Year: 2024
Type: article
Abstract: Considering the navigation for complex spaces in large buildings such as campuses, hospitals, public buildings, and shopping malls, where there is a high probability of getting lost, it is believed that a successful navigation approach for indoor spaces will positively impact our lives in the same way as solutions for outdoor spaces.The challenges arising from the structural complexity of buildings are increasing the interest in indoor map generation and the establishment of indoor navigation network models has become an important research topic.In facility management, there is a growing demand to identify human movement associated with indoor environments and to develop various applications for wayfinding that support human spatial cognition.In disaster and emergency management, indoor navigation is of great importance in the development of building evacuation scenarios.Outdoor navigation is widely used in navigation applications due to the positioning accuracy provided by GNSS.Due to the unavailability of GNSS indoors, the use of positioning systems such as RFID (Radio Frequency Identification), UWB (Ultra Wide Band) and WLAN (Wireless Local Area Network) is developing (Sen et al., 2024).Besides, the fact that outdoor spaces are surrounded by street networks makes it easier to establish a navigation network for the use of a navigation system.In contrast to outdoor spaces, indoor spaces are typically bounded by architectural structures.The lack of predetermined walking routes such as street networks or sidewalks, the fact that interiors contain structural elements such as columns and walls that restrict visibility, their differentiated structures depending on their architectural design, and their multi-storey structure generally make interiors more complex than exteriors.This study aims to integrate the landmarks and actions extracted by using Natural Language Processing (NLP) methods from crowdsourced human route descriptions collected on the Soleway web service (https://soleway.ugent.be/),which is a crowdsourced database that collects human route descriptions for indoor navigation (Ooms et al., 2019), into the indoor
Source: Abstracts of the ICA
Author: Alper Sen
Institution: Yıldız Technical University
Language: English
Subfield: Automotive Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4402202220