Cognitive Swarm Intelligence in Multi-Agent AIoT Systems in Business & Automation Industries 4.0 & 5.0
Description
Cognitive Swarm Intelligence in Multi-AgeArtificial Intelligence of Things (AIoT) is transforming cyber-physical systems by embedding intelligence at the edge. While traditional AIoT systems often rely on centralized models, they fail in dynamic or bandwidth-limited environments. Swarm intelligence—decentralized coordination inspired by nature—offers a scalable solution. By embedding cognitive capabilities in each agent, this study proposes a cognitive swarm AIoT framework that mimics brain-like adaptability and learning across thousands of distributed nodes. The convergence of artificial intelligence, Internet of Things (IoT), and swarm intelligence has given rise to a new paradigm: Cognitive Swarm Intelligence in Multi-Agent AIoT systems. This field represents the integration of collective decision-making capabilities with distributed intelligent systems, enabling autonomous coordination and optimization across networked devices and agents.nt AIoT Systems in Business & Automation Industries
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This paper introduces a novel framework that combines Cognitive Artificial Intelligence of Things (AIoT) with swarm intelligence to create adaptive, decentralized decision-making systems for industrial and environmental applications. A synthetic dataset of 500 agents simulates autonomous decision-making in an edge-based, bio-inspired environment. Visual analytics and statistical models demonstrate that cognitive swarm systems exhibit superior performance in coordination, adaptability, and energy optimization. This research lays the groundwork for scalable, field-ready AIoT swarms applicable in agriculture, disaster response, and autonomous logistics.
Institutions
- North South University