Bangjie Sun, Sean Rui Xiang Tan, Zhiwei Ren, Mun Choon Chan and Jun Han. 2022. Detecting Counterfeit Liquid Food Products in a Sealed Bottle Using a Smartphone Camera. In The 20th Annual International Conference on Mobile Systems, Applications and Services (MobiSys ’22), June 25–July 1, 2022, Portland, OR, USA. ACM, New York, NY, USA, 14 pages. Acceptance Rate: 21.6% (38 of 176). Best Poster Award [paper] [project website]

Abstract

We are witnessing a surge in the reported cases of counterfeit liquid products in the market including olive oil, honey, and alcohol. Counterfeiters often adulterate the liquid products by replacing a large portion of the authentic content with cheaper substitutes (e.g., mixing vodka with cheaper alcohol or potentially toxic methanol). Exacerbating the problem, the counterfeits are packaged and sealed to factory standards, rendering it extremely difficult for an average consumer to identify them. While solutions exist, they are often impractical for the general public as they require specialized and costly equipment. To overcome these limitations, we propose LiquidHash, a novel counterfeit liquid food product detection system. LiquidHash is a practical solution that only requires the use of a commodity smartphone to detect adulterated liquid products without opening the bottles. LiquidHash works by detecting and tracking the shape and movement of air bubbles that form inside the bottles. We implement LiquidHash and evaluate its feasibility with real-world experiments under varying conditions with a total of more than 500 minutes of video recording and observe an overall detection accuracy of up to 95%.