Artificial intelligence (AI) and machine learning (ML) can collect vast amounts of data at the edge. Utilizing this, it is possible to implement predictive maintenance solutions for embedded systems that address failure issues occurring in manufacturing sites, and to utilize them in the field.

Microchip will present on 'Implementing Predictable Maintenance Solutions in Embedded Systems' using Edge ML at the Microchip Tech Insights Korea online webinar series to be held on the 25th.

As the computational power of AI and ML gradually increases, cost-effectiveness in the industrial and manufacturing sectors is gradually rising. In addition, ready-made solutions gradually emerged in the market, leading to increased adoption by the industry.

Accordingly, Microchip plans to introduce a predictive maintenance solution utilizing ML at the edge. Il Kim, the lead presenter, will cover the requirements for AI and machine learning (ML) today, the causes of the acceleration of AI adoption, ML definitions and training methods, software and tools, Microchip's AI and ML portfolio and application areas, and a demo demonstration.

In addition, we will explore how to support data collection, model building, verification, and deployment by combining Microchip's product portfolio with partner solutions, and introduce a 'real-time demo of a fan anomaly detection system' to help develop predictive maintenance applications.

Kim Il, the head, stated, “Applications in the field of artificial intelligence where Microchip products can be applied include smart embedded vision, smart predictive maintenance, smart human-machine interfaces, and workstation and server management applications.”

This Microchip webinar series will run for three days until the 27th, featuring presentations on topics ranging from artificial intelligence and machine learning to stability and security, and connectivity and embedded solutions. On the day of the seminar, you can ask questions and receive answers via live Q&A chat.