Predicting household water use behaviour for improved hygiene practices in internet of things environment via dynamic behaviour intervention model. Issue 5 (1st September 2016) - Fu, Yang; Wu, Wenyan
Abstract : Recent advances in Internet of Things (IoT) enabled technologies allow the intelligent sensor systems to effectively and efficiently observe and identify human behaviour in many applications, particularly in energy consumption and healthcare sectors. One typical case is that how to use IoT technologies to understand human water use behaviour for improved and sustained hygiene practice. Traditionally, static behaviour intervention models are widely utilised to simulate behaviour intervention process over time. These static methods can predict targeted human behaviour reasonably well, but lack of capabilities on understanding and responding behaviour change process in IoT environments. In this study, the authors proposed a dynamic behaviour intervention model for predicting household water user behaviour for improved hygiene practices. This model is based on an expanded theory of planned behaviour (ETPB), and adopted structure equation model approach and control engineering concept. A case study of household water consumption model using artificial neural network is utilised to evaluate intervention trend of proposed ETPB dynamic behaviour model with system parameter identification. The ETPB dynamic model has been proved to be effective for modelling human behaviour intervention process.