More than anything else, the foundational power of personnel in fieldwork merely lies in the fact that we can see. ​ By extension, it makes sense that the biggest impact on industrial digital transformation will come from embedding vision in intelligent connected components. ​ More so when embedded vision and AI software are widely deployed in mobile and battery-powered field equipment. ​ To learn more about building this capability into industrial products, I invited Taylor Cooper for a chat on the podcast. ​ Taylor is the CEO and Principal Engineer at MistyWest where he's recently led the company in developing an Embedded Vision System on Module (MistySOM), based on the Renesas RZ/V2L processor, that enables the embedding of vision-based AI capabilities in field equipment. ​ Below is the outline of our conversation. ​ ✅ Misty West, Embedded Vision & IIoT ✅ Latest Trends in Industrial IoT, and Chip Shortage ✅ Google IoT Core Retirement, IoT Boom and Bust ✅ MQTT in IIoT and Computer Vision ✅ Delivering AI Capabilities for IIoT with Renesas RZ/V2L Based System on Module ✅ Potential Applications of Low Power System on Module in Connected Intelligence, ✅ Workflow for developing Embedded Vision for Connected Products ✅ AI versus Rules-Based Image Processing in Embedded vision ✅ Selecting Embedded Vision Middleware ✅ Selecting wireless connectivity for Embedded Vision Applications