industrial IoT (IIoT) settings more robust and last longer.

Self-healing AI is a smart system that can check its own health, find problems or strange occurrences, and fix them straight away without anybody else having to help. These systems are like the body's immune system. They see a problem, figure out what it is, respond in a way that makes sense, and then learn from it so that it doesn't happen again. Machine learning (ML), deep learning (DL), and edge computing are all coming together to make these kinds of flexible, powerful infrastructures that can fulfil the needs of modern industrial environments.

Self-healing skills are crucial in an industrial setting for more than just keeping systems running. They are also vital for keeping expenses down and personnel safe. Think of a smart factory where vibration analysis tells a machine when it is about to break down. To protect itself, it shuts down for a short time and tells a nearby backup system to take control. Things will go more smoothly if you think ahead and plan ahead swiftly. You won't have to mend things by hand as often. It also stops small problems from getting worse, which keeps people and things safe.

Self-healing AI can also learn, which is another nice point. Every day, these systems get better at what they do by learning new things, adapting to their surroundings, and remembering what they've done in the past. They can handle changes in how they work better because they are continually learning. This happens when the supply chain breaks down, demand changes, or hardware breaks. When utilised on a large scale over many industrial nodes, this produces a network of smart agents that work together and talk to each other to keep the system working well.

Edge computing is a crucial part of this design because it lets processing and decision-making happen closer to where the data is stored. This reduces latency and the necessity for servers to be in one place. Self-healing systems that act at the edge can learn from what happens in one area and use that information to improve a model of group intelligence. This protects both privacy and performance.

There is a lot of promise for self-healing AI systems, but it will be challenging to get them to function in factories. We need to focus on making sure that old equipment can operate together, standardising data, making models available, and enhancing cybersecurity in order to develop confidence and make sure that systems work well. Also, sectors need to change the way they do things so that they don't just fix things when they break. Instead, they should manage their systems proactively and on their own. This will need both investing in technology and training workers.

This paper intends to deliver an exhaustive analysis of self-healing AI systems inside IIoT contexts, scrutinising their fundamental design, facilitating technologies, and practical implementations. The study lays the groundwork for future innovations that will transform the functioning of intelligent, autonomous industrial systems by examining successful implementations and pinpointing the key problems. Industry 4.0, also known as the fourth industrial revolution, is changing how factories and other businesses work by combining AI, the Internet of Things, and cyber-physical systems. As industrial processes are more networked, the systems that run them get harder to use and less safe. Self-healing AI systems are a new way to solve these problems since they let machines fix their own problems. These systems watch over things and remedy them when they go wrong by using machine learning (ML), deep learning (DL), and edge computing.