Geospatial Information System based on indoor plan UKM (FKAB)

• Main Authors: Zikrul Hakiem Ishak, Sallehuddin Mohamed Haris, Wang, Long
• Format: Article
• Language: English
• Published: Penerbit Universiti Kebangsaan Malaysia 2020
• Online Access: http://journalarticle.ukm.my/17141/1/19.pdf; http://journalarticle.ukm.my/17141/; https://www.ukm.my/jkukm/volume-323-2020/
• Institution: Universiti Kebangsaan Malaysia

In recent years, the academic field has seen tremendous leaps in mapping and navigation technology. Features such as accuracy, functionality, time efficiency and ease of access in mobile mapping applications have poured into the market, which has led to the near extinction of conventional paper maps. Big players such as Google Maps, MapBox, Bing Maps, OpenStreetMap and many others are enabling Geospatial Information Systems (GIS) to be accessed with ease. However, the problem arises as GIS is more tailored towards outdoor mapping and navigation information through the implementation and utilization of Global Positioning System (GPS) coordinates. The main objective of this study was to enable GIS incooperated together with georeferenced image containing global positioning coordinates (GPS) making it feasible and compatible for the purpose of positioning and navigation focusing in an indoor environment. In this research, we present a method for utilising GIS for indoor localisation focusing on using Quantum GIS (QGIS) as the open source Geospatial Data Abstraction Library (GDAL), and the rendering of raster maps by locating ground control points (GCP). As a case study, the method was implemented on the 2nd Floor, East Wing of the Faculty of Engineering and Built Environment (FKAB) of Universiti Kebangsaan Malaysia (UKM), as the indoor space of interest. The significant findings of this paper contribute to the possibility of using GPS coordinates in an indoor environment for accurate positioning. Consequently, the proposed method has the potential to perform as an easily implementable localisation technique in Simultaneous Localisation and Mapping (SLAM) applications for mobile robots.