Community-Based AI Energy Audit System and Service
2026
Human-Centred AI Award
Winner
Industrial Technology Research Institute
Designers / Creators / Authors / Leaders
Ju-Min Liao, Yu-Chen Lin and Hsiao-Yun Huang
“Community-Based AI Energy Audit System and Service” transforms traditional energy audits into an automated, digitalized, and trackable service model. It adopts a dual-track strategy of AI tool-use training and user-led explanation and support, using visualized charts and easy-to-understand explanations to help older adults better understand household energy issues.
Responding to the challenges facing aging communities—limited understanding of household energy use, barriers to adopting digital tools, and concerns for electricity safety—the service integrates empowerment and guidance into a human-centered model. Trained users conduct on-site audits via mobile devices, while AI processes the data and generates visualized reports.
Scalable from communities to cities, the service supports residential energy governance by enabling data accumulation, energy-use profiling, and proactive identification of needs, hereby fostering a more resilient and safer living environment.
Bringing AI community energy audits into everyday life, this service transforms complex energy data into a catalyst for energy-saving behavior change. It establishes a standardized, replicable digital audit process by replacing paper-based operations with modular forms, ensuring consistent quality and accessibility across diverse user groups. By integrating generative AI, decision-making models, a cloud database, and feedback mechanisms, it streamlines data collection, analysis, and application, slashing audit time from three working days to under 10 minutes.
Beyond efficiency, the service creates shared human-centered benefits for users, residents, and communities by helping residents identify energy-use and safety issues, reducing users’ administrative burden, and enabling communities to strengthen energy management through accumulated data. Collectively, these benefits support a sustainable and scalable service model for community.
In response to population aging, this service model addresses the digital divide and develops its core framework accordingly.
For AI tool users, it provides multi-stage training in energy-saving knowledge, electricity safety, diagnostic and digital tool use, as well as hands-on practice in conducting home energy audits and explaining report findings to residents.
For older adults, reports are presented in a visualized format, covering household electricity-use patterns, environmental illuminance, appliance energy efficiency, and recommendations for immediate or longer-term actions. Clear and easy-to-understand explanations from trained users help lower comprehension barriers.
The development team also strictly adheres to personal data protection regulations and ensuring residents’ privacy while continuously optimizing the AI tool and service model based on user feedback.
