Human-Centric AIoT and Swarm Intelligence for Dynamic Energy Optimization and Decision-Making in Smart Factories

The convergence of Artificial Intelligence of Things (AIoT) and Swarm Intelligence (SI) represents a transformative shift in smart manufacturing, particularly when designed to include human-in-the-loop feedback. This paper proposes a unified framework for real-time energy optimization, dynamic pricing response, and collaborative decision-making using AI-driven forecasting, swarm coordination, and human oversight. A synthetic dataset simulating four factories shows strong correlations between AI prediction accuracy, energy cost reduction, swarm agent efficiency, and supervisory interventions. The results suggest such hybrid systems reduce energy waste, increase resilience, and enable ethically aligned industrial automation.

物联网人工智能（Artificial Intelligence of Things, AIoT）与群智能（Swarm Intelligence, SI）的融合，为智能制造领域带来了变革性的转变，尤其是在设计引入人在回路反馈（human-in-the-loop feedback）机制的场景下。本文提出了一种统一框架，依托人工智能驱动的预测、群智能协同与人工监管，实现实时能源优化、动态电价响应与协同决策。本研究所构建的模拟四家工厂运行的合成数据集（synthetic dataset），证实了人工智能预测准确率、能源成本削减幅度、群智能体（swarm agent）运行效率与监管干预（supervisory interventions）力度之间存在显著相关性。研究结果表明，此类混合系统可降低能源浪费、提升系统韧性，并实现符合伦理准则的工业自动化应用。