@article{bibcite_1136,
  author = {Ahmad Gholizadeh_Lonbar and Kaiwen Chen and Yunping Liang and Sophia Arthur},
  title = {Digital Twin Adoption in Weatherization Assistance Programs: Compliance Requirements, Liability Concerns, and Stakeholder Needs},
  abstract = {As climate-induced extreme weather events intensify, aging homes in low-income and rural communities face mounting energy burdens and vulnerabilities. Emerging Digital Twin technologies, combined with Unmanned Aerial Vehicles, Infrared Thermography, Computer Vision, and Artificial Intelligence, offer promise for efficient building energy auditing {\textendash} an essential step for government programs to release funds. However, the adoption of such technologies by certified auditors remains limited due to systemic barriers. To address the gap, this research starts with a systematic literature review to identify key factors influencing the implementation of these advanced technologies, considering both technical and managerial constraints. Afterwards, a framework derived from the literature was used to support focus groups and surveys with statewide weatherization audit agencies to capture local perceptions, concerns, and needs. The descriptive results suggest that, despite engineers focusing on pushing the technological boundaries, potential end users tend to prioritize managerial aspects such as cost, training, ease of use, addressing outstanding needs, compliance, and data security. The results also illustrate the silhouette of future weatherization audit scenarios, outlining core required features. The findings inform the participatory design of a Digital Twin platform intended to democratize access to energy auditing and enable data-driven retrofit decisions within publicly administered weatherization assistance programs.},
  year = {2026},
  journal = {Journal of legal affairs and dispute resolution in engineering and construction},
  month = {06},
  publisher = {Journal of Legal Affairs and Dispute Resolution in Engineering and Construction},
  issn = {1943-4170},
  url = {https://par.nsf.gov/biblio/10682495},
}