# An Overview of Indoor Localization System for Human Activity Recognition (HAR) in Healthcare
## 2 Ips  
The principle of operation of an indoor positioning system (IPS) uses reference sensor nodes with known positions that send a ranging signal to the mobile device attached to the target. Then, the mobile device perceives the request signals and issues a ranging reply to the reference sensor. At this point, the traveling time of the ranging signal between the transmitter sensor node and the moving target can be calculated. The measured data are transferred to a data center using positioning algorithms, and we can determine the target's exact position. Therefore, for the localization of unknown nodes, we must first measure some metrics and then use the algorithm to calculate the position itself, as shown in Figure 3 [16].  
Figure 1: Indoor positioning systems.  
Figure 2: Diagram of relationships between the sections.  
In the first phase of the process, between fixed and mobile nodes, all the characteristic information of the signals is exchanged, such as direction, length, time of arrival, and coordinates of the referent node. In the second phase, however, the obtained parameters are transferred to the calculation algorithm to determine the exact position of the moving object.  
Positioning systems can be distinguished according to the principle applied, such as proximity, range, and scene analysis.  
**Proximity** uses the maximum received signal strength of an anchor node to calculate the location of the moving node. The near-field communication (NFC) technique is commonly used. We can easily implement the system; however, the accuracy is of a low level.  
**The range** is based on measuring the distance of the communication signals. The location of the target node is determined either according to the direction or distance. For example, the angle of arrival (AoA) is usually applied for the first one. The time parameter (ToA or TDoA) or signal properties (RSSI) can be used for the second.  
**Scene analysis** is a pattern recognition class of methods that uses the characteristics of a scene from a particular viewpoint to match patterns. The currently measured wireless characteristics are compared to prestored characteristics for each pattern to determine a match. We use the best match as the current location of the mobile node. The commonly used method is fingerprinting [14]. The system's accuracy is excellent but burdensome, as it takes a long time to collect the characteristics needed for each pattern and requires substantial storage space. Moreover, changes to the environment may require the characteristics to be re-evaluated. In recent years, numerous indoor positioning technologies have been developed [17], which differ in the type of hardware used and the localization algorithm. Each has been developed for a specific need and has attributes that make it preferable in certain respects and characteristics or limited by its very nature if used for an application other than that assumed. To understand which of these technologies is the most suitable to apply in a specific context, it is necessary to create metrics against which to evaluate each technology.