# Mobile-AI-Based Docent System: Navigation and Localization for Visually Impaired Gallery Visitors
## 3 Material and Methods  
### System Design  
The overview of the proposed guide system is shown in Figures 1 and 2. The system provides a comprehensive navigation and guidance service for visually impaired individuals, combining real-time location tracking, adaptive audio guidance, and obstacle detection to ensure safe and informative exploration of the art gallery environment. The navigation service enables people to move along a predefined route while avoiding obstacles, including other people. As shown in Figure 2, the localization module determines the user's location by utilizing ML models based on the RSSI from BLE beacons. BLE beacons are installed on the ceiling of the art gallery and set to advertising mode. A mobile device continuously scans the RSSI values from these beacons and transmits the data to the server. The server then processes the data using pre-trained machine-learning models to estimate people's location. Since RSSI values can be affected by environmental noise and movement, the system includes a localization error calibration process to detect and correct localization errors. The calibration process refines the estimated location by comparing it with the previous position. The system provides various navigation instructions based on people's location. For example, when they reach a corner, a voice guide instructs them to change direction. Similarly, when they approach an artwork, an audio announcement informs them about the surrounding exhibits. Additionally, the system continuously refines localization accuracy using movement history. Algorithm 1 represents the error calibration and the guide comment that varies depending on the measured location. For example, if the previous location number is 3, the measured location number is 5, and \(Th\) is 1, the measured location is in error and it is ignored. However, if \(Th\) is 2, the measured location is not an error, and the user's current location changes to location number 4. \(Th\) is set as the appropriate value during the experiment. When the user arrives at the location of the artwork, the system notifies them that the artwork is nearby. If the user looks at the artwork, the system provides a  
Figure 1: System architecture. information as voice guide. When the user moves away from the artwork, the system automatically stops the voice guidance to prevent unwanted audio. The depth of the guide service is a novel feature that adaptively provides an audio guide based on people's behavior, as shown on the left side of Figure 1. First, when a person approaches an artwork, the system announces that there are artworks nearby. Second,  
Figure 2: Framework of the system consisting of the navigation service and the adaptive depth of the guidance service. if they look at the artwork, the system provides detailed information about it. Third, when they move away, the audio guide stops automatically. This process is managed by the localization module and the orientation module, which utilize the mobile device's magnetic field and gyroscope sensors. As a result, the system dynamically adjusts the audio guide, ensuring that it provides relevant information while avoiding unnecessary sounds. Notably, the initiation and termination of the descriptions occur automatically. The Detection Module implements the YOLOv5 deep learning architecture for efficient image analysis and obstacle identification. For individuals with visual disabilities, the capacity to promptly identify obstacles is vital for ensuring safety and independence while navigating unfamiliar environments [1]. This capability is particularly relevant in art gallery settings, which present unique navigational challenges. Introduced in 2020, YOLOv5 has established its reputation for exceptional computational efficiency and performance speed, making it particularly appropriate for deployment in edge computing environments with resource constraints--a critical consideration for mobile applications.