Background The proliferation of mobile health (mHealth) applications is partly driven by the advancements in sensing and communication technologies, as well as the integration of artificial intelligence techniques. Data collected from mHealth applications, for example, on sensor devices carried by patients, can be mined and analyzed using artificial intelligence–based solutions to facilitate remote and (near) real-time decision-making in health care settings. However, such data often sit in data silos, and patients are often concerned about the privacy implications of sharing their raw data. Federated learning (FL) is a potential solution, as it allows multiple data owners to collaboratively train a machine learning model without requiring access to each other’s raw data. Objective The goal of this scoping review is to gain an understanding of FL and its potential in dealing with sensitive and heterogeneous data in mHealth applications. Through this review, various stakeholders, such as health care providers, practitioners, and policy makers, can gain insight into the limitations and challenges associated with using FL in mHealth and make informed decisions when considering implementing FL-based solutions. Methods We conducted a scoping review following the guidelines of PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews). We searched 7 commonly used databases. The included studies were analyzed and summarized to identify the possible real-world applications and associated challenges of using FL in mHealth settings. Results A total of 1095 articles were retrieved during the database search, and 26 articles that met the inclusion criteria were included in the review. The analysis of these articles revealed 2 main application areas for FL in mHealth, that is, remote monitoring and diagnostic and treatment support. More specifically, FL was found to be commonly used for monitoring self-care ability, health status, and disease progression, as well as in diagnosis and treatment support of diseases. The review also identified several challenges (eg, expensive communication, statistical heterogeneity, and system heterogeneity) and potential solutions (eg, compression schemes, model personalization, and active sampling). Conclusions This scoping review has highlighted the potential of FL as a privacy-preserving approach in mHealth applications and identified the technical limitations associated with its use. The challenges and opportunities outlined in this review can inform the research agenda for future studies in this field, to overcome these limitations and further advance the use of FL in mHealth.
more »
« less
This content will become publicly available on June 1, 2024
Decision-Making Approach to Urban Energy Retrofit—A Comprehensive Review
This research presents a comprehensive review of the research on smart urban energy retrofit decision-making. Based on the analysis of 91 journal articles over the past decade, the study identifies and discusses five key categories of approaches to retrofit decision-making, including simulation, optimization, assessment, system integration, and empirical study. While substantial advancements have been made in this field, opportunities for further growth remain. Findings suggest directions for future research and underscore the importance of interdisciplinary collaboration, data-driven evaluation methodologies, stakeholder engagement, system integration, and robust and adaptable retrofit solutions in the field of urban energy retrofitting. This review provides valuable insights for researchers, policymakers, and practitioners interested in advancing the state of the art in this critical area of research to facilitate more effective, sustainable, and efficient solutions for urban energy retrofits.
more »
« less
- Award ID(s):
- 2046374
- NSF-PAR ID:
- 10417443
- Date Published:
- Journal Name:
- Buildings
- Volume:
- 13
- Issue:
- 6
- ISSN:
- 2075-5309
- Page Range / eLocation ID:
- 1425
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
This paper describes the temporal progression of human and social dimensions that undergraduate information and communications technology (ICT) students realized during an experiential learning externship where they explored digital divide technology solutions for low-income neighborhoods in the surrounding urban community. The described research represents significant adaptation and use of socio-technical integration research (STIR) with undergraduate ICT students engaged in work based experiential learning to promote equity in STEM education, instill a sense of civic responsibility, and practice approaches to tackling complex societal problems. Methods used for the research study included: STIR, semi-structured interviews, and on-site group observations. Using STIR, an embedded social scientist conducted regular one-on-one dialogs with three of four student externs, to collaboratively describe each student’s consideration of human and social dimensions as part of their technical work, explore alternative choices and their potential outcomes, and engage in reflexive learning that in some cases, influenced deliberate changes to material and behavioral practices. The on-site observation of group activities within the ICT innovation center situated in the local urban community provided additional ecosystem context during technical solution design and development of the digital divide solution for local high schools and feeder schools. Outcomes for participating undergraduate ICT students showed: 1) Technology learning improvements for all students; 2) Capacity building to reflect, anticipate and respond to socio-technical interactions for some students; and 3) Each student was able to progress to a new level of socio-technical learning and decision making. Reflexive discourse with participants surfaced cultural assets and consideration of alternative knowledges in collaborative technology design, development, and implementation that can potentially lead to solutions that are more community centered now and in the future as the ICT students transition to the workforce.more » « less
-
This paper describes the temporal progression of human and social dimensions that undergraduate information and communications technology (ICT) students realized during an experiential learning externship where they explored digital divide technology solutions for low-income neighborhoods in the surrounding urban community. The described research represents significant adaptation and use of socio-technical integration research (STIR) with undergraduate ICT students engaged in work based experiential learning to promote equity in STEM education, instill a sense of civic responsibility, and practice approaches to tackling complex societal problems. Methods used for the research study included: STIR, semi-structured interviews, and on-site group observations. Using STIR, an embedded social scientist conducted regular one-on-one dialogs with three of four student externs, to collaboratively describe each student’s consideration of human and social dimensions as part of their technical work, explore alternative choices and their potential outcomes, and engage in reflexive learning that in some cases, influenced deliberate changes to material and behavioral practices. The on-site observation of group activities within the ICT innovation center situated in the local urban community provided additional ecosystem context during technical solution design and development of the digital divide solution for local high schools and feeder schools. Outcomes for participating undergraduate ICT students showed: 1) Technology learning improvements for all students; 2) Capacity building to reflect, anticipate and respond to socio-technical interactions for some students; and 3) Each student was able to progress to a new level of socio-technical learning and decision making. Reflexive discourse with participants surfaced cultural assets and consideration of alternative knowledges in collaborative technology design, development, and implementation that can potentially lead to solutions that are more community centered now and in the future as the ICT students transition to the workforce.more » « less
-
null (Ed.)Since its commissioning in 2004, the UC San Diego Large High-Performance Outdoor Shake Table (LHPOST) has enabled the seismic testing of large structural, geostructural and soil-foundation-structural systems, with its ability to accurately reproduce far- and near-field ground motions. Thirty-four (34) landmark projects were conducted on the LHPOST as a national shared-use equipment facility part of the National Science Foundation (NSF) Network for Earthquake Engineering Simulation (NEES) and currently Natural Hazards Engineering Research Infrastructure (NHERI) programs, and an ISO/IEC Standard 17025:2005 accredited facility. The tallest structures ever tested on a shake table were conducted on the LHPOST, free from height restrictions. Experiments using the LHPOST generate essential knowledge that has greatly advanced seismic design practice and response predictive capabilities for structural, geostructural, and non-structural systems, leading to improved earthquake safety in the community overall. Indeed, the ability to test full-size structures has made it possible to physically validate the seismic performance of various systems that previously could only be studied at reduced scale or with computer models. However, the LHPOST's limitation of 1-DOF (uni-directional) input motion prevented the investigation of important aspects of the seismic response of 3-D structural systems. The LHPOST was originally conceived as a six degrees-of-freedom (6-DOF) shake table but built as a single degree-of-freedom (1-DOF) system due to budget limitations. The LHPOST is currently being upgraded to 6-DOF capabilities. The 6-DOF upgraded LHPOST (LHPOST6) will create a unique, large-scale, high-performance, experimental research facility that will enable research for the advancement of the science, technology, and practice in earthquake engineering. Testing of infrastructure at large scale under realistic multi-DOF seismic excitation is essential to fully understand the seismic response behavior of civil infrastructure systems. The upgraded 6-DOF capabilities will enable the development, calibration, and validation of predictive high-fidelity mathematical/computational models, and verifying effective methods for earthquake disaster mitigation and prevention. Research conducted using the LHPOST6 will improve design codes and construction standards and develop accurate decision-making tools necessary to build and maintain sustainable and disaster-resilient communities. Moreover, it will support the advancement of new and innovative materials, manufacturing methods, detailing, earthquake protective systems, seismic retrofit methods, and construction methods. This paper will provide a brief overview of the 1-DOF LHPOST and the impact of some past landmark projects. It will also describe the upgrade to 6-DOF and the new seismic research and testing that the LHPOST6 facility will enable.more » « less
-
Over the past several decades, urban planning has considered a variety of advanced analysis methods with greater and lesser degrees of adoption. Geographic Information Systems (GIS) is probably the most notable, with others such as database management systems (DBMS), decision support systems (DSS), planning support systems (PSS), and expert systems (ES), having mixed levels of recognition and acceptance (Kontokosta, C. E. (2021). Urban informatics in the science and practice of planning. Journal of Planning Education and Research, 41(4), 382–395. doi:10.1177/0739456X18793716; Yigitcanlar, T., Desouza, K. C., Butler, L., & Roozkhosh, F. (2020). Contributions and risks of artificial intelligence (AI) in building smarter cities: Insights from a systematic review of the literature. Energies, 13(6), 1473). Advances in information technologies have moved very slowly in the field of urban planning, more recently concerning ‘smart city’ technologies while revolutionizing other domains, such as consumer goods and services. Baidu, Amazon, Netflix, Google, and many others are using these technologies to gain insights into consumer behaviour and characteristics and improve supply chains and logistics. This is an opportune time for urban planners to consider the application of AI-related techniques given vast increases in data availability, increased processing speeds, and increased popularity and development of planning related applications. Research on these topics by urban planning scholars has increased over the past few years, but there is little evidence to suggest that the results are making it into the hands of professional planners (Batty, M. (2018). Artificial intelligence and smart cities. Environment and Planning B: Urban Analytics and City Science, 45(1), 3–6; Batty, M. (2021). Planning education in the digital age. Environment and Planning B: Urban Analytics and City Science, 48(2), 207–211). Others encourage planners to leverage the ubiquity of data and advances in computing to enhance redistributive justice in information resources and procedural justice in decision-making among marginalized communities (Boeing, G., Besbris, M., Schachter, A., & Kuk, J. (2020). Housing search in the Age of Big data: Smarter cities or the same Old blind spots? Housing Policy Debate, 31(1), 112–126; Goodspeed, R. (2015). Smart cities: Moving beyond urban cybernetics to tackle wicked problems. Cambridge journal of regions, Economy and Society, 8(1), 79–92). This article highlights findings from a recent literature review on AI in planning and discusses the results of a national survey of urban planners about their perspectives on AI adoption and concerns they have expressed about its broader use in the profession. Currently, the outlook is mixed, matching how urban planners initially viewed the early stages of computer adoption within the profession. And yet today, personal computers are essential to any job.more » « less
