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Over the years, researchers have explored various approaches for capturing and monitoring the eating activity, one among which is via Wi-Fi channel state information (CSI). CSI-based approaches commonly rely on multi-antenna systems for the capturing and monitoring tasks. With the advent of low-cost, single-antenna IoT devices with CSI measuring capabilities, a question that arises is whether these inexpensive devices can monitor human activities? In this paper we present the SandDune system that demonstrates the possibility of monitoring one human activity–eating–using only inexpensive single-antenna Wi-Fi devices. SandDune is an infrastructure-based system that continuously monitors CSI information to detect the eating activity occurring in its vicinity. When it detects an eating activity, it scrutinizes the signals further to identify all hand-to-mouth eating gestures in the eating episode. We tested SandDune and observed that SandDune can distinguish eating from other activities with an F1-score of 85.54%. Furthermore, it can detect the number of hand-to-mouth gestures that occurred in the eating episode with an error of ±3 gestures. Overall, we believe that a SandDune-like system can enable low cost, unobtrusive eating activity detection and monitoring with potential use-cases in several health and well-being applications. 

Human studies often rely on wearable lifelogging cameras that capture videos of individuals and their surroundings to aid in visual confirmation or recollection of daily activities like eating, drinking, and smoking. However, this may include private or sensitive information that may cause some users to refrain from using such monitoring devices. Also, short battery lifetime and large form factors reduce applicability for long-term capture of human activity. Solving this triad of interconnected problems is challenging due to wearable embedded systems’ energy, memory, and computing constraints. Inspired by this critical use case and the unique design problem, we developed NIR-sighted, an architecture for wearable video cameras that navigates this design space via three key ideas: (i) reduce storage and enhance privacy by discarding masked pixels and frames, (ii) enable programmers to generate effective masks with low computational overhead, and (iii) enable the use of small MCUs by moving masking and compression off-chip. Combined together in an end-to-end system, NIR-sighted’s masking capabilities and off-chip compression hardware shrinks systems, stores less data, and enables programmer-defined obfuscation to yield privacy enhancement. The user’s privacy is enhanced significantly as nowhere in the pipeline is any part of the image stored before it is obfuscated. We design a wearable camera called NIR-sightedCam based on this architecture; it is compact and can record IR and grayscale video at 16 and 20+ fps, respectively, for 26 hours nonstop (59 hours with IR disabled) at a fraction of comparable platforms power draw. NIR-sightedCam includes a low-power Field Programmable Gate Array that implements our mJPEG compress/obfuscate hardware, Blindspot. We additionally show the potential for privacy-enhancing function and clinical utility via an in-lab eating study, validated by a nutritionist. 

With the rapid growth in the number of IoT devices that have wireless communication capabilities, and sensitive information collection capabilities, it is becoming increasingly necessary to ensure that these devices communicate securely with only authorized devices. A major requirement of this secure communication is to ensure that both the devices share a secret, which can be used for secure pairing and encrypted communication. Manually imparting this secret to these devices becomes an unnecessary overhead, especially when the device interaction is transient. In this paper, we empirically investigate the possibility of using an out-of-band communication channel -- vibration, generated by a custom smart ring, to share a secret with a smart IoT device. This exchanged secret can be used to bootstrap a secure wireless channel over which the devices can communicate. We believe that in future IoT devices can use such a technique to seamlessly connect with authorized devices with minimal user interaction overhead. In this paper, we specifically investigate (a) the feasibility of using vibration generated by a custom wearable for communication, (b) the effect of various parameters on this communication channel, and (c) the possibility of information manipulation by an adversary or information leakage to an adversary. For this investigation, we conducted a controlled study as well as a user study with 12 participants. In the controlled study, we could successfully share messages through vibrations with a bit error rate of less than 2.5%. Additionally, through the user study we demonstrate that it is possible to share messages with various types of objects accurately, quickly and securely as compared to several existing techniques. Overall, we find that in the best case we can exchange 85.9% messages successfully with a smart device.