A data driven method for optimal sensor placement in multi-zone buildings

In this paper, we propose a data-driven methodology to identify the optimal placement of sensors in multi-zone building. The proposed is based on statistical tests that study (in) dependence measurements from various available sensors. advice set most dissimilar be retained, as they would convey maximum information. method starts with an initial setup can provide every building zone carry out study; any these removed eventually decrease costs normal operation. has advantages being purely data driven and computationally efficient, against several methods scientific literature, operate under premise detailed models are available, evaluate number/position required This property makes scale different buildings, expert free manner. help towards better characterization for control monitoring applications. It validated widely used – Kalman filtering Grey-box models, using two case studies. both cases, approach agrees results grey box suggesting reliable, while quick efficient.