Archinect - News2024-11-21T13:42:38-05:00https://archinect.com/news/article/150411113/a-cambridge-university-research-paper-explores-the-challenges-faced-by-architectural-design-practitioners-in-embracing-inclusive-design
A Cambridge University research paper explores the challenges faced by architectural design practitioners in embracing inclusive design Josh Niland2024-01-05T12:15:00-05:00>2024-10-25T04:07:38-04:00
<img src="https://archinect.gumlet.io/uploads/08/08c9a774f41cc45d204912e99f9aae2a.jpeg?fit=crop&auto=compress%2Cformat&enlarge=true&w=1200" border="0" /><p>New research produced by the <a href="https://archinect.com/cambridge" target="_blank">University of Cambridge</a> has identified key strategies to better effect a widespread implementation of <a href="https://archinect.com/news/tag/729627/inclusive-design" target="_blank">inclusive design</a> beyond its current status as a nascent set of concepts that have yet to be fully adopted by practitioners in almost every sector.</p>
<p>The paper’s lead investigators, Dr. Matteo Zallio and Professor P John Clarkson, surveyed a total of 114 different practitioners of architecture to produce an assessment of the current perceptions and challenges inherent in designing for inclusivity. The results are a reminder of how far the industry still has to go in terms of raising awareness and dispelling misconceptions about inclusive design by identifying critical gaps in client and practitioner awareness.</p>
<p>For example, the paper states “only 41.6% of clients were reported to have requested guidance on regulatory and legal compliance in the pre-design process.” A post-design evaluation of occupants' usability using available tools is another key lagging ...</p>
https://archinect.com/news/article/150393820/cambridge-researchers-develop-ai-model-to-help-retrofit-and-decarbonize-housing
Cambridge researchers develop AI model to help retrofit and decarbonize housing Niall Patrick Walsh2023-11-02T11:45:00-04:00>2024-10-25T04:07:38-04:00
<img src="https://archinect.gumlet.io/uploads/ce/cea9753c83077fff30b49eb9aee73643.jpg?fit=crop&auto=compress%2Cformat&enlarge=true&w=1200" border="0" /><p>Researchers from the <a href="https://archinect.com/cambridge" target="_blank">University of Cambridge</a> have unveiled a “first-of-its-kind AI model” that can help policymakers identify and prioritize houses for <a href="https://archinect.com/news/tag/212775/retrofitting" target="_blank">retrofitting</a> and other decarbonizing measures. The deep learning model, <a href="https://www.cam.ac.uk/research/news/ai-trained-to-identify-least-green-homes-by-cambridge-researchers" target="_blank">trained by researchers</a> from the university’s Department of Architecture, promises “to make it far easier, faster, and cheaper to identify these high-priority problem properties and develop strategies to improve their green credentials,” the team says.</p>
<p>The model and wider research centers on ‘hard-to-decarbonize’ (HtD) houses that, while responsible for a quarter of all direct housing emissions, are rarely identified or targeted for improvement. According to the team, the age, structure, location, availability of data, and socioeconomic context can all lead to a house being classified as HtD.</p>
<p>In response, a team including urban researcher and data scientist Maoran Sun and the university’s Sustainable Design group lead, Dr. Ronita Bardhan, has developed their <a href="https://archinect.com/news/article/150348101/introducing-the-archinect-in-depth-artificial-intelligence-series" target="_blank">AI</a> mo...</p>