Next-Generation IoT Sensor Systems: Integrating Distributed Intelligence and Decentralised Trust
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".
Deadline for manuscript submissions: 20 March 2026 | Viewed by 1600
Special Issue Editor
Special Issue Information
Dear Colleagues,
The rapid evolution of IoT sensor systems demands integrated solutions for trustworthy, intelligent sensing across industrial, environmental and urban applications. Next-generation architectures require embedded AI capabilities—such as federated learning and neuromorphic computing—to enable autonomous, real-time decision-making at the edge while maintaining cryptographic data integrity and resilience against emerging threats such as model inversion attacks or sensor spoofing. This convergence necessitates novel approaches to AI-driven sensor intelligence, including verifiable neural networks and adaptive calibration algorithms, coupled with distributed trust mechanisms like lightweight blockchain attestation and zero-knowledge proofs. These solutions must address critical challenges of scalability in massive sensor deployments, privacy-preserving data fusion, and security in distributed sensing environments with heterogeneous devices and protocols.
This Special Issue seeks cutting-edge research on integrating trusted AI with IoT sensor systems, with a focus on the following topics:
- Sensor-native trusted AI: Lightweight, verifiable AI models for resource-constrained sensors;
- Trustworthy sensing frameworks: Security and privacy-preserving techniques (e.g., zero-knowledge proofs, homomorphic encryption) for sensor data;
- Autonomous sensor intelligence: Self-adaptive AI for real-time anomaly detection, calibration, and decision-making in sensor networks;
- Resilient sensor–AI ecosystems: Cyber–physical security for sensor spoofing, data poisoning, and adversarial attacks;
- Scalable trust architectures: Decentralized audit trails (e.g., lightweight blockchain) for sensor data provenance and integrity;
- Privacy-aware sensor AI: Federated learning and differential privacy for multi-stakeholder sensor environments.
Original research, case studies, and reviews are welcome. Research advancing theoretical foundations or demonstrating practical deployments of trusted AI in IoT sensor systems, with an emphasis on secure sensor–AI architectures and real-world industrial/transportation/UAV/agricultural implementations—particularly through interdisciplinary integrations of sensor networks, AI, distributed systems, and security—is welcome.
Dr. Xiao Chen
Guest Editor
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Keywords
- next-generation IoT
- sensor networks
- distributed intelligence
- decentralised trust
- 6G communications
- edge AI
- blockchain security
- smart agriculture
- Industry 4.0
- low-altitude economy
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