STMicroelectronics & Schneider Electric unveil prototype IoT sensor

STMicroelectronics, a Swiss semiconductor manufacturing company, and Schneider Electric, a leading provider of automation and energy digital solutions for sustainability and efficiency, have reportedly announced that they have developed a new prototype IoT sensor that facilitates a better understand building occupancy levels and application.

This collaboration has seen both companies together integrate AI (Artificial Intelligence) within a high-performance people counting sensor, solving the issues related with checking attendance in big spaces with various entry gates.

The queue monitoring solution would help in smart building management and also respect the privacy of individuals using its design. The new enhanced IoT sensor has essentially been developed by integrating the expertise of ST’s AI group with the Schneider’s immense experience in making deep sensor applications, to effectively identify and insert a top performing object recognizing neural network in a tiny MCU (microcontroller).

Schneider Electric’s utilization of STM32Cube AI. toolchain, which can support the making of AI applications for a wide portfolio of ATM32 MCUs, has allowed it to have much higher efficiency and flexibility in hardware design through the ease of use and engineering resources offered by the STM32Cube software creation ecosystem.

The developed prototype sensor integrates an LYNRED ThermEye family thermal imager, which is integrated into a ultra-low power design made by Schneider Electric, along with a Yolo powered Neural Network model operating on the recently launched STM32H723 MCU. 

IoT Sensors Program Manager, Schneider Electric, Maxime Loidreau stated that the new promising technology brings a new solution to attendance monitoring as well as crowd counting across various applications like social distancing, building usage, and monitoring queues.

AI Solutions Business Line Manager, STMicroelectronics, Miguel Castro stated that the IoT sensor showcases the strength of deep learning to improve the performance of embedded data processing, demonstrating how high-value applications would be hosted upon a cost-effective microcontroller (MCU) based platform.

Castro further added that the company’s STM32Cube AI ecosystem helps users to make flexible solutions within a rapid time to market window.

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