Design of a Cost-Effective Multimodal IoT Edge Device for Building Occupancy Estimation

Depending on the architectural typology and function of a specific building or compartment, Building Occupancy Estimation (BOE) is a critical factor for effective green building management. By estimating the building occupancy over time we can reduce the overall energy consumption, and therefore, improve the building energy efficiency. In a public building context, for example, such as an administration office, a school or a kindergarten, building occupancy is normally restricted to a regular work schedule and its effective occupation can considerably vary in this period, in terms of number of occupants per compartment or in the overall building, and therefore considerable impact the building energy consumption for heating, HVAC, lightning, etc. Occupancy estimation over time can be used to compute several metrics that are highly relevant for effective building management, e.g. users per room during work schedule, users per building overnight, etc. Towards that, in this work we introduce the design and implementation of a cost-effective IoT edge device for BOE. The proposed device, collects and transmits up to the cloud, several networking and indoor environmental parameters, that combined, will be later used to specify a multi-parameter metric for effective BOE.

I. Introduction

Green Building Management can be seen as the orchestration of state-of-the-art technologies, such as the Internet of Things (IoT) and cloud computing with the green building energy efficiency standards [1]. On the other hand, in [2], Buckman Et. al. define a Smart Building as the harmonious integration of intelligent systems, control mechanisms, architecture and construction materials to operate as an entire building system, with adaptability at its core to enable continuous building improvement in terms of energy efficiency, longevity, comfort, and satisfaction. Furthermore, Green Building Management can be seen as hierarchically under the Smart Building scope. Both concepts share some core features by focusing on the harmonious integration of technology in the building, not forgetting two important resources, i.e. people and the physical environment, to achieve green building energy efficiency standards [1]. Moreover, context-aware building control can be directly driven by estimating building occupancy information [3], such as presence detection, people counting, etc.