The success of wireless and mobile systems has led to a digital infrastructure that is integrated into the fabric of the physical world at a scale unimaginable two decades ago. This has come to be known as the internet of things, or the IoT. Batteryless devices constitute the largest component of this infrastructure, as they are attached to clothing, food, drugs, and manufacturing parts. However, due to their batteryless nature, these devices were assumed to be intrinsically limited in bandwidth, range, and sensing capability. To overcome these limitations, existing approaches required designing new hardware that replaces the hundreds of billions of devices already deployed.
In this talk, I will describe how our research enables transforming batteryless devices into powerful sensors without modifying their hardware in any way, thus bringing direct benefits to the billions of devices deployed in today's world. Specifically, I will describe how we can extract a sensing bandwidth from batteryless devices that is 10,000x larger than their communication bandwidth, and how we can extend their operation range by over 10x. I will also describe how we have designed novel inference algorithms and learning models that build on these techniques to deliver a variety of sensing tasks including sub-centimeter positioning, deep-tissue communication, and non-contact food sensing.
The systems we have built have transformative implications on smart environments, healthcare, manufacturing, and food safety. They enable agile robots to operate in non-line-of-sight environments where vision systems typically fail. They have led to the first demonstration of communication with deep-tissue batteryless micro-implants in a large living animal (pig) from meter-scale distances. Most recently, we demonstrated the potential of using these techniques to sense contaminated food in closed containers. I will conclude by describing how rethinking the abstractions of computing will enable us to bring the next generation of micro-computers to exciting new domains ranging from the human body to the depth of the ocean.
Fadel Adib is an Assistant Professor at MIT and the founding director of the Signal Kinetics research group at the MIT Media Lab. His research develops innovative technologies and algorithms for wireless perception, networking, and sensing with a focus on biomedical sensing, autonomous systems, and subsea IoT.
Adib received his PhD in 2016 from MIT and Bachelor's in 2011 from AUB. He has been named to Technology Review's list of the world's top 35 innovators under 35 (TR35) in 2014 and to Forbes' list of 30 under 30 in 2015. His research on seeing through walls has been named as one of the 50 ways MIT has transformed computer science over the past 50 years. His work has also won best demo and honorable mentions at ACM CHI (2015) and ACM MobiCom (2015) and was selected to the CACM Research Highlights (2018). His research has been repeatedly featured in major media outlets including the BBC, CNN, The Wall Street Journal, The Washington Post, and The Guardian. Adib is also the recipient of the William A Martin Master's thesis Award from MIT (2013), the Sony Career Development Chair (2016), the Google Faculty Research Award (2017), the AUB Distinguished Young Alumnus Award (2017), the Sprowl's Dissertation Award from MIT (2017), the ACM SIGMOBILE Doctoral Dissertation Award (2018), the NSF CAREER Award (2019), and most recently the ONR Young Investigator Award (2019).
Adib has had the honor to demo his research to President Obama at the White House (2015) and in the UK House of Lords (2015). Currently, his research is being commercialized by a startup called Emerald Innovations, and his devices are being used by doctors at major US hospitals to monitor patients with Alzheimer's, Parkinsons', and Multiple Sclerosis.