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Smart city article details
| Title | Paving The Way Towards Collective Intelligence At The Iot Edge |
|---|---|
| ID_Doc | 41489 |
| Authors | Mohamudally N. |
| Year | 2022 |
| Published | Procedia Computer Science, 203 |
| DOI | http://dx.doi.org/10.1016/j.procs.2022.07.004 |
| Abstract | With the scale of data generated and the increasing computing capabilities at the IoT Edge, moving intelligence to end-devices and gateways in IoT networks is within the realms of possibility. There are tremendous hopes on how self-awareness in IoT networks could be helpful to solve a variety of smart city use case problems. Self-awareness implies self-teaching; the network devices autonomously become smarter with AI. Collective intelligence is a subset of self-awareness but not yet formalized and exploited at the Edge of IoT networks. In this paper, current mathematical models for Collective Intelligence are studied and compared. Their suitability for on-device machine learning deployment is also explored. Moreover, it attempts to lay down a framework using graph theory coupled with artificial neural networks to model a collective intelligence system applicable to a specific scenario. © 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the Conference Program Chairs. |
| Author Keywords | AIoT; Collective Intelligence; Distributed Intelligence; Edge AI; End-devices; Graph Theory; Swarm |
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