Sensing at the Control Level: Leveraging Data for Both Safety and Analytics

Moore's Lobby · 19 May 2026 · 53m · Episode 3

AI in practice: 3 real uses of AI described

What this episode covers

Kate Sokolnicki, Global Business Director for Rockwell Automation's Sensing & Safety business unit, explains the shift from simple on/off sensors to smart devices providing dual-channel process and health data. She details how IO-Link and GuardLink protocols enable condition monitoring and precise fault identification in daisy-chained safety systems, reducing troubleshooting time. Sokolnicki emphasizes that while AI and vision systems are commoditized, their value depends on robust metadata and edge computing, urging young engineers to prioritize practical 'back-of-the-napkin' math over pure theory.

AI in practice

Where this conversation describes AI being used to build or deliver a product. Part of the AI in practice tracker.

ManufacturingRockwell Automation GuardLink protocolapproaching half $1000000 a year

AI-driven analytics on safety sensor data identified when a photoelectric sensor lens was getting dirty in a tire plant, allowing maintenance to clean it before failure, preventing product loss and downtime.

“their savings was, I think, approaching half $1000000 a year, just from that because they weren't checking out tires that are, um, very expensive and and every 2 that stuck together. You didn't just lose one. You lose two.”

Speaker 3 · Hear it at 41:55

Engineering & simulationRockwell Automation Vision AI

AI models analyze images from cameras to perform quality control checks, such as verifying if a label is applied correctly on products.

“we have a product of vision AI. It looks at, um, images of products and can tell, you know, quality control tax is the label on properly, something like that. That's all technically AI.”

Speaker 3 · Hear it at 12:16

Engineering & simulationRockwell Automation Architecture Class drives

AI is combined with motor current signature analysis on Variable Frequency Drives to look for potential failures on the load by analyzing the drive's operation.

“we can combine that with AI to look for potential failures, um, actually on the load, but looking at the drive to see, um, what could be going on.”

Speaker 3 · Hear it at 27:51

Mentioned

Companies
Rockwell Automation, Allen-Bradley
Tools
IO-Link, GuardLink, MQTT, OPC UA
Also
First Robotics

Other shows on the same ground, closest first.

  • Over the Air · 37m

    Making Industrial IoT Work: Lessons from 30 Years in Automation with Grace Technologies

    Drew Allen, CEO of Grace Technologies, discusses the company's 30-year evolution from automation components to industrial IoT solutions, including Graceport interface connectors, electrical safety devices, and wireless vibration monitoring. He explains the technical complexity of vibration analysis using Fast Fourier Transforms and the strategic importance of integrating sensors directly with Rockwell Automation PLCs via Ethernet/IP to serve plant floor operators. Allen highlights a critical failure mode where lack of real-time integration led to an $800,000 transformer arc flash event, emphasizing the need for robust connectivity strategies like LTE and Zigbee in harsh industrial environments.

  • IoT For All Podcast · 27m

    Vinsa’s Daniel Bruce | Empowering IoT Automation with Visual AI

    Daniel Bruce, CEO of Vinsa, explains how visual AI extends IoT by extracting insights from video and imagery rather than just structured sensor data. He details Vinsa's platform, Lira, and its use in industrial inspections, such as reading analog gauges and detecting PPE, to replace expensive manual labor or costly digital sensor retrofits. Bruce outlines key ROI drivers including safety, cost reduction, and quality management, while noting the industry's shift toward niche point solutions and handling AI uncertainty.

  • Lights Out · 52m

    Your Machines Have a Heartbeat: Here's What It's Telling You | Ep #48

    Lauren Dunford, co-founder and CEO of Guidewheel, explains how their platform uses current transformers on power cords to monitor machine electrical heartbeats, providing non-invasive visibility into run, idle, and down states without PLC integration. She details how this data enables cycle counting, anomaly detection, and predictive maintenance, while emphasizing a philosophy of using data to empower teams rather than surveil them. Dunford shares origin stories from her food manufacturing background and describes how customer feedback shaped Guidewheel’s API-first approach, allowing partners like Slytek to layer industry-specific depth onto their broad platform.

  • IoT For All Podcast · 19m

    AI and IoT in the Mining Industry | Razor Labs' Michael Zolotov | Internet of Things Podcast

    Michael Zolotov, CTO and co-founder of Razor Labs, explains how their flagship product DataMind AI uses sensor fusion to predict maintenance failures in heavy mining operations. He details the challenge of high-vibration environments causing false alarms in traditional vibration-only systems and describes how combining camera, oil, and vibration data allows for accurate root-cause diagnosis. Zolotov highlights a specific case where they prevented a major mill failure, saving over $100,000 per hour in downtime, and discusses the importance of building trust through transparent AI evidence rather than black-box predictions.

  • Over the Air · 39m

    Embedded Systems and IoT Connectivity: Lessons from Automate 2024

    Ryan Prosser, CEO of Very Technology, reports from Automate 2024, interviewing leaders from Machine Metrics, Unit X, Sensory Robotics, On Logic, Light Guide, Elementary, Snowbottics, Acme Manufacturing, Happily, Kongitech, MyTech, Lincode, Wheel Me, and Orbit 3D. The conversation covers AI-driven vision platforms, robotic safety sensors, rugged edge computing, and autonomous mobile robots, highlighting the shift toward edge AI and human-centric automation. Key technical discussions include point cloud generation for safety, modular industrial PCs, and AI-based defect detection for high-speed manufacturing lines.

The summary, chapters and topics are generated from the episode’s audio by this directory, not written by Moore's Lobby. The episode itself belongs to its publisher.