Towards an Intelligent Approach for Ventilation Systems Control using IoT and Big Data Technologies

Heating, ventilation and air conditioning systems are generally deployed in buildings for maintaining occupants’ comfort. They are the most considered systems in improving the energy saving while sustaining occupants’ comfort. Several approaches have been proposed, in the past few years, to develop an optimal control for ventilation systems. However, these approaches could not be efficiently performed under diverse contexts. In fact, we introduce an intelligent approach that selects the most appropriate control among three existing strategies. This paves the way to approaches in which an antifragile platform learns and adapts which strategy to enact. The proposed approach is implemented using IoT devices and recent Big-data technologies for real-time monitoring and data processing. A case study was deployed in our EEBLab test site for real testing. Experiments have been conducted and preliminary results show the effectiveness of using adaptive control approaches for ventilation systems control.