The Internet of Things (IoT) continues to transform power systems by enabling massive-scale sensing, actuation, and machine-to-machine (M2M) coordination across the electricity value chain. Building on the SGIoT 2025 focus on IoT-driven smart grid communications, edge intelligence, reliability, and cybersecurity, SGIoT 2026 highlights the rapid convergence of Artificial Intelligence and IoT (AIoT) toward data-driven, autonomous, and resilient grid operations. SGIoT 2026 invites original research and practical innovations on how to achieve secure, efficient, and sustainable energy systems through the integration of edge–cloud–device computing, learning at the edge (e.g., federated learning), and AI-powered digital twins for planning, operation, and real-time optimization. The conference particularly welcomes contributions addressing next-generation grid challenges such as high penetration of distributed energy resources (DERs), renewable integration, EV charging and vehicle-to-grid (V2G) coordination, microgrids, and extreme-event resilience—while emphasizing security-by-design and trustworthy / responsible AI for critical infrastructure.

In order to address and solve many of the tough challenges in the IoT-driven smart grid, prospective authors are cordially invited to submit their original and unpublished research contributions to this event on the following technical areas of (but not limited to) smart grid communications and IoT.

A. Smart Grid Communications, Networking, and Computing
• Communication networks for smart grids, AMI, and smart metering (HAN/BAN/NAN)
• Sensor, actuator, and M2M networking for grid monitoring and automation
• Ultra-reliable and low-latency communications (URLLC) for grid control (5G/6G, private 5G)
• Time-sensitive / deterministic networking for cyber-physical energy systems
• Edge–cloud–device collaboration and resource orchestration in AIoT smart grids
• Interoperability, middleware, and scalable data pipelines for grid IoT
B. AIoT, Edge AI, and Data Analytics for the Grid (Main Theme)
• Machine learning for smart device networking and traffic engineering
• Edge AI / TinyML for low-power sensing, anomaly detection, and event classification
• Federated learning, split learning, and privacy-preserving analytics for grid/IIoT
• Continual / online learning for non-stationary grid environments
• Physics-informed ML and hybrid AI + power-system modeling
• Generative AI for grid operation assistance (planning, diagnostics, decision support)
• Data quality, uncertainty quantification, and explainable AI for safety-critical decisions
C. Control, Optimization, and Energy Management
• Control techniques for smart grid energy systems
• Demand-side management, demand response, and dynamic pricing
• Distributed / multi-agent optimization for DER coordination and microgrid control
• Transactive energy, energy trading, and market mechanisms enabled by AIoT
• Carbon-aware / sustainability-aware scheduling and optimization
• Predictive maintenance, asset health monitoring, and outage management with Edge AI
D. DERs, Renewables, EVs, and Grid Edge
• Renewable integration, forecasting, and grid stability enhancement
• Microgrids, virtual power plants (VPPs), and DER aggregation/orchestration
• EV charging infrastructure, V2G/V2H coordination, and grid impact analysis
• Edge intelligence for local autonomy and hierarchical control
• Energy storage coordination and hybrid energy systems
E. Reliability, Resilience, Cybersecurity, Privacy, and Trustworthy AI
• Reliability, availability, resiliency, robustness, and fault tolerance in smart grids
• Security-by-design for grid IoT devices: identity, key management, secure boot, OTA updates, lifecycle security
• Smart grid cybersecurity: threat modeling, intrusion detection, incident response
• AI security for grid applications: adversarial ML, data poisoning, model integrity, robust training
• Privacy, governance, and risk management for AI-enabled critical infrastructure
• Explainability, auditing, and compliance of AI models for grid-critical decisions
F. Digital Twins, Testbeds, Benchmarks, and Deployments
• AI-powered digital twins for grid planning, monitoring, and real-time optimization
• Co-simulation, hardware-in-the-loop, and cyber-physical testbeds for AIoT smart grids
• Open datasets, benchmarks, reproducibility, and evaluation methodologies for Edge AI in energy systems
• Large-scale pilots, field deployment lessons, and best practices
• Standards, interoperability, and regulatory considerations for AIoT smart grids

All registered and presented papers will be submitted for publication in the Springer LNICST series and made available through the SpringerLink Digital Library: SGIoT proceedings. This series is indexed in leading indexing services, such as Web of Science, Compendex, Scopus, DBLP, EU Digital Library, Inspec, SCImago and Zentralblatt MATH. 

Available Journals 

Authors of selected papers will be invited to submit an extended version to:

• Mobile Networks and Applications (MONET) Journal [IF: 2.0 (2024)]

Authors have the opportunity to publish their articles in the EAI Endorsed Transactions journal selected by the conference (Scopus, Ei-indexed, ESCI-WoS, Compendex) by paying an additional $250, discounted from the standard $400 rate for conference authors.

• EAI Endorsed Transactions on Internet of Things (Scopus)
• EAI Endorsed Transactions on Energy Web (Scopus, Compendex)

The article’s publication is subject to the following requirements:  

• It must be an extended version of the conference paper with a different title and abstract. In general, 30% of new content must be added.
• The article will be processed once the conference proceedings have been published.
• The article will be processed using the fast-track option.

Once the conference proceedings are published, the corresponding author should contact us at [email protected] with the details of their article to begin processing.

Additional publication opportunities

• EAI Transactions series (Open Access)
• EAI/Springer Innovations in Communications and Computing Book Series
  (titles in this series are indexed in Ei Compendex, Web of Science & Scopus)

EAI is an open community dedicated to creating an environment where every member receives the same opportunities and benefits to develop and grow their research mission and career. As the largest free professional research society in the world, EAI offers a complete range of conference proceedings publication opportunities. Based on the qualification of the conference and the conference scope, EAI provides the possibility to publish the proceedings for every sponsored conference. Consistent with its mission to support developing communities, all EAI sponsored conferences appear in EUDL, the European Union Digital Library (EUDL). EUDL is Open Access and free for EAI members, reaching a community of 250,000 subscribers and providing the visibility that allows the conference organisers to develop the conference into a fully fledged indexed proceedings publication in subsequent years.

Papers should be submitted through the EAI ‘Confy+‘ system, and have to comply with the Springer format (see Author’s kit section).

• Full/ Regular papers should be 12-20 pages in length. (Excluding appendices, references, appreciation, etc.)

*Please note that additional pages will be subject to an extra charge for each extra page uploaded.

All conference papers undergo a thorough peer review process prior to the final decision and publication. This process is facilitated by experts in the Technical Program Committee during a dedicated conference period. Standard peer review is enhanced by EAI Community Review which allows EAI members to bid to review specific papers. All review assignments are ultimately decided by the responsible Technical Program Committee Members while the Technical Program Committee Chair is responsible for the final acceptance selection. You can learn more about Community Review here.

1. Go to Confy+ website.
2. Log in or sign up as a new user.
3. Select your desired track.
4. Click the ‘Submit Paper’ link within the track and follow the instructions.

• All papers must be submitted in English. 

• Submitted PDFs should be anonymized.

• Previously published work cannot be submitted, nor can it be concurrently submitted to any other conference or journal. These papers will be rejected without review. 
• Papers must follow the Springer formatting guidelines (available in the Author’s Kit section). 
• Authors must read and agree to the Publication Ethics and Malpractice Statement.
• As per new EU accessibility requirements, going forward, all figures, illustrations, tables, and images should have descriptive text accompanying them. Please refer to the document below, which will assist you in crafting Alternative Text (Alt Text)

HOW TO WRITE GOOD ALT TEXT

For full information, click HERE.

AI Authorship Policy

Large Language Models (LLMs), such as ChatGPT, do not currently satisfy our authorship criteria. Notably an attribution of authorship carries with it accountability for the work, which cannot be effectively applied to LLMs. We thus ask that the use of an LLM be properly documented in the Acknowledgements, or in the Introduction or Preface of the manuscript.

The use of an LLM (or other AI-tool) for “AI assisted copy editing” purposes does not need to be declared. In this context, we define the term “AI assisted copy editing” as AI-assisted improvements to human-generated texts for readability and style, and to ensure that the texts are free of errors in grammar, spelling, punctuation and tone. These AI-assisted improvements may include wording and formatting changes to the texts, but do not include generative editorial work and autonomous content creation. In all cases, there must be human accountability for the final version of the text and agreement from the authors that the edits reflect their original work. This reflects a similar stance taken on the AI generative figures policy, where it was acknowledged that there are cases where AI can be used to generate a figure without being concerned about copyright e.g. to generate a graph based on data provided by the author. 

AI Authorship Guidance

Authors should familiarise themselves with the current known risks of using AI models before using them in their manuscript. AI models have been known to plagiarise content and to create false content. As such, authors should carry out due diligence to ensure that any AI-generated content in their book is correct, appropriately referenced, and follow the standards as laid out in our Book Authors’ Code of Conduct.

AI-generated Images Policy

The fast-moving area of generative AI image creation has resulted in novel legal copyright and research integrity issues. As publishers, we strictly follow existing copyright law and best practices regarding publication ethics. While legal issues relating to AI-generated images and videos remain broadly unresolved, Springer Nature journals and books are unable to permit its use for publication.

Exceptions:

• Images/art obtained from agencies that we have contractual relationships with that have created images in a legally acceptable manner.
• Images and videos that are directly referenced in a piece that is specifically about AI and such cases will be reviewed on a case-by-case basis.
• The use of generative AI tools developed with specific sets of underlying scientific data that can be attributed, checked and verified for accuracy, provided that ethics, copyright and terms of use restrictions are adhered to.

Papers must be formatted using the Springer LNICST Authors’ Kit.

Instructions and templates are available from Springer’s LNICST homepage:

• LaTeX2e Proceedings Templates (zip)
• Microsoft Word Proceedings Templates (zip)

Please make sure that your paper adheres to the format as specified in the instructions and templates.

When uploading the camera-ready copy of your paper, please be sure to upload both:

• a PDF copy of your paper formatted according to the above templates, and
• an archive in .ZIP file, containing LaTeX or Word source material prepared according to the above guidelines.