AI and Fusion Methods for Urban and Medical Sensing
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".
Deadline for manuscript submissions: 30 November 2026 | Viewed by 260
Special Issue Editor
Special Issue Information
Dear Colleagues,
Recent advances in sensing technologies have generated unprecedented volumes of heterogeneous data across urban environments and medical systems. However, the full value of these data streams can only be realized through intelligent processing, integration, and interpretation. This Special Issue focuses on Artificial Intelligence (AI) and data fusion methods that enhance the reliability, accuracy, and decision-making capabilities of urban and medical sensing systems.
We invite original research and review articles that address novel AI-driven algorithms, sensor fusion frameworks, and data-centric methodologies for multi-modal sensing.
Topics of interest include, but are not limited to, deep learning, Bayesian inference, probabilistic fusion, edge and cloud-based intelligence, and real-time analytics applied to smart cities, environmental monitoring, healthcare diagnostics, wearable sensing, and biomedical signal processing.
Emphasis is placed on solutions that improve robustness under uncertainty, compensate for sensor limitations, and support scalable deployment in real-world conditions. By bridging urban and medical sensing domains, this Special Issue aims to foster cross-disciplinary innovation, promote transferable AI methodologies, and highlight practical implementations that contribute to safer cities, improved public health, and more efficient healthcare systems.
Dr. Faizan Ullah
Guest Editor
Manuscript Submission Information
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Keywords
- artificial intelligence
- sensor fusion
- multi-modal sensing
- smart cities
- medical and biomedical sensing
- deep learning
- bayesian inference
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