# Indoor-Guided Navigation for People Who Are Blind: Crowdsourcing for Route Mapping and Assistance
## 1 Introduction
For that matter, they use wearable ETA equipment with IMU sensors, stereo, and IR (depth) video cameras that record a visual stream and send it through Wi-Fi or GSM to the web cloud server where adapted SLAM algorithms produce clouds of characteristic points for each sequential video frame and use this information to form 3D routes. In our setting, we call this set of procedures the first operational modality. In the proposed setting, the wearable ETA device undergoes some initial real-time data stream processing using Raspberry Pi4 and local mini PCUs such as NUC, but the main computational vision-based algorithms do the rest of the work offline in the web cloud server (video stream data from the wearable ETA device have to be transferred in advance). The server side analyzes video streams, recognizes objects, classifies them, measures distance and direction, and relates semantic POI tags with route coordinates. In the second operational modality, the database of prearranged routes for people who are BSVI is maintained in the web cloud server and is available online for their use. People who are BSVI use the same wearable ETA equipment with a local mini PCU, such as the NUC. They can choose building and indoor routes from the online web cloud database using the mobile app. Wearable ETA equipment use computational vision-based algorithms such as SLAM to recognize clouds of points on the BSVI route and guides the BSVI user through bone-conductive headphones and tactile signals. The latter are displayed using a unique headband with a tactile interface display. In this way, people who are BSVI can arrive at their desired indoor destinations through visual-based guided navigation. In the proposed approach, the third operational modality deals with extraordinary situations such as dead reckoning and unrecognized paths or objects. For that reason, BSVI can use the mobile app to call volunteers who are familiar with that building or who were involved with the production of its routing data in the first modality. The web cloud server provides information about the current BSVI position on the chosen route (or last known location) and on that building's digitalized evacuation scheme. A volunteer can help to recognize obstacles, read texts, and find a route in dead reckoning situations. Compared with other earlier-reviewed approaches, this novel indoor navigation setting for people who are BSVI requires relatively more input from (i) social networking using the help of volunteers, (ii) AI-based computational intelligence algorithms, (iii) server and client-side processing power units, and (iv) a Wi-Fi or GSM Internet connection. However, its main advantages are (1) the indoor route database is available 24/7 (a kind of Visiopedia), (2) it has an offline working mode, (3) there is no need for indoor infrastructural investments, (4) it has an autonomous and flexible, wearable ETA device with a tactile display and bone-conductive headphones, (5) real-time online volunteer help is available in complex situations using a mobile app, (6) it employs a user-centric approach, and (7) routes can be rated after each guided navigation to allow consequent improvement of the route database via BSVI feedback. The remainder of the paper is organized as follows: Section 2 briefly describes the results of a survey conducted on people who are BSVI concerning their navigation and social networking needs and expectations; Section 3 layouts some insights on ETA enhancements of navigation and orientation using the advantages of participatory Web 2.0; Section 4 brings forth the wearable prototype R&D challenges; Section 5 provides web-based crowd-assisted social networking implications for navigation indoors; Section 6 presents the conclusions and discussion.