{"slug": "from-thermal-preference-prediction-to-adaptive-thermal-intervention-a-learning", "title": "From Thermal Preference Prediction to Adaptive Thermal Intervention: A Reinforcement Learning Approach Using Physiological and Environmental Sensing", "summary": "Researchers from Nottingham Trent University, led by Isibor Kennedy Ihianle, proposed a two-stage personalized thermal comfort approach that integrates multimodal physiological and environmental sensing with reinforcement learning-based decision-making, submitted to arXiv on 19 Aug 2026. The method aims to replace static HVAC setpoints and population-level comfort models with adaptive thermal interventions tailored to individual physiological variability, potentially improving occupant wellbeing and building-control responsiveness.", "body_md": "# Computer Science > Machine Learning\n\n[Submitted on 19 Aug 2026]\n\n# Title:From Thermal Preference Prediction to Adaptive Thermal Intervention: A Reinforcement Learning Approach Using Physiological and Environmental Sensing\n\n[View PDF](/pdf/2608.20423)\n\n[HTML (experimental)](https://arxiv.org/html/2608.20423v1)\n\nAbstract:Personalised thermal comfort is essential for occupant wellbeing and for the development of more responsive building-control strategies, yet conventional Heating, Ventilation, and Air Conditioning (HVAC) systems rely on static setpoints and population-level comfort models that fail to capture individual physiological variability. This paper presents a two-stage personalised thermal comfort approach integrating multimodal physiological and environmental sensing with reinforcement learning-based decision-making.\n\n## Submission history\n\nFrom: Isibor Kennedy Ihianle [[view email](/show-email/8e7b6e66/2608.20423)]\n\n**[v1]** Wed, 19 Aug 2026 09:39:15 UTC (2,437 KB)\n\n### References & Citations\n\nLoading...\n\n# Bibliographic and Citation Tools\n\nBibliographic Explorer\n\n*(*[What is the Explorer?](https://info.arxiv.org/labs/showcase.html#arxiv-bibliographic-explorer))\nConnected Papers\n\n*(*[What is Connected Papers?](https://www.connectedpapers.com/about))\nLitmaps\n\n*(*[What is Litmaps?](https://www.litmaps.co/))\nscite Smart Citations\n\n*(*[What are Smart Citations?](https://www.scite.ai/))# Code, Data and Media Associated with this Article\n\nalphaXiv\n\n*(*[What is alphaXiv?](https://alphaxiv.org/))\nCatalyzeX Code Finder for Papers\n\n*(*[What is CatalyzeX?](https://www.catalyzex.com))\nDagsHub\n\n*(*[What is DagsHub?](https://dagshub.com/))\nGotit.pub\n\n*(*[What is GotitPub?](http://gotit.pub/faq))\nHugging Face\n\n*(*[What is Huggingface?](https://huggingface.co/huggingface))\nScienceCast\n\n*(*[What is ScienceCast?](https://sciencecast.org/welcome))# Demos\n\n# Recommenders and Search Tools\n\nInfluence Flower\n\n*(*[What are Influence Flowers?](https://influencemap.cmlab.dev/))\nCORE Recommender\n\n*(*[What is CORE?](https://core.ac.uk/services/recommender))\nIArxiv Recommender\n\n*(*[What is IArxiv?](https://iarxiv.org/about))# arXivLabs: experimental projects with community collaborators\n\narXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.\n\nBoth individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.\n\nHave an idea for a project that will add value for arXiv's community? [ Learn more about arXivLabs](https://info.arxiv.org/labs/index.html).", "url": "https://wpnews.pro/news/from-thermal-preference-prediction-to-adaptive-thermal-intervention-a-learning", "canonical_source": "https://arxiv.org/abs/2608.20423", "published_at": "2026-08-24 04:00:00+00:00", "updated_at": "2026-08-24 04:15:04.148981+00:00", "lang": "en", "topics": ["machine-learning", "artificial-intelligence"], "entities": ["Nottingham Trent University", "Isibor Kennedy Ihianle", "arXiv"], "alternates": {"html": "https://wpnews.pro/news/from-thermal-preference-prediction-to-adaptive-thermal-intervention-a-learning", "markdown": "https://wpnews.pro/news/from-thermal-preference-prediction-to-adaptive-thermal-intervention-a-learning.md", "text": "https://wpnews.pro/news/from-thermal-preference-prediction-to-adaptive-thermal-intervention-a-learning.txt", "jsonld": "https://wpnews.pro/news/from-thermal-preference-prediction-to-adaptive-thermal-intervention-a-learning.jsonld"}}