Ananda Roy, Senior Product Line Manager at Synaptics (https://www.synaptics.com), demonstrated their latest AI-enhanced Wi-Fi sensing technology at Embedded World 2025. Utilizing their compact Wi-Fi chip, the 43752, integrated into the Astra Machina development kit, Synaptics showcased a method of environmental sensing through Wi-Fi signal deflection. The chip operates by exchanging packets with a router, interpreting signal reflections to detect the presence and movements of people within a room.
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Synaptics is my Embedded World 2025 video coverage sponsor, check out my Synaptics videos here: https://www.youtube.com/playlist?list=PL7xXqJFxvYvhAbQoe9YN4c84SqXxIY3fQ
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The technology relies on analyzing Channel State Information (CSI) from Wi-Fi signals, creating graphical representations that AI algorithms interpret. Synaptics has developed machine learning models capable of identifying subtle indicators, such as human breathing, which appear as regular, periodic wave patterns. Larger movements produce distinctly wider patterns, allowing clear differentiation between stationary presence and active motion.
Ananda explained that the AI model operates with defined confidence thresholds to accurately distinguish between various activities, ensuring reliable detections. Currently, the model is finely tuned to differentiate between stationary breathing and significant movements, but its capabilities extend beyond this initial scope. Through additional training, the AI can identify specific situations, such as falls, multiple occupants, or unique motion signatures, significantly broadening its potential applications in security, healthcare, and smart homes.
A key advantage highlighted by Ananda is the absence of additional hardware requirements. Since Wi-Fi is already standard in most IoT devices, Synaptics’ technology eliminates the need for supplementary sensors like radar or Ultra Wideband (UWB), enabling cost-effective and seamless integration. Devices equipped with existing Wi-Fi capabilities can immediately utilize this advanced sensing feature.
This approach leverages Wi-Fi’s widespread availability, making it practical for diverse environments. Synaptics’ system effectively uses environmental RF signal reflections, providing a non-invasive and privacy-friendly alternative to cameras or intrusive sensors. By harnessing inherent wireless infrastructure, it becomes possible to enhance existing IoT products, offering scalable sensing capabilities without extensive modifications.
Synaptics’ implementation demonstrates how AI-driven interpretations of Wi-Fi signals can significantly expand traditional connectivity roles, transforming passive network hardware into active sensing infrastructure. This technology presents valuable use cases, such as occupancy detection, elder care monitoring, fall detection, and home automation, demonstrating a notable step forward in smart environment interactions.
The demonstration at Embedded World 2025 showcased not only technical feasibility but practical versatility, emphasizing Synaptics’ approach toward integrated, minimally intrusive environmental sensing solutions. As the AI model evolves, Anand suggested it could be further trained to recognize specific patterns, such as counting occupants or detecting emergency events, enhancing its adaptability to diverse real-world scenarios.
Synaptics’ demonstration emphasized the shift from specialized, single-purpose sensors toward multifunctional use of commonplace technologies, highlighting the potential of Wi-Fi as a robust sensing medium. This advancement supports the integration of more intelligent, responsive environments without significant hardware complexity or cost overhead, representing a notable development for the IoT and connected device industries.
Check out all my Embedded World 2025 videos in this playlist: https://www.youtube.com/playlist?list=PL7xXqJFxvYvjgUpdNMBkGzEWU6YVxR8Ga
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