AIoT Methodologies & Techniques for Reliable CPS and Smart Environment Monitoring
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".
Deadline for manuscript submissions: 15 June 2026 | Viewed by 13
Special Issue Editors
Interests: smart cities; cooperative smart environments; IoT; cyber-physical systems; continuum computing; distributed systems
Special Issues, Collections and Topics in MDPI journals
Interests: cyber-physical systems; cybersecurity; internet of things (IoT); dependability; sustainability
Special Issues, Collections and Topics in MDPI journals
Interests: machine learning; deep learning; cyber physical systems; Internet of Things; anomaly detection; fault diagnosis; edge computing; cloud computing
Special Issues, Collections and Topics in MDPI journals
Interests: parallel computing; natural language processing; artificial intelligence; deep learning; eHealth; big data analytics; cyber physical systems
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
AIoT (Artificial Intelligence of Things) has emerged as a transformative paradigm, integrating AI-driven analytics with IoT networks to enhance the intelligence, efficiency, and reliability of cyber-physical systems (CPS) and smart environment monitoring. The convergence of edge computing, machine learning, and real-time data processing has unlocked new possibilities in automation, predictive maintenance, and environmental sensing by enabling smarter, more responsive infrastructures.
Furthermore, the edge computing facilities offered by a CPS need to manage dynamic workloads, real-time latency constraints, and secure distributed decision-making, while their exploitation models in IoT-driven smart environments rely on adaptive AI at the edge, federated learning for privacy-aware analytics, and fault-tolerant architectures to ensure reliability in large-scale deployments.
As industries and cities evolve toward autonomous operations and sustainable resource management, AIoT plays a pivotal role in ensuring system resilience, data accuracy, and real-time decision-making. However, challenges remain in optimizing AIoT deployments, particularly in scalability, interoperability, and security across heterogeneous environments.
- AIoT for Cyber-Physical Systems (CPS)
CPSs are bridging the physical and digital worlds, but they are demanding high reliability, low latency, and adaptive intelligence to function effectively in dynamic settings. AIoT enhances CPS through:
- Real-time anomaly detection using deep learning on sensor streams,
- Predictive maintenance via AI-based failure forecasting,
- Edge AI deployment for decentralized, low-latency processing.
Key research challenges include model robustness in uncertain conditions, energy-efficient AI at the edge, and secure data fusion across distributed nodes.
- AIoT for Smart Environment Monitoring
Smart environments such as smart cities, precision agriculture, and industrial IoT rely on AIoT for autonomous sensing, adaptive control, and sustainability optimization. Critical applications include:
- Air/water quality monitoring using AI-enhanced sensor networks,
- Traffic and energy management via real-time analytics,
- Disaster prediction through multimodal data fusion.
However, challenges such as sensor drift, environmental noise, and scalability in large deployments must be addressed to ensure long-term reliability.
Call for Contributions
We welcome the submission of high-quality, original research and review papers on the latest advancements in AIoT for CPS and smart environment monitoring and management, with a focus on:
- Novel AI/ML techniques for real-time and distributed intelligence,
- Edge/cloud AI architectures for scalable and low-latency systems,
- Security, privacy, and trust in AIoT-enabled environments,
- System Resiliency, Reliability and Availability,
- Case studies and real-world deployments demonstrating AIoT’s impact.
We particularly welcome contributions that bridge theoretical innovation with practical implementation in industrial, urban, or ecological settings.
Dr. Giuseppe Tricomi
Guest Editor Assistant
Dr. Maurizio Giacobbe
Dr. Giovanni Cicceri
Dr. Stefano Silvestri
Guest Editors
Manuscript Submission Information
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Keywords
- AIoT
- AI, ML, and DL
- IoT
- smart environment
- cyber-physical systems
- resource orchestration
- system resiliency, reliability and availability
- computing continuum
- edge computing
- edge/cloud systems
- security
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