Conference Information

AI-SIIS 2026: IEEE International Conference on AI and Security for Industrial IoT Systems

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Submission Date:
2026-02-15
Notification Date:
2026-04-25
Conference Date:
2026-09-24
Location:
Hyderabad, India
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Call For Papers

AI-SIIS 2026 (IEEE International Conference on AI and Security for Industrial IoT Systems) is an academic conference held in Hyderabad, India on 2026-09-24. The paper submission deadline is 2026-02-15. Acceptance notifications are sent on 2026-04-25.

AI-SIIS 2026 focuses on industrial and upcoming frontier technologies, applications of electronics, controls, communications, instrumentation and computational intelligence. The objectives of the conference are to provide high quality research and professional interactions for the advancement of science, technology, and fellowship. Papers with new research results are encouraged for submission. Technical Topics (but not limited to) Track 1: AI-Based Security and Intelligence for Industrial IoT AI-based threat detection and mitigation for Industrial IoT (IIoT) Machine learning for anomaly detection in industrial networks Federated and distributed learning for industrial cybersecurity Fault-tolerant AI architectures for industrial automation Intrusion detection and prevention in smart factories Deep learning for malware classification in IIoT environments Blockchain for secure IIoT data sharing and identity management Track 2: AI for Smart Healthcare and Medical IoT Deep learning for disease diagnosis and early detection AI-enabled predictive healthcare analytics and patient monitoring Federated learning for clinical data sharing and privacy preservation Explainable AI (XAI) for medical decision-making Reinforcement learning in personalized treatment planning AI-driven biomedical signal and image analysis Digital twins and AI modeling for healthcare systems AI for remote monitoring and telemedicine applications Track 3: Secure and Ethical AI Systems for Industry and Society Ethics-by-design frameworks for AI in industrial automation AI control mechanisms and failsafe architectures Explainability and interpretability for critical decision systems AI accountability and auditability models Managing algorithmic bias in industrial and social contexts Standards and benchmarks for ethical and safe AI Track 4: Human–Machine Collaboration and Cognitive AI Systems AI-driven human-machine collaboration in industrial environments Cognitive AI systems for decision support and control Adaptive interfaces for human-in-the-loop systems Trust, transparency, and human factors in AI-enabled operations Track 5: Smart and Intelligent Sensor Applications AI and machine learning for sensor data processing Sensor fusion and signal conditioning Self-calibrating and self-healing sensors Smart camera systems Industrial IoT and predictive maintenance sensors
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