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https://www.um.edu.mt/library/oar/handle/123456789/25030
Title: | SCENARIO - setting crowd events using augmented reality and artificial intelligence |
Authors: | Farrugia, Vincent Emmanuel Montebello, Matthew Dingli, Alexiei |
Keywords: | Business logistics Genetic algorithms Mobile communication systems in education Augmented reality Artificial intelligence |
Issue Date: | 2013 |
Publisher: | ICAART |
Citation: | Farrugia, V. E., Montebello, M., & Dingli, A. (2013). SCENARIO - setting crowd events using augmented reality and artificial intelligence. 5th International Conference on Agents and Artificial Intelligence - ICAART2013, Barcelona. 225-233. |
Abstract: | Crowd events pose numerous challenges on organisers, security personnel, and attendees who experience the event and who potentially can be at risk should an emergency arise. The research documented in this paper presents a system, SCENARIO, which aims to provide tools to aid organisers and attendees during crowd events. The system automates the organisation of the layout of attractions, attempts to reduce crowd con- gestion and enhances attendees’ safe experience. An optimiser agent was developed to solve a variant of the NP-Complete Facility Layout Problem to reduce congestion for venues which may include obstructions. Fur- thermore, an agent-based simulator is provided for visualising the effect of a layout on crowd flows, with the employment of a combination of a number of path-finding techniques. Moreover, a mobile agent, deployed on a hand-held device, visually and dynamically lays out an optimised path for attendees to assist their transition to their chosen attraction making use of path-finding structures, GPS and Augmented Reality, together with on-board sensors. The results presented show that the time for the layout optimisation convergence varies depending on complexity, with satisfactory layout output. Simulations run at efficient rates and agents keep their mobile state and avoid extreme congestion. |
URI: | https://www.um.edu.mt/library/oar//handle/123456789/25030 |
ISBN: | 9789898565389 |
Appears in Collections: | Scholarly Works - FacICTAI |
Files in This Item:
File | Description | Size | Format | |
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59.pdf Restricted Access | Full paper | 7.19 MB | Adobe PDF | View/Open Request a copy |
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