The two companies have collaborated to integrate Artificial Intelligence (AI) into a high-performance people-counting sensor, which overcomes the challenge of monitoring attendance in large spaces with multiple entrance points.
With the digitization of building occupancy, Schneider is following its mission to be its customers' digital partner for sustainability and efficiency by delivering new and highly valuable insights such as queue monitoring to assist smart building management while respecting individuals' privacy by design. The advanced IoT sensor has been developed by combining the high expertise of ST's AI group and the deep sensor-application expertise of
The prototype people-counting sensor combines a LYNRED ThermEyeTM family thermal imager, integrated in a unique ultra-low-power design created by
"This promising technology opens a new solution for attendance monitoring and people counting in numerous applications such as monitoring queues, building usage, and social distancing," said Maxime Loidreau, IoT Sensors Program Manager at
"This project demonstrates the power of deep learning to enhance embedded data-processing performance, showing how high-value applications can be hosted on a cost-effective microcontroller-based platform," added
Further Technical Information
The STM32 AI ecosystem provides essential building blocks for neural networks to run on STM32 MCUs, enabling a cost-effective and power-efficient solution. Various deep-learning frameworks such as Keras, TensorFlow(TM) Lite, and ONNX exchange format are supported natively.
Included in the ecosystem is the X-CUBE-AI software expansion package, which extends the capabilities of the STM32CubeMX initialization tool to automatically convert pre-trained neural networks, generate optimized libraries for the target MCU, and integrate these into the user's project. Additional support to automate laborious development tasks includes several ways of validating neural network models and measuring performance on STM32 MCUs without creating the necessary C code by hand.
The general DNN approach supported by ST's software-development ecosystem, mapped onto the rich STM32 portfolio, lets users efficiently replicate development effort to create products for multiple markets. The STM32H723 MCU powering the demonstration at ST Live Days has excellent credentials for hosting AI applications, including high core performance, up to 1Mbyte Flash, high-speed off-chip memory interfaces, and integrated features for connecting a wide variety of sensor types.
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At ST, we are 46,000 creators and makers of semiconductor technologies mastering the semiconductor supply chain with state-of-the-art manufacturing facilities. An independent device manufacturer, we work with our 100,000 customers and thousands of partners to design and build products, solutions, and ecosystems that address their challenges and opportunities, and the need to support a more sustainable world. Our technologies enable smarter mobility, more efficient power and energy management, and the wide-scale deployment of the Internet of Things and 5G technology. Further information can be found at www.st.com.
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