Dive into the foundational principles and evolution of Origin’s cutting-edge wireless sensing technology alongside ongoing research and developments shaping the future of wireless sensing.


Origin’s Wireless Sensing Journey

  • In 2009, DARPA enlisted the expertise of Dr. Ray Liu, a Distinguished University Professor at the University of Maryland, College Park, to address a critical problem hindering in-submarine wireless communication in emergency situations – that wireless signals tend to interfere with and cancel each other in enclosed environments, especially in the confined space in submarines with highly irregular interior surfaces. 
  • Dr. Liu’s proprietary purpose-built solution using special wireless signaling not only resolved the submarine communication problem but also sparked his curiosity and vision about applying the experience and knowhow for other applications – to solve everyday domestic problems using smart radio. This is where the concept of wireless sensing was born. As a result, Origin was founded by Dr. Liu and emerged as the first pioneer in the field. Origin Research is the research arm of Origin.
  • Since 2013, Origin Research has been dedicating itself to pioneer the understanding and exploration of the underlying science of wireless signal propagation in enclosed environments and the associated wireless “channel state information” using extensive research experimentation, rigorous mathematical formulation and deep machine learning. Over the years, Origin Research has achieved pivotal scientific discoveries, some of which were shared with the academic research community in prestigious journals. 
  • Based on the solid mathematical foundation of the basic science, Origin Research has developed in support of Origin’s business units a rich technology platform with a plethora of AI analytics engines utilizing the ubiquitous WiFi signals to monitor presence, motion, movement, location, intrusion, occupancy, vital sign, gait, sleep, fall, and more. More information about various engines will be provided below.
  • In 2019, Origin successfully enabled its first major industrial partner to launch a motion detection service over mesh WiFi, setting the stage for WiFi sensing to revolutionize the entire home environment. Since then, Origin has expanded and refined its collection of AI analytics engines and used them to work with partners to launch many powerful WiFi sensing products and services, winning many prestigious awards along the way. As of now, Origin is the first-ever WiFi Sensing company to deploy with Tier-1 internet service providers, Tier-1 IoT and Tier-1 security companies. In turn, partners’ feedback helps to guide Origin’s research.
  • From simple but effective tricks to sophisticated algorithms and systems, Origin Research has a lot of intellectual properties to protect. To this end, Origin Research has about 100 patents issued or allowed, with another 100+ patents filed, covering a wide spectrum of wireless sensing techniques, algorithm constructs and system designs.

The Fundamental Breakthroughs

Time-reversal physics has been known for a long time but mostly found development in research labs and applications in defense-related military applications. The Origin team was the first to bring time reversal to the practice and use of our daily lives by leveraging radio-frequency multipaths in indoor or multipath-rich environments and proving that it can work effectively. 

Using the time-reversal principle, our team developed the world’s first centimeter-accuracy indoor positioning and tracking system in 2015 with only a single transmitter and terminal device, both with a single antenna, in a completely non-line-of-sight environment. It represented the first non-line-of-sight, non-triangulation technique for accurate position estimation, solving a long-standing conundrum of indoor positioning/tracking for decades.

We further showed that when there is a large enough number of multipath signals (such as in indoor environments), the time-reversal focusing spot exhibits a stationary behavior in its energy distribution. Specifically, in the limit of large time-resolved multipath signals, the time-reversal spot has a spatially independent structure that follows a Bessel-function power distribution. This means that the time-reversal spot structure is inherently independent on location and environment. Thus, the distance an object has moved and its speed can be determined. 

This is an unprecedented discovery in that one can now accurately/reliably estimate/detect the speed of a moving object indoors without line-of-sight. The more multipaths, the better the performance, defying and contrary to any prior scientific beliefs. It was a groundbreaking discovery that broke the impasse of the almost two-century-long quest for new physics that could rival the Doppler effect. Not only did it enable accurate tracking of an unlimited number of subjects indoors without costly infrastructure or a-priori measurements, but it also served as the theoretical foundation for accurate/reliable wireless sensing by simply using ambient radio waves, including WiFi.

With that, our team at Origin developed an AI platform that includes many analytic engines with endless applications, including the following:

  • Indoor tracking
  • Gait determination
  • Motion detection for security
  • Sleep monitoring
  • Monitoring small motions inside a car
  • Material sensing
  • Monitoring heart rate and breathing
  • Heart rate variability detection
  • Fall detection
  • Recognizing and counting people in hidden spaces
  • Millimeter-wave imaging
  • Millimeter-wave real-time handwriting tracking and analysis
  • Millimeter-wave keystroke tracking
  • Sound detection

Our team was the first to propose in 2019 the establishment of an international standard on wireless sensing to the chair of the IEEE 802 Standard Committee, who facilitated the creation of 802.11bf WLAN Sensing as the world’s first wireless sensing standard.

A Science Based on Solid Physical Principles and Deep Understanding of AI

The science we developed is rooted in the solid time-reversal physical principles we discovered in the past decade, as well as our decades of pioneering discoveries and experiences in signal processing, machine learning, and AI. This sets us apart from most of our competitors, who have employed heuristic algorithms and pseudoscience that might work in lab conditions but are not robust enough to cover most scenarios of use cases.

Are you ready to explore the groundbreaking advancements in wireless sensing science? Our comprehensive white papers below will take you to the latest innovations in wireless AI, from the science, principles, technology development, and development of IEEE 802.11bf WLAN Sensing standards to real-world applications transforming the way we live and work.

An Unparalleled World-Class Track Record

Dr. K. J. Ray Liu is the founder, former CEO, and now chairman and CTO of Origin, pioneering AI for wireless sensing and indoor tracking. The invention of wireless AI, he’s won three prestigious CES Innovation Awards, including CES Best of Innovation in 2021.

Dr. Liu served as the 2022 Institute of Electrical and Electronics Engineers (IEEE) president and CEO and the 2019 IEEE vice president for technical activities. He has also served as the 2012–2013 president of the IEEE Signal Processing Society, where he once served as the editor-in-chief of IEEE Signal Processing Magazine.

He was Distinguished University Professor, Distinguished Scholar-Teacher, and Christine Kim Eminent Professor of Information Technology of the University of Maryland, College Park, from where he retired after over three decades in education. His research contributions encompass broad aspects of signal processing and communications, with over 10 books and 800 peer-reviewed publications. He has trained 74 doctoral/postdoctoral students, 12 of whom are now IEEE fellows. According to the Mathematics Genealogy Project, he has had over 200 doctoral descendants worldwide.

Dr. Liu is the recipient of two IEEE Technical Field Awards: the 2021 IEEE Fourier for Signal Processing and the 2016 IEEE Leon K. Kirchmayer Graduate Teaching Award. He also received the IEEE Signal Processing Society 2014 Norbert Wiener Society Award and the 2009 Claude Shannon-Harry Nyquist Technical Achievement Award. Recognized as a Web of Science Highly Cited Researcher, he is a member of the National Academy of Engineering and a Fellow of IEEE, the American Association for the Advancement of Science (AAAS), and the National Academy of Inventors.