Our Research Learning food and water contaminants using wireless signals 

Cartoon depiction of smartphone being used to check food safety

Photo Credit: Adib Research team

Cartoon depiction of wireless reader and sticker that would be placed on food product

Photo Credit: Adib Research team

Test sticker and sensor

Photo Credit: Adib Research team

Cartoon depiction of smartphone being used to check food safety

Photo Credit: Adib Research team

Cartoon depiction of wireless reader and sticker that would be placed on food product

Photo Credit: Adib Research team

Test sticker and sensor

Photo Credit: Adib Research team

Principal Investigator

Fadel Adib

  • Associate Professor
  • Program in Media Arts and Sciences
  • MIT Media Lab

Fadel Adib is an associate professor at MIT and the founding director of the Signal Kinetics research group at the MIT Media Lab. His research group develops innovative technologies and algorithms for wireless perception, networking, and sensing. Professor Adib received his PhD in 2016 from MIT and Bachelor’s in 2011 from the American University of Beirut. His doctoral research on seeing through walls was named as one of the 50 ways MIT has transformed computer science, and itis currently being commercialized and utilized in medical studies at major US hospitals. Professor Adib has had the honor to demo his research to President Obama in the White House and in the UK House of Lords. His awards include the NSF CAREER Award, the ONR Young Investigator Award, and being named as one of the world’s top 35 innovators under 35.

Challenge:

Can we sense food and water contaminants using wireless signals? Can we perform this sensing using low-cost, ubiquitous wireless technologies?

Research Strategy

  • Transform few-cent off-the-shelf stickers (RFIDs) into non-contact RF spectroscopes and use the spectroscopic measurements to infer material contents and discover contaminants
  • Develop algorithms and machine learning models for extracting large bandwidth from RFIDs and detecting contamination
  • Building a practical system and evaluating it in real environments

Project description

Food safety is a matter of global concern. Reports of foodborne illness outbreaks increasingly make news headlines as growing urbanization and changing consumer habits across the globe align with an uptick in the overall consumption of prepared foods. Food contamination and foodborne pathogens cause sickness and even death, though there are other costs as well: the wasted labor and resources that occur when a contaminated product is disposed of; the lost profit to affected companies; and the lost food products that could have nourished a number of people.

Developing a tool to quickly and accurately assess whether or not a given product is contaminated could help minimize costs and lower public health effects of food pathogen outbreaks. This funded project is meeting this challenge with a food safety sensor that uses wireless signals to determine food quality and safety using an RFID sticker placed on a food product’s container. This system turns off-the-shelf RFID tags into spectroscopes which, when read, can measure the material contents of a product without the need to open its package. The sensor can also identify the presence of contaminants—pathogens as well as adulterants that affect the nutritional quality of the food product. If successful, this research, and the technology that results, will pave the way for wireless sensing technologies that can inform their users about the health and safety of their food and drink.

Outcomes

  • Developed RF-EATS, the first RFID-based sensing system that can noninvasively sense food and liquids in closed containers
  • Designed and built AI that can can infer dielectric changes from contamination and verify the authenticity of food and liquids using wireless signals
  • Created multiple hardware prototypes that were demoed and evaluated in real-world scenarios (100+ companies, 50+ policymakers), demonstrating accuracy, efficiency, and robustness

Publications

News

Additional Details

Impact Areas

  • Water
  • Food

Research Themes

  • Sensors & Monitoring

Year Funded

  • 2019

Grant Type

  • Seed Grant

Status

  • Completed