Transforming urban energy systems with scalable non-invasive building thermal sensing

The urgent need for sustainable buildings has accelerated the development of non-invasive sensing methods to assess thermal parameters, such as thermal transmittance, temperature, and humidity. Unlike intrusive traditional approaches that lack scalability, non-invasive techniques, including infrared thermography and ground-penetrating radar, offer contactless diagnostics. However, their transition into robust sensing systems is hindered by environmental sensitivity, a lack of standardization, and limited capacity to capture large-scale indoor-outdoor interactions. This review systematically analyzes these barriers and presents emerging integrated solutions. Key advancements include unmanned aerial vehicle multimodal sensing that enables high-throughput data collection and physics-informed learning frameworks that enhance measurement accuracy and model interoperability. These approaches can transform these techniques from isolated diagnostic tools into scalable urban-level intelligence systems. This transformation fundamentally strengthens building energy modeling at the city scale, providing critical data support for decarbonization pathways and climate-resilient urban planning.