AI-ops and IoT

AIOps, or artificial intelligence for IT operations, is critical for optimizing IT operations. AIOps combines big data and machine learning to automate IT operations processes, according to Gartner.

The most common application of AIOps is the automation of big data management. This would entail:

• Data from sensors and equipment in factories is collected and integrated.
• The shop floor is being tracked and monitored in real-time, and its performance is being measured against set benchmarks.
• Predictive analytics is being used to identify, predict, and prevent IT service issues, as well as to perform precise capacity planning.
• Big data analytics is being used to track and improve resource utilization as well as cloud infrastructure performance.

Event correlation and analysis, performance analysis, anomaly detection, causality determination, and IT service management are some of the other use cases.

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Smart, connected devices with sensors that generate large amounts of operational data in real-time are referred to as IoT. The Industrial Internet of Things, or IIoT, is a term used in the manufacturing industry to describe this. IIoT can help manufacturing processes achieve higher levels of precision and productivity when combined with AI.

The following are some of the most well-known IIoT use cases:

• Smart glasses, for example, can be used to view instructions hands-free and provide real-time situation awareness.
• For improved workplace safety, continuous monitoring of equipment performance, energy use, environment temperature, and the presence of toxic gases is required.
• For efficient energy consumption, smart lighting and HVAC control are used.
• Data from edge devices on the factory floor is used for industrial analytics.

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