Nivedita Arora

Qitong Li, Raj Nileshbhai Dave, Rhema Amanda Phiri et al.

Rapid environmental change and advances in data-driven analysis highlight the need not only to use computational tools, but also to foster understanding of the natural world and inspire creativity. Photosynthesis, the process that fuels nearly all life on Earth, provides a compelling context for such learning, particularly in understanding how plants alter their photosynthetic strategies in response to environmental changes. However, existing tools for studying photosynthesis are often inaccessible or limited to demonstrating its presence, rather than capturing its temporal dynamics. We present PhytoBits, a frugal in situ gas-exchange sensing toolkit for distinguishing and teaching photosynthetic strategies. PhytoBits combines leaf enclosure with accessible materials, an off-the-shelf CO\textsubscript{2} sensor, and a low-cost microcontroller, to support multi-day monitoring of plant gas-exchange in educational and research contexts. We validated PhytoBits against research-grade gas-exchange systems, confirming that it identifies C\textsubscript{3} and CAM (Crassulacean Acid Metabolism) photosynthetic pathways. In addition to obligate CAM, PhytoBits also resolves facultative CAM and developmental CAM dynamics in plants. This work presents an early-stage hardware validation; user deployment studies, open-source code dissemination, and automated pathway classification are planned as future work.

Jack Thoene, Omar Kamil, Thekra Alkadee et al.

Deep understanding of a field's soil moisture content is the leading indicator for predicting crop yields and making data driven decisions for irrigation and application of topical chemicals for drought resilience. Despite this importance, the cost of adopting and maintaining IoT infrastructure prevents modern farms from employing widespread real time soil moisture sensors. We present an end-to-end platform of buried battery-free sensor nodes and a mobile basestation that leverages the farmer's daily routine for data retrieval. Each node features a self-powered galvanic soil-moisture probe, employing a high impedance analog front end to enable durability. Operating entirely on harvested solar energy for up to 21 days on a single capacitor charge, each node collects soil moisture, temperature, and environment condition data. Using a predictable finite-state machine, handshake-based data exchanges occur with a basestation affixed to standard farming vehicles designed to listen for the nodes while moving through the farm. Our platform organizes all sensor, link-quality, and location data into an easy-to-interpret dashboard to seamlessly integrate with the farmer's everyday routine. Costing less than $35, the platform is a financially accessible, accurate, and easily scalable platform that enables persistent, regular data collection from the most rural plots without adding to or impeding farming operations. Experimental evaluation demonstrates reliable communication over 1 km at 2 dBm transmit power, stable sensor readings over 70 days of indoor operation, and continuous data recovery during multiple periods of intermittent connection.

Nivedita Arora, Ali Mirzazadeh, Injoo Moon et al.

Augmenting everyday surfaces with interaction sensing capability that is maintenance-free, low-cost (about $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 (about 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.