Regional air-conditioning management based on fine-grained environmental information

这项研究旨在通过实时传递细粒度环境信息来优化空调，从而降低一定区域的能耗。为了以低成本收集环境信息，我们研究了各种传感技术，如利用用户的智能手机作为传感器的参与式传感，从社交媒体文本中传感，通过动物可穿戴设备传感。我们还开发了一种参与式感知的隐私保护方案，使用了负面调查和随机响应技术相结合的方法。最后，在分析多个信息源的传感器数据的基础上，开发了一个控制包括空调在内的各种家用电器的家庭自动化系统。总体而言，我们在对传感数据进行分析的基础上，研究了从环境数据采集到空调控制的整个能源管理过程。

This research aims to reduce energy consumption in a certain region by optimizing air-conditioning based on fine-grained environmental information delivered in real-time. In order to collect environmental information at low cost, we studied various sensing techniques such as participatory sensing which utilizes smartphones of users as sensors, sensing from social media texts, sensing by an animal-wearable device. We also developed a privacy-preserving scheme for participatory sensing by using a combination of negative surveys and randomized response techniques. Finally we developed a home automation system that controls various home appliances including air-conditioner based on the analysis of sensor data from multiple information sources. Overall, we studied the whole story of energy management from acquisition of environmental data to the control of air-conditioner based on the analysis of the sensing data.