SMARTER Updates - January 2026
Layer of smog blankets Salt Lake City in early winter. Photo credit: Salil Bhatt
Greetings from the SMARTER team! Our project, funded by NIEHS and initiated in 2024, is developing community-driven, shared, generalizable metadata and data management tools that support reproducible exposure health research. Sensor metadata is a major focus.
SMARTER Project Updates: Interface Design & Development, Technical Infrastructure, Dissemination
Over the past several months, the SMARTER project has made steady progress across user-centered design and development, technical infrastructure, and dissemination. Below we highlight recent updates and upcoming work as we continue building the SMARTER Sensor Library.
Expanding APIs and Metadata Infrastructure
Our team developed multiple application programming interfaces (APIs) to support interaction between the Neo4j-based Metadata Repository (MDR) and the SMARTER Sensor Library website. These APIs currently support core use cases such as:
Fetching detailed sensor metadata
Browsing sensors by attributes
Categorizing sensors across metadata domains
In parallel, we are actively developing additional APIs to support more advanced functionality, including sorting and filtering, metadata contribution workflows, user reviews, and other community-facing features. These APIs are designed to support both the SMARTER web interface and programmatic access by downstream platforms and tools.
Advancing User-Centered Design of the SMARTER Sensor Library
We conducted multiple brief usability testing sessions with exposure health researchers and research staff to inform the ongoing user-centered design (UCD) of the SMARTER Sensor Library interface. These sessions focused on understanding how users navigate sensor metadata, interpret sensor attributes, and compare sensors for study planning and analysis workflows.
Feedback from these sessions provided actionable insights into layout, terminology, and interaction patterns. Based on these findings, we iterated on the interface design, refining navigation, information hierarchy, and visual presentation of sensor metadata. We are now preparing for additional rounds of testing and evaluation, which will help us to refine the design and test with new types of users, even as development has begun.
If you are able to contribute by participating in remote, user testing sessions where you would briefly test software designs or features, please let us know!
Development in Progress: SMARTER Sensor Library
We are currently developing a proof-of-concept SMARTER Sensor Library website, integrating early interface designs with the underlying metadata repository and APIs. This effort is focused on validating end-to-end workflows—from metadata ingestion and storage to user-facing discovery and comparison—before scaling to a full production deployment.
Recent Dissemination and Community Engagement
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Podium Presentation:
Shishupal, S., Gouripeddi, R., Cummins, M., Facelli, J., & Sward, K. (2025). Developing a US Air Quality Shapelet Repository for High Temporal Resolution Environmental Health Studies. 2025 Europe Regional Chapter of the International Society of Exposure Science (ISES Europe 2025), Lisbon, Portugal
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Poster Presentation:
Im, S., Jandhyala, L., Sward, K., Facelli, J., Motagi, P., Cummins, M., & Gouripeddi, R. (2025). Metadata-centric Approaches for Incorporating Sensors into Exposure Health Informatics Ecosystem. The 3rd Annual DELPHI Data Science Symposium (DELPHI 2025), Salt Lake City, UT
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Webinar presentation on SMARTER as part of the Environmental Health Language Collaborative webinar series: https://www.niehs.nih.gov/research/programs/ehlc/events
Date: Friday, December 12, 2025
Webinar title: “Sensors and Metadata for Analytics and Research in Exposure Health (SMARTER)”.
Speakers:
Mollie Cummins, PhD, RN, FAAN, FACMI, Professor of Nursing and Biomedical Informatics at the University of Utah.
Ram Gouripeddi, MBBS, MS, FAMIA, Assistant Professor of Biomedical Informatics and an Assistant Director of Informatics at the Clinical and Translational Science Institute at the University of Utah.
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Shah-Mohammadi F, Im S, Facelli JC, Cummins MR, Gouripeddi R. Scaling sensor metadata extraction for exposure health using LLMs. Preprint posted online August 2025. doi:10.1101/2025.08.21.25334173
Background The rapid evolution and diversity of sensor technologies, coupled with inconsistencies in how sensor metadata is reported across formats and sources, present significant challenges for generating exposomes and exposure health research.
Objective Despite the development of standardized metadata schemas, the process of extracting sensor metadata from unstructured sources remains largely manual and unscalable. To address this bottleneck, we developed and evaluated a large language model (LLM)-based pipeline for automating sensor metadata extraction and harmonization from exposure health literature publicly available.
Methods Using GPT-4 in a zero-shot setting, we constructed a pipeline that parses full-text PDFs to extract metadata and harmonizes output into structured formats. Results: Our automated pipeline achieved substantial efficiency gains in completing extractions much faster than manual review and demonstrated strong performance with average accuracy and precision of 94.74%, recall of 100%, and F1-score of 97.28%.
Conclusions This study demonstrates the feasibility and scalability of leveraging LLMs to automate sensor metadata extraction for exposure health, reducing manual burden while enhancing metadata completeness and consistency. Our findings support the integration of LLM-driven pipelines into exposure health informatics platforms.
Available here: https://www.medrxiv.org/content/10.1101/2025.08.21.25334173v1
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Nelson R, Taber P, Motagi P, et al. Needs, Preferences, and Challenges of Environmental Health Researchers in Using Sensors: A Content Analysis (Preprint). JMIR Human Factors. Preprint posted online January 12, 2026. doi:10.2196/preprints.91311
Background:
Environmental exposures can influence human health in complex ways. It remains difficult for researchers to integrate exposure data, partly due to an unmet need for informatics and metadata tools.
Objective:
The purpose of this study was to understand the needs, preferences, and pain points of environmental health researchers regarding the selection, deployment, and integration of sensors for their research studies, to inform user requirements for a sensor metadata repository.
Methods:
We purposively recruited six exposure health researchers with expertise entailing sensors, corresponding to one of eight role types, and conducted semi-structured interviews between February 7-26, 2025. Interviews centered on understanding the needs, preferences, and pain points of environmental health researchers seeking to use sensors for their research projects. We conducted deductive content analysis of interview transcripts, guided by the HITREF framework.
Results:
The participants held primary roles of primary investigator, study coordinator, sensor developer, biomedical informaticist, and study sponsor. Content analysis revealed that participants consider multiple characteristics of sensors when selecting sensors for studies, including cost, physical parameters and limitations of the sensors, reliability, suitable environments for deployment, and software and processes required for data acquisition, transfer, integration, and analysis. User training and interaction are important considerations, often conceptualized as burdens on study participants that research teams seek to minimize. Participants described a desire for adequate support from sensor developers and flexibility in data transfer and analysis.
Conclusions:
Participants in varied roles described many similar themes regarding considerations for sensor selection, deployment, and integration as well as desired features for a sensor metadata repository.
Available here: https://preprints.jmir.org/preprint/91311
Meet our team at these upcoming conferences:
Air Sensors International Conference (ASIC) 2026, May 4-8, 2026, Los Angeles California
AMIA Amplify Informatics Conference, May 18-21, 2026, Denver, CO
International Society of Exposure Science (ISES) 2026, October 4-8, 2026, Vancouver, Canada
Welcome to Web Developer Monika Gunashekar!
We are pleased to welcome Monika Gunashekar, who joined the SMARTER team in October 2025 as a Web Developer - Full Stack. Monika holds a Master’s degree in Computer Engineering from Wright State University. She enjoys turning complex ideas into clear, scalable web applications and works through open-ended problems to create solutions that are both user-friendly and technically sound. Monika is contributing to the development of user interfaces and APIs.
SMARTER Software Engineer Monika Gunashekar.
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The University of Utah SMARTER Project is funded by the National Institutes of Health, National Institute for Environmental Health Sciences (“Community-Driven Sensor Metadata Ecosystem for Exposure Health“, 1R24ES036134-01, Multi-Principal Investigators Ramkiran Gouripeddi & Mollie R. Cummins). The content of this web site is solely the responsibility of the authors and does not necessarily represent the official views of the University of Utah or the National Institutes of Health.
