# An Overview of Indoor Localization System for Human Activity Recognition (HAR) in Healthcare
## 1 Introduction
For indoor positioning, the following issues must be taken into account in order to obtain precise results:  
* The presence of obstacles weakens the signal (fast fading);
* The presence of obstacles creates the problem of signals not being in a direct line (not line of sight (NLOS));
* The structure and nature of the construction materials of the indoor environment may create the problem of reflection and refraction (multipathing), making it difficult to determine the correct origin of the signal;
* The climatic changes in the signal's means of transport affect the propagation speed. These conditions affect the propagation of electromagnetic waves; therefore, positioning techniques must consider this to improve indoor position performance. For the outdoor environment, the most widely used system is the GPS (Global Positioning System) [5], a satellite-based global geolocation system. In addition to the GPS, there are other satellite navigation systems such as GLONASS (Global Orbiting Navigation Satellite System) developed in the Soviet Union [6], BDS (Bei Dou Navigation Satellite System) developed in China [7], and Galileo, developed in Europe [8]. GPS satellites emit radio signals from which information is obtained relating to the distance between the satellite and a receiver on Earth and the time it takes for the signal to reach it. From a structural point of view, the GPS consists of the following components:  
* The space segment consists of a constellation of satellites. * The control segment comprises ground stations with the task of synchronizing the clocks of all the satellites, knowing their position, and possibly correcting them. * The user segment comprises an antenna capable of acquiring signals and a receiver capable of decoding and processing them. However, GPS is an excellent system for obtaining the position of a receiver with good precision, and it can be used mainly in an external environment. Indoor, however, the accuracy drops dramatically due to the inability to penetrate most building materials. Currently, much of human life takes place inside buildings, and it is increasingly necessary to know the location of a mobile device. Inside buildings, due to the lack of line of sight, the loss of the signal, the multiple errors due to multipathing that are created, and the problem of inconsistent time delays, it is not possible to rely on the satellite system. This limitation hinders the implementation of GPS in indoor localization systems, although it can be solved using \"high-sensitivity GPS receivers or GPS pseudoliths\" [9]. Pseudoliths (contraction of \"pseudo-satellites\") are RF transmitters that emit signals similar to GNSS, allowing a more accurate localization closer to the receivers than traditional GPS transmitters installed on board satellites. Transmissions reach places where GPS struggles typically, such as deep urban canyons, forests, and valleys. Pseudoliths can be placed where they can increase or replace GPS signals from satellites However, the cost of implementation can be an obstacle to this system's application. Therefore, other technologies should obtain real-time information on humans and objects in indoor areas [10]. In the literature, there are different experiences on indoor localization [11]. There are different technologies capable of localizing objects or people indoors in an accurate manner, but this is achieved by using specialized and rather expensive hardware and sensors that must though be placed in advance within a confined space; such systems also reach sub-millimeter accuracies but to the detriment of usability, cost, and scalability. Compared with outdoor localization, indoor localization is more complex because the indoor communication channel varies significantly with the environment and depends heavily on many factors, such as building structure, room layout, and construction materials. Positioning systems can use 2D [12] or 3D [13] models. The latter has a higher positioning accuracy but requires higher costs due to the hardware infrastructure.