Identification and Classification of Indoor and Outdoor Environments: A review

Abstract

The efficient method to conserve energy and minimize power consumption is to identify the surrounding environment and to classify the environment as indoor and outdoor. Based on the type of environment, tracking of people and devices becomes easy. This identification and classification can be achieved in many ways.  There have been different solutions proposed for this purpose. The most common ones were by using sensors. The GPS sensors are widely used to identify the environment. These work well in the outdoor area. When it comes to indoor, it is difficult to collect data from these sensors due to the absence of an unobstructed line of sight. Classification of indoor environment is very essential to identify different environments in such cases. This paper gives a review of different methods that have been proposed to differentiate outdoor from indoor environments and also ways to classify indoor environments for IoT applications using different techniques like Machine learning, Deep learning, etc.

Keywords: Indoor and Outdoor Environment, IoT sensors, Machine Learning, Deep Learning, RF Signatures.