Change search
ReferencesLink to record
Permanent link

Direct link
Finding the Nearest Wheelchair: the Application of AI Search Methods to Logistical Problems in the Hospital
Norwegian University of Science and Technology, Faculty of Information Technology, Mathematics and Electrical Engineering, Department of Computer and Information Science.
2014 (English)MasteroppgaveStudent thesis
Abstract [en]

Ever since the invention of the Global Positioning System (GPS) and its slow entry into the public domain in the 80s and 90s, location tracking has become an increasingly important tool for scientific research, surveillance, and commerce. The potential for increased efficiency and quality of care has resulted in an increase in Indoor Positioning System (IPS) technology uptake by the healthcare sector. The main focus of this master’s thesis has been on the application of search methods from Artificial Intelligence (AI) literature to a logistical problem in the hospital, facilitated by the use of location tracking technologies. Using a Requirements Engineering (RE) framework the thesis explores use cases where time spent looking for wheelchairs can be reduced. The three use cases: “View Wheelchair Location”, “Find Available Wheelchair”, and “Find Nearest Wheelchair” was identified, where finding the nearest wheelchair was found to be most suitable for further investigation. The thesis proposes a search framework for describing the problem of finding the nearest wheelchair given the current position and task information of a hospital porter. Furthermore, the RE study proposes a set of requirements that the search framework must adhere to. A literature study of AI search methods such as the well known Dijkstra’s and A* algorithm along with different kinds of acceleration methods were performed, and a prototype of the search framework was built. The search framework and all the proposed search methods have been evaluated by performing a series of experiments on two different kinds of datasets made by the author.

Place, publisher, year, edition, pages
Institutt for datateknikk og informasjonsvitenskap , 2014. , 82 p.
URN: urn:nbn:no:ntnu:diva-26792Local ID: ntnudaim:9264OAI: diva2:751700
Available from: 2014-10-01 Created: 2014-10-01 Last updated: 2014-10-01Bibliographically approved

Open Access in DiVA

fulltext(3163 kB)475 downloads
File information
File name FULLTEXT01.pdfFile size 3163 kBChecksum SHA-512
Type fulltextMimetype application/pdf
cover(184 kB)9 downloads
File information
File name COVER01.pdfFile size 184 kBChecksum SHA-512
Type coverMimetype application/pdf
attachment(25 kB)6 downloads
File information
File name ATTACHMENT01.zipFile size 25 kBChecksum SHA-512
Type attachmentMimetype application/zip

By organisation
Department of Computer and Information Science

Search outside of DiVA

GoogleGoogle Scholar
Total: 475 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 52 hits
ReferencesLink to record
Permanent link

Direct link