Scope

Nowadays, nearly 15 years following the introduction of the Industry 4.0 paradigm, the convergence of the Internet of Things (IoT), Artificial Intelligence (AI), and cyber-physical systems continues to redefine industrial competitiveness across domains such as manufacturing, energy, healthcare, and smart cities. IoT technologies extend digital infrastructures into the physical world through connected devices that sense, reason, and act. Meanwhile, AI and machine learning enable the orchestration of complex data flows, predictive insights, and autonomous decision-making across distributed environments.

Recent breakthroughs in Large Language Models (LLMs) and AI agents are accelerating a new wave of intelligence in IoT ecosystems. In 2026, Agentic AI systems can act as autonomous software entities that are capable of planning, collaboration, and continuous adaptation, which represents a major step forward for the Industry 5.0 vision. When integrated into the IoT continuum, these agents can coordinate distributed devices and services, enable self‑organization and contextual reasoning at the edge, and support human experts in high-stakes decision management. However, ensuring trustworthiness, accountability, safety, and compliance in such multi-agent environments remains a pressing challenge. This challenge also involves compliance to the regulatory environment, such as the AI Act in the European Union.

In this context, emerging research directions highlight the importance of regulatory intelligence, compliance orchestration, and trusted data governance across decentralized infrastructures. Similarly, the integration of advanced reasoning techniques (such as neuro-symbolic learning and knowledge-driven inference) can complement conventional Machine Learning and LLM-based reasoning to enhance explainability, reliability, and alignment with human values. Nevertheless, addressing these dimensions requires rethinking how IoT/AI systems are designed, tested, and validated within complex multi-stakeholder ecosystems that combine autonomy with human oversight.

Building on the success of its previous editions, the TI-2026 Workshop welcomes original contributions on next-generation architectures, tools, and methodologies for developing trusted, human-centered, and agentic IoT/AI systems aligned with Industry 5.0 principles.

Topics of Interest

Contributions are invited in, but not limited to, the following areas:

• Architectures and frameworks for multi-agent and agentic IoT/AI systems.
• Autonomous agent workflows and pipeline orchestration in industrial environments.
• Federated and decentralized approaches for trusted knowledge exchange and collaboration.
• Distributed reasoning, neuro-symbolic AI, and cognitive architectures for IoT agents.
• Intelligent resourcre management and orchestration in converged telco/cloud/edge environments for Industry 4.0 and Industry 5.0 applications.
• Regulatory intelligence, compliance-by-design, and trustworthy data governance.
• Verified and explainable decision-making in AI-enabled industrial systems, including LLM-based and Agentic AI systems.
• Distributed Ledger Technologies (DLTs) and smart contracts for autonomous and auditable operations in support of emerging AI-based systems.
• Security, safety, and privacy in agentic and decentralized IoT/AI systems.
• Human-AI collaboration, human-in-the-loop control, and interaction design for Industry 5.0.
• Resource-efficient and adaptive deployment of LLMs and AI agents at the edge.
• Digital twins and cyber-physical simulations supported by LLMs and autonomous reasoning.
• Generative and multimodal AI for intelligent sensing, monitoring, and anomaly detection in IoT settings.
• Data spaces and interoperability strategies enabling cross-organizational collaboration and trust.

Objectives

The TI-2026 Workshop aims to bring together researchers, practitioners, and policymakers from academia, industry, and governance bodies to:

• Discuss new paradigms for agentic, decentralized, and human-aligned AI/IoT systems, including the evolution of LLM-based systems and agentic systems.
• Share case studies and open-source tools enabling trustworthy, compliant, and explainable automation.
• Explore socio-technical and regulatory implications of next-generation IoT ecosystems.

For Authors

Prospective authors are invited to submit high-quality original technical papers reporting original research of theoretical or applied nature for presentation at the workshop and publication in the TI-2026 Proceedings. All papers will be reviewed and evaluated by independent experts and selected based on their originality, merit, and relevance to the workshop. Accepted papers will be published as part of the IEEE DCOSS-IoT 2026 conference proceedings and submitted to IEEE Xplore.

The authors of accepted papers will be required to prepare a presentation in PDF file format and provide it along with the camera-ready manuscript. All presentations will be made publicly available.

The manuscripts must be prepared in English, following the IEEE two-column Manuscript Templates for Conference Proceedings (available here) with a maximum length of eight (8) printed pages including text, figures, and references. Authors may add at most two (2) pages, but only for an appendix, i.e. these two pages contain supplementary material only. The additional two pages will incur overlength charges at $100/page.

Submissions will be made using the EasyChair system. The workshop submission link is: TI-2026.

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