Landis+Gyr: Sense and Landis+Gyr Announce Collaboration on 1MHz Processing for the Revelo? Grid Sensing Platform at DTECH

Sense and Landis+Gyr announced their collaboration and work with the semiconductor industry to bring 1MHz sampling to the Revelo®? grid sensing platform. High sampling rates like those demonstrated by Sense and Landis+Gyr in booth 2708 at DISTRIBUTECH International (DTECH) 2025 are feeding a new class of AI models, able to operate efficiently within the meter itself, offering utilities an ultra-high resolution view of the distribution grid and supporting the next generation of consumer applications. The DTECH demonstrations will highlight how Sense's technology transforms AMI 2.0 meters into a high-resolution sensing, compute, and control platform for the modern grid, delivering: Arc fault detection: Identifying electrical faults in real time to prevent fires, equipment damage, and service disruptions; Edge-based AI processing: Running advanced machine learning models directly on the meter for faster, more scalable insights; Improved grid reliability: Continuously monitoring device-level usage to anticipate demand spikes, abnormal behavior, and potential outages; Operational efficiency: Reducing unnecessary service calls and manual inspections through remote diagnostics; Customer engagement: Providing personalized, actionable energy insights through existing utility infrastructure. Sense and Landis+Gyr announced their collaboration and work with the semiconductor industry to bring 1MHz sampling to the Revelo®? grid sensing platform. High sampling rates like those demonstrated by Sense and Landis+Gyr in booth 2708 at DISTRIBUTECH International (DTECH) 2025 are feeding a new class of AI models, able to operate efficiently within the meter itself, offering utilities an ultra-high resolution view of the distribution grid and supporting the next generation of consumer applications. The DTECH demonstrations will highlight how Sense's technology transforms AMI 2.0 meters into a high-resolution sensing, compute, and control platform for the modern grid, delivering: Arc fault detection: Identifying electrical faults in real time to prevent fires, equipment damage, and service disruptions; Edge-based AI processing: Running advanced machine learning models directly on the meter for faster, more scalable insights; Improved grid reliability: Continuously monitoring device-level usage to anticipate demand spikes, abnormal behavior, and potential outages; Operational efficiency: Reducing unnecessary service calls and manual inspections through remote diagnostics; Customer engagement: Providing personalized, actionable energy insights through existing utility infrastructure.