Iot Technologies and Deep Learning to Support the Smart Building Development: Review, Opportunities, and Challenges

Abstract

The Internet of Things (IoT) and artificial intelligence offer everyone new types of services to improve daily life in our buildings. The integration of these two technologies allows for the improvement of old services and the innovation of new systems.  Smart buildings rely on the use of smart sensors and IoT systems to retrieve many data (temperature, humidity, presence or not of people in a given space...). This data must be analyzed to obtain valuable information that contributes to improving the quality of life of users. Deep Learning (DL), a subfield of artificial intelligence (AI), based on mathematical approaches, recently demonstrated its ability to model data and increase the efficiency and performance of IoT big data analysis. In this paper, we present a literature review of smart building development using IoT and DL. We start with define the IoT and liste the characteristics of big data from IoT. We then introduce the key computing technologies needed to analyzeIoT big data, including cloud, and edge computing. We then examine common DL models and review recent studies that leverage both IoT and DL to develop smart solutions and tools for smart buildings. Finally, we describe current issues and problems encountered when deploying services for smart buildings.