Hedgehog: Detecting Drink Spiking on Wearables

Zhigang Yin, Mohan Liyanage, Agustin Zuniga, Petteri Nurmi, Huber Flores

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review


People increasingly carry wearables and the capabilities of these devices have reached a point where it is increasingly possible to harness the devices to support everyday interactions. We contribute a new use of wearables by demonstrating how they can be used to safeguard against drink spiking, the deliberate act of adding substances to another person's drink. We design Hedgehog, a pervasive sensing approach that re-purposes the optical sensors in off-the-shelf wearables to identify spiked drinks by analysing differences in light reflectivity resulting from small particles inside the drink. We present a wearable prototype inspired by a smart ring design and conduct rigorous experiments and show that Hedgehog reaches up to 89.71% accuracy in detecting drinks that are tampered with. Our work demonstrates how pervasive sensing enables innovative applications and how smart wearables can be re-purposed to support personal safety.
Original languageEnglish
Title of host publicationHotMobile '23: Proceedings of the 24th International Workshop on Mobile Computing Systems and Applications
Number of pages6
Place of PublicationNew York
Publication date2023
ISBN (Electronic)979-8-4007-0017-0
Publication statusPublished - 2023
MoE publication typeA4 Article in conference proceedings
EventInternational Workshop on Mobile Computing Systems and Applications: HotMobile - Newport Beach , United States
Duration: 22 Feb 202323 Feb 2023
Conference number: 24

Fields of Science

  • 113 Computer and information sciences
  • Liquid Sensing
  • Light sampling
  • Wearables
  • IoT

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