Tools
Tools
Falcon-Caro, A., Peytchev, E. 
ORCID: 0000-0001-5256-4383 and Sanei, S. ORCID: 0000-0002-3437-2801,
2024.
Adaptive network model for assisting people with disabilities through crowd monitoring and control.
Bioengineering, 11 (3): 283.
Abstract
Here we present an effective application of adaptive cooperative networks namely assisting disables navigating in the crowd in a pandemic or emergency situation. To achieve this, we model the crowd movement and introduce a cooperative learning approach to enable cooperation and self-organization of the crowd members with impaired health or on wheelchair to ensure their safe movement in the crowd. Here, it is assumed that the movement path and the varying locations of the other crowd members can be estimated by each agent. Therefore, the network nodes (agents) should continuously reorganize themselves by varying their speeds and distances from each other, surrounding walls, and obstacles within a predefined limit. It is also demonstrated how the available wireless trackers such as AirTags can be used for this purpose. The model effectiveness is examined with respect to the real-time changes in environment parameters and its efficacy verified.
| Item Type: | Journal article | ||||||
|---|---|---|---|---|---|---|---|
| Publication Title: | Bioengineering | ||||||
| Creators: | Falcon-Caro, A., Peytchev, E. and Sanei, S. | ||||||
| Publisher: | MDPI AG | ||||||
| Date: | 16 March 2024 | ||||||
| Volume: | 11 | ||||||
| Number: | 3 | ||||||
| Identifiers: |
|
||||||
| Rights: | © 2024 by the authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). | ||||||
| Divisions: | Schools > School of Science and Technology | ||||||
| Record created by: | Jeremy Silvester | ||||||
| Date Added: | 24 May 2024 08:30 | ||||||
| Last Modified: | 24 May 2024 08:30 | ||||||
| URI: | https://irep.ntu.ac.uk/id/eprint/51470 |
Actions (login required)
 |
Edit View |
Views
Views per month over past year
Downloads
Downloads per month over past year
