# A Comprehensive Review of Indoor Localization Techniques and Applications in Various Sectors
## 3 Methodology and Application of Indoor Localization in Various Fields
### Transforming Industrial Operations with Indoor Localization Technologies
#### 3.2.2 RFID-Based Methodology for Construction Sites  
[PERSON] et al. [59] introduce a low-cost indoor localization and material tracking system using ultra high frequency (UHF) passive RFID technology, specifically designed for construction projects. This system aims to automate the tracking of materials, workforce, and equipment in near real-time to improve project management and operational efficiency. The methodology relies on strategically placed RFID reference tags and mobile RFID readers carried by workers to capture location data. The system architecture consists of several key components, as shown in Figure 15, integrating RFID reference tags, mobile RFID readers, and a positioning database to enable user and material localization. RFID reference tags are strategically placed across predefined zones, serving as landmarks with known locations. Workers carry mobile RFID readers, which detect signals from passive RFID tags and capture RSSI values. The collected data, including tag IDs, RSSI values, worker movements, and timestamps, are stored in a relational database for efficient retrieval and analysis. The process begins with Step One, where the system updates the position and applies trilateration or proximity-based localization to determine the user's location. Once the user is located, the system moves to Step Two, focusing on material localization. Using the positioning database, it retrieves location data, applies trilateration or proximity-based localization, and identifies the material's position. This methodology ensures precise tracking of users and materials, making it highly applicable in construction, logistics, healthcare, and industrial environments, where RFID-based positioning enhances operational efficiency. Figure 14: Scenario analysis for UWB localization positioning method. (**a**) Precision of ranging; (**b**) position detection precision; and (**c**) localization precision in dynamic environments. Two primary localization methods are employed to determine the position of workers and materials. Figure 16 illustrates the optimized deployment of RFID reference tags and its flowchart. The first method, triangulation, estimates a worker's position by measuring distances to multiple reference tags based on RSSI values. These distances are represented as circles centered on the known locations of the reference tags. The worker's location is determined by finding the intersection of these circles, and the area with the smallest sum of radii is selected to minimize errors. The second method, proximity-based localization, estimates the worker's position by identifying the closest reference tags and calculating a weighted average of their coordinates based on RSSI values [59]. The system follows a two-step algorithm for tracking. In the first step, the mobile RFID reader captures signals from the reference tags to identify the worker's location, which is then stored in the database along with a timestamp. In the second step, materials tagged with RFID labels are tracked by associating their location with the worker's identified position. As workers move through the site, the system captures signals from material tags and uses either the triangulation or proximity method to determine the material's location. The methodology was validated through experiments conducted on a real construction site and in a controlled laboratory environment. Five test beds were set up to cover various  
Figure 16: Optimizing the deployment of RFID reference tags. Figure 15: Development methodology of RFID system. areas and time spans. The results showed a mean error of 1.0 m for worker localization using triangulation and 1.9 m for material tracking. The proximity method produced a mean error of 1.9 m for worker localization and 2.6 m for material tracking. Additionally, the system demonstrated 100% accuracy in identifying the correct zones for both workers and materials. This approach offers a cost-effective and low-maintenance solution for tracking materials and workforce in dynamic construction environments.