How to Create Edge AI Models for Industrial Sensor Nodes

How to Create Edge AI Models for Industrial Sensor Nodes

Industry 4.0 will see every essential machine, robot, and motor constantly monitored to quickly detect condition status and predict required maintenance. The data and analysis from these system-wide automation processes will provide vital actionable decision-making information that will increase efficiency, lower costs, and improve safety, ultimately increasing revenues.

Continuously monitoring systems allow manufacturing organizations to do process optimizations and plan maintenance during regular maintenance cycles. While significantly reducing the costs and downtime associated with unplanned maintenance, predictive maintenance also reduces unnecessary manual check-ups and the premature replacement of equipment before the end of normal duty cycles.

Using sensor nodes for this monitoring lets manufacturers get valuable insights and control and make decisions in real-time without disrupting production systems. Retrofitting production systems with Edge AI sensor nodes means not only a significant reduction of investment and depreciation costs but also less downtime and minimal interference in the production process.

The final puzzle piece is the need for software solutions to transform the sensor data at the edge into actionable insights at scale to drive the business value.

This webinar will show how to build this type of Edge AI application using the onsemi RSL10 Sensor Development Kit and the SensiML Analytics Toolkit.

About The Speaker

Theo Kersjes - Application Manager, onsemi

Theo manages a team of product definers and applications engineers for power and sensing solutions. He started his career at Philips/NXP focusing on digital video processing and moved from the Netherlands to the San Jose Bay area to work on broadband routers, VoIP and cable modem systems. In the RF group Theo gained diverse experience developing products for Hearing-aid digital-signal-processors, and Wi-Fi modules. And in the NXP applications group he managed a team working on digital-power point-of-load, Wi-Fi and ZigBee applications. Joining a start-up, he developed unique 60Ghz wireless connectivity products with top electronics companies. Theo has three patents issued and is a public speaker.

Chris Rogers - CEO, SensiML

With over 25 years of experience running embedded systems, wireless communications, and algorithm development businesses, Chris has led high caliber teams at companies ranging from Intel to startups. As CEO and founder of SensiML, his drive is to offer industry-leading tools that empower all developers with the ability to create amazingly smart and beneficial IoT devices and applications. Prior to spinning out SensiML from Intel Corporation, Chris was general manager of Intel’s Quark/Curie machine learning software tools business and held prior positions as product line manager turning around Intel’s $750M business in Wi-Fi and Bluetooth modules. An engineer at heart, Chris started his career in automotive test/measurement building bespoke embedded systems for major US automotive suppliers and test vendors. He holds a bachelor’s in Mechanical Engineering and an MBA from Carnegie Mellon’s Tepper School of Business.

Giveaway

Three lucky webinar attendees will receive an RSL10 SensiML starter pack, including the RSL10 Sensor Development Kit.

Key Takeaways

Learn more about how onsemi and SensiML have collaborated to deliver a complete machine learning solution.

• Articulating the benefits of bringing centralized, cloud-based sensor data analytics to the IoT edge
• Describing key use-cases for edge AI within the industrial sector
• Understanding the overall workflow required to build edge AI sensor applications
• Learning how to easily implement edge AI using the onsemi RSL10 Sensor Development Kit and SensiML tools