Smart air-conditioning control by wireless sensors: an online optimization approach

One of the most prominent applications of smart technology for energy saving is in buildings, in particular, for optimizing heating, ventilation, and air-conditioning (HVAC) systems. Traditional HVAC systems rely on wired temperature regulators and thermostats installed at fixed locations, which are both inconvenient for deployment and ineffective to cope with dynamic changes in the thermal behavior of buildings. New generation of wireless sensors are increasingly becoming popular due to their convenience and versatility for sophisticated monitoring and control of smart buildings. However, there also emerge new challenges on how to effectively harness the potential of wireless sensors. First, wireless sensors are energy-constrained, because they are often powered by batteries. Extending the battery lifetime, therefore, is a paramount concern. The second challenge is to ensure that the wireless sensors can work in uncertain environments with minimal human supervision as they can be dynamically displaced in new environments. Therefore, in this paper, we study a fundamental problem of optimizing the trade-off between the battery lifetime and the effectiveness of HVAC remote control in the presence of uncertain (even adversarial) fluctuations in room temperature. We provide an effective offline algorithm for deciding the optimal control decisions of wireless sensors, and a 2-competitive online algorithm that is shown to attain performance close to offline optimal through extensive simulation studies. The implication of this work is to shed light on the fundamental trade-off optimization in wireless sensor controlling HVAC systems.

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