Current developments in wearables and body sensors have largely overlooked measuring the risk of eye damage due to UV radiation. This work addresses that gap by designing smart glasses capable of measuring UV exposure directly incident on the eyes. Leveraging a UV sensor by AMS-Osram and a compact ESP32S3 microcontroller, our prototype collects UVA/B/C data in real time. We developed a data pipeline to convert raw sensor output into spectral irradiance and compare fluence values against established ICNIRP ocular UVR exposure thresholds. Preliminary field measurements indicate ocular UV exposure often exceeds safety limits, demonstrating the urgency of this problem and the feasibility of our approach. Our work lays the foundation for affordable, wearable UVR monitoring tools that could support preventative eye care and future smart eye-wear designs. This paper issues a timely call to the body sensor network (BSN) and physiological sensing communities to integrate UV sensors into smart glasses.

We have witnessed explosive growth in computing devices at all scales, in particular with small wireless devices that can permeate most of our physical world. The IoT industry is helping to fuel this insatiable desire for more and more data. We have to balance this growth with an understanding of its environmental impact. Indeed, the ENSsys community must take leadership in putting sustainability up front as a primary design principle for the future of IoT and related areas, expanding the research mandate beyond the intricacies of the computing systems in isolation to encompass and integrate the materials, new applications, and circular lifecycle of electronics in the IoT. Our call to action is seeded with a circularity-focused computing agenda that demands a cross-stack research program for energy-harvesting computational things.

Augmenting everyday surfaces with interaction sensing capability that is maintenance-free, low-cost (∼ $1), and in an appropriate form factor is a challenge with current technologies. MARS (Multi-channel Ambiently-powered Realtime Sensing) enables battery-free sensing and wireless communication of touch, swipe, and speech interactions by combining a nanowatt programmable oscillator with frequency-shifted analog backscatter communication. A zero-threshold voltage field-effect transistor (FET) is used to create an oscillator with a low startup voltage (∼ 500 mV) and current (< 2uA), whose frequency can be affected through changes in inductance or capacitance from the user interactions. Multiple MARS systems can operate in the same environment by tuning each oscillator circuit to a different frequency range. The nanowatt power budget allows the system to be powered directly through ambient energy sources like photodiodes or thermoelectric generators. We differentiate MARS from previous systems based on power requirements, cost, and part count and explore different interaction and activity sensing scenarios suitable for indoor environments.

We present Surface++, which leverages our previous work SATURN, a self-powered flexible acoustic sensor, and ZEUSSS, a passive wireless sound communication technique using analog backscatter, to create a scalable and self-sustainable wireless sound sensing surface. Our new prototype allows for large area acoustic sensing using modular fabrication techniques with the promise of being fully printable. A single small Surface++ patch can be used to extend voice and gesture input for everyday surfaces, while our more sensitive Surface++ modular array allows for large-area context sensing and localization.