Wireless AI Perception: A New Sense for Machine Intelligence
Principal Investigator: Dr. Chenshu WU (Assistant Professor from Department of Computer Science)
This project is showcased in the second exhibition – Digitization in Innovation Wing Two
Principal Investigator: Dr. Chenshu WU (Assistant Professor from Department of Computer Science)
This project is showcased in the second exhibition – Digitization in Innovation Wing Two
Research interests:
• Mobile and wireless AIoT systems
• Digital health
• Ubiquitous computing
• Internet of Things
Email: chenshu@cs.hku.hk
Website: https://cswu.me
Can Machines Sense without Cameras/Sensors?
Computer vision enables machines to “see”. The capability of machine vision based on cameras, however, is fundamentally limited to a certain field-of-view with good lighting conditions – they cannot see through any occlusions or in the dark.
Wireless sensing opens a new sense for machine perception to decipher the physical world, even in absolute darkness and through walls and obstacles.
It can capture human activities invisibly in a contactless and sensorless way.
Still use Wi-Fi for the Internet only? You are missing a lot!
Wireless AI perception leverages ambient wireless signals (such as Wi-Fi / millimeter-wave / UWB signals) to enable ubiquitous sensing.
Wireless sensing technology turns a Wi-Fi device into an all-in-one sensor and revolutionizes sensing from sensor-based to sensorless.
Wireless sensing utilizes ambient Wi-Fi signals to analyze and interpret human motions and object movements, underpinning many sensing applications such as motion detection, sleep monitoring, fall detection, gait recognition, etc.
What’s Next?
The next big deal for wireless technologies is not about communication, but sensing.
With wireless AI perception, Wi-Fi sensing will enter billions of devices and millions of homes, creating a smarter space for a smarter life. Now is just the beginning of this revolution.
Please feel free to give your enquiry / feedbacks to the research team by filling the form (https://forms.gle/JV59N47nTj19ndYz6). Thank you!