Autonomous and Self-organized Artificial Intelligent Orchestrator for a Greener Industry 4.0 (TALON)

下一代工业系统承诺不仅在性能方面，而且在解释能力、可信度和透明度方面提供前所未有的卓越。为了实现这一新目标，人工智能（AI）、边缘到云（E2C）计算、区块链和可视化等最先进的概念需要去风险化和应用。受此启发，TALON旨在通过开发一种全自动的人工智能架构，为下一次工业革命开辟道路，这种架构能够以灵活、适应性强、可解释、节能和数据高效的方式将智能推向边缘。TALON架构由三个基本支柱组成：a)一个人工智能协调器，协调网络和服务协调器，以优化边缘与云的关系，同时通过决定每个数据集、算法和模型的位置来提高数据集、算法和模型的可重用性；B)在隐私和安全保护伞下引入新的服务模型和应用程序的轻量级分层区块链方案；c)新的数字孪生增强迁移学习和可视化方法，提高人工智能的可信度和透明度。它结合了人工智能、边缘和云网络以及区块链和dt的优势，并通过a)新的关键绩效指标进行优化，将人工智能的优势转化为有洞察力的指标；b)描述人工智能特征的新颖理论框架；C)区块链用于提供基于安全、隐私和信任机制的个性化和永久保护；d)用于自动和协同优化边缘和云资源以及AI执行节点的AI方法；e)语义AI，减少学习延迟，增强可重用性；f)数字双胞胎，将人工智能输出可视化，并结合人在环的方法。所有的技术突破都通过概念验证仿真和四个真实世界的飞行员进行了演示，验证和评估。

Next generation industrial systems promise to deliver unprecedented excellence not only in terms of performance, but also explain ability, trustworthiness, and transparency. To achieve this new objectives, state-of-the-art concepts of artificial intelligence (AI), edge-to-cloud (E2C) computing, blockchain, and visualisation need to be de-risked and applied. Motivated by this, TALON aims at sculpturing the road towards the next Industrial revolution by developing a fully automated AI architecture capable of bringing intelligence near the edge in a flexible, adaptable, explainable, energy and data efficient manner. TALON architecture consists of three fundamental pillars: a) an AI orchestrator that coordinates the network and service orchestrators in order to optimise the edge vs cloud relationship, while boosting reusability of datasets, algorithms and models by deciding where each one should be placed; b) a lightweight hierarchical blockchain schemes that introduce new service models and applications under a privacy and security umbrella; and c) new digital-twin empowered transfer learning and visualization approaches that enhance AI trustworthiness and transparency. It combines the benefits of AI, edge and cloud networking, as well as blockchain and DTs, optimized by means of a) new key performance indicators that translate the AI benefits into insightful metrics; b) novel theoretical framework for the characterisation of the AI; c) blockchain used to deliver personalised & perpetual protection based on security, privacy and trust mechanisms; d) AI approaches for automatically and co-optimising edge and cloud resources as well as the AI execution nodes; e) semantic AI to reduce the learning latency and enhance reusability; and f) digital twins that visualize the AI outputs and together with human-in-the-loop approaches. All the technological breakthroughs are demonstrated, validated and evaluated by means of proof-of-concept simulation and four real-world pilots.