Abstract
Smart buildings use Internet of Things (IoT) sensors for monitoring indoor environmental parameters, such as temperature, humidity, luminosity, and air quality. Due to the huge amount of data generated by these sensors, data analytics and machine learning techniques are needed to extract useful and interesting insights, which provide the input for the building optimization in terms of energy-saving, occupants’ health and comfort. In this paper, we propose an IoT-based smart building (SB) solution for indoor environment management, which aims to provide the following main functionalities: monitoring of the room environmental parameters; detection of the number of occupants in the room; a cloud platform where virtual entities collect the data acquired by the sensors and virtual super entities perform data analysis tasks using machine learning algorithms; a control dashboard for the management and control of the building. With our prototype, we collected data for 10 days, and we built two prediction models: a classification model that predicts the number of occupants based on the monitored environmental parameters (average accuracy of 99.5%), and a regression model that predicts the total volatile organic compound (TVOC) values based on the environmental parameters and the number of occupants (Pearson correlation coefficient of 0.939).
Highlights
It is a matter of fact that around 40% of the energy use worldwide is consumed by buildings to provide building occupants with healthy and comfortable indoor environments to live and work in, as they spend more than 90% of their time indoors [1]
A Raspberry Pi 3 Model B was equipped with the camera (Logitech C920 HD Pro), the obstacle sensor and the considered indoor environmental sensors, namely, temperature and humidity (DHT11), luminosity (VEML7700), eCO2 and total volatile organic compound (TVOC) (CCS811)
We have presented our Internet of Things (IoT)-based smart building (SB) solution for indoor environment management, which we have implemented by considering all levels of the IoT infrastructure, from the hardware devices to the cloud platform, passing for the middleware
Summary
It is a matter of fact that around 40% of the energy use worldwide is consumed by buildings to provide building occupants with healthy and comfortable indoor environments to live and work in, as they spend more than 90% of their time indoors [1] For this reason, in recent years, there has been a significant increase in the development of smart building (SB) control systems, which aim to connect the monitored environment variables (e.g., temperature, humidity, luminosity, and air quality) with building management systems (e.g., heating, ventilation, and air-conditioning (HVAC) system, lighting system) to optimize the indoor environmental state of the building [2,3].
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