Home Manufacturing Self Healing Machine Learning for IoT and Industrial Use

Self Healing Machine Learning for IoT and Industrial Use

No, it’s not science fiction. It is real life. In the not too distant future, with technology continuing to advance at the rate it is now, we’ll soon be seeing artificial intelligence (AI) based machines like never before. These new-style AI will be able predict when they’ll break down and set to work making adjustments before that happens. The’ll be able to run diagnostics, order new parts, and schedule an engineer to carry out the repairs at the same time. This is what the continuing evolution of Industrial Internet of Things (IIoT) technology will bring upon us (among other things).

Machine learning is critical to any IIoT system and is the key to improving business outcomes. The more information a company has access to, the better informed their business choices will be. Machines are able to sort through large amounts of data much quicker than humans can, and this is primarily where they are used within the realms of machine learning and IIoT.

For companies that haven’t already integrated AI into their business models, now is the time to do so. Generally the first step is to consolidate all machine data into one central location. Machines can quickly sort and analyze data that comes in all different formats, saving you valuable time and money. Algorithms are used by the machines in order identify patterns in the data and builds an overall analytical model as a result.

Using machine learning as part of an IIoT system will give you much greater insight into the business’ movements, trends, successes, and failures. But to really benefit from the AI, that information needs to somehow be incorporated back into the business to initiate change where necessary. As each machine progresses through its lifecycle, its state will change. To maintain accuracy, it’s vital you track these changes and retrain digital models accordingly.

Automation is another area of AI that companies will need to embrace as part of the future. By automating how analytics are employed, how those results are used, and what action should be taken, businesses will stand a chance at competing with others at the top of their game.

Machine learning should be an important part of any successful business, but it needs to be implemented correctly in order to be efficient. The successful integration of analytics, machine learning, automation and other aspects of IIoT now will help companies survive the competition moving forward.

Source IOT Business News

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KC Cheung
KC Cheung
KC Cheung has over 18 years experience in the technology industry including media, payments, and software and has a keen interest in artificial intelligence, machine learning, deep learning, neural networks and its applications in business. Over the years he has worked with some of the leading technology companies, building and growing dynamic teams in a fast moving international environment.
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