Related data for: Heterogeneous Transfer Learning for Thermal Comfort Modeling

These datasets are collected for the GBIC project to conduct research about indoor human thermal comfort. The GBIC research project proposes to develop online thermal comfort models via a deep-learning approach and apply them to behavioral studies to drive “greener, smarter and healthier buildings” in the tropics (e.g., Singapore). Leveraging privacy-preserving data analytics over information acquired from smartphone crowdsourcing and in-situ wearables measurements, the project plans to develop and validate an integrative, economical and scalable thermal comfort management system. NTU-SCSE News about GBIC Project本数据集为GBIC项目采集所得，用于开展室内人体热舒适相关研究。GBIC研究项目旨在通过深度学习方法开发在线热舒适模型，并将其应用于行为学研究，以推动热带地区（例如新加坡）打造“更绿色、更智能、更健康的建筑”。本项目依托智能手机众包采集与现场可穿戴设备测量获取的信息，开展隐私保护型数据分析，计划开发并验证一套集成化、经济高效且可扩展的热舒适管理系统。南洋理工大学计算机科学与工程学院（NTU-SCSE）关于GBIC项目的相关新闻资讯。