# Implementing an Industry 4.0 UWB-Based Real-Time Locating System for Optimized Tracking
## 2 Literature Review
### Related Works  
The main direction of RTLS-related research concerns the development of more accurate systems based on existing technologies. Thus, few studies compare the RTLS implementations of different technologies [11; 12]. Other studies have contributed to the improvement of: (i) the Wi-Fi method, using different strategies [13; 14; 15]; (ii) the object localization accuracy on multifloored structures [16]; and (iii) distance measurements, using neural networks to predict positions more accurately [17]. On the other hand, some studies introduce the UWB signal technology for real-time tracking in different environments and analyzed the system's performance [18; 19; 20]. Moreover, others proposed a positioning estimation technique based on particle filtering, which is applied to distance measurements in order to improve the overall system's performance [21]. In other cases, researchers proposed combining technologies based on UWB and IMU, as the integrated application could locate assets with better accuracy when IMU and UWB were cooperatively used. For example, in a recent study, positioning accuracy was improved using a Variable Noise Variance (VNV) Kalman filter that fuses data from the UWB, IMU, and magnetometer sensors [22]. As the system cost was high, a low-cost and high-accuracy Wi-Fi solution was also proposed using an Unscented Kalman filter (UKF) to improve the tracking accuracy of the  
Figure 1: Research methodology. Figure 2: Article categorization based on tracking technology after 2017. Wi-Fi [23]. Moreover, RTLS implementations have been proposed for safety and body posture monitoring purposes in indoor environments. In this regard, some researchers tried to use UWB technology to develop a system for underground positioning and collision avoidance [24]. Furthermore, a system based on IR-UWB for human localization and the tracking of human body limb movements in 3D for healthcare applications was proposed, with a system error lower than 3 cm for 90% of the measurements [25]. In more recent research, an RTLS based on UWB technology was used to track lambs and their movement in an indoor barn [26]. The above literature review highlights the increased research interest in RTLSs and, specifically, in the use of UWB technology for tracking purposes. A technology that is widely used for RTLS is RFID; this emerging technology enables the mobility tracking of objects and humans. There are three main types of RFID systems: (i) passive [27]; (ii) semi-passive; and (iii) active systems. A typical RFID system contains tags (also referred to as transponders, smart tags, smart labels, or radio barcodes), a reader (also called a writer, decoder, interrogator, transmitter, receiver, or transceiver), and a host computer. A comparative analysis between low-frequency RFID (LF-RFID), ultra-high-frequency RFID (UHF-RFID) and UWB IPSs showed that the UWB system was more accurate than the RFID systems, with a mean error of 0.58 m compared to 1.53 m and 3.78 m for the LF-RFID and UHF-RFID systems, respectively [28]. For an alternate solution, the RFID tag devices were placed in the position of the anchor devices. Thus, to track an object, the object was equipped with an RFID reader while many RFID tags were placed in the industrial facility. The biggest shortfall of the proposed system was the small coverage area. After the experiments, the researchers concluded that the proposed system needed many tags to achieve small localization errors, which results in high costs for large coverage areas [native techniques. To this end, an RTLS implementation based on Bluetooth v4.2 on an Apple iPhone 5s device was proposed. The researchers conducted two experiments, using three and then four beacons, placed in two different ways. The overall average error in this experiment was calculated to be 0.77 m [34]. Moreover, an analysis of the tracking accuracy of the new version of Bluetooth, 5.1, has been conducted, and the average error was 0.7 m [35].