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http://hdl.handle.net/1893/3371| Appears in Collections: | Computing Science and Mathematics Journal Articles |
| Peer Review Status: | Refereed |
| Title: | Sensing Emergence in Complex Systems |
| Author(s): | Niazi, Muaz A K Hussain, Amir |
| Contact Email: | thhgttg@gmail.com |
| Keywords: | Event detection Multiagent systems Agent-based simulation complex adaptive system environment flocking cognitive sensor network Wireless sensor network Computer simulation Simulation methods Computer networks |
| Issue Date: | Oct-2011 |
| Date Deposited: | 28-Sep-2011 |
| Citation: | Niazi MAK & Hussain A (2011) Sensing Emergence in Complex Systems. IEEE Sensors Journal, 11 (10), pp. 2479-2480. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5750012&isnumber=5975325; https://doi.org/10.1109/JSEN.2011.2142303 |
| Abstract: | We propose the Sensing of Emergent behavior in a Complex Adaptive System (SECAS), an extension of our previous work Formal Agent Based Simulation Framework (FABS). Using aggregated data from an array of proximity sensors, SECAS allows for the detection of complex behavior such as flocking of mobile robots or life forms. For validation, we develop an agentbased simulation model. Extensive simulation experiments using a wide range of randomly deployed sensors demonstrate the effectiveness of SECAS in the sensing of flocking. |
| URL: | http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5750012&isnumber=5975325 |
| DOI Link: | 10.1109/JSEN.2011.2142303 |
| Rights: | Published in IEEE Sensors Journal. © Copyright 2011 IEEE.; © 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| final_secas_authors_versionv1.pdf | Fulltext - Accepted Version | 305.3 kB | Adobe PDF | View/Open |
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