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Integrating Smart Sensors and Artificial Intelligence Technologies for Human Healthcare Applications

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biomedical Sensors".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 801

Special Issue Editors


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Guest Editor
School of Information Technology, University of Cincinnati, Cincinnati, OH 45221, USA
Interests: network science; evolutionary computation; and artificial intelligence; including natural language processing; machine learning; deep learning; graph representation learning; swarm intelligence and big data analytics in support of smart services; cybersecurity; population health
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Information Technology, University of Cincinnati, Cincinnati, OH 45221, USA
Interests: cyber and strategic deterrence; flow of information and disinformation in irregular warfare; flow of cyberattacks and network resiliency in cyber warfare; flow of infectious diseases in biological warfare and resilience of supply chains
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Computing, Montclair State University, Montclair, NJ 07043, USA
Interests: disasters; disaster medicine; social medicine; resilient systems; biosecurity

Special Issue Information

Dear Colleagues,

This Special Issue, titled ‘Integrating Smart Sensors and Artificial Intelligence Technologies for Human Healthcare Applications’, seeks to explore the synergistic integration of the latest smart sensor systems and artificial intelligence (AI) technologies to modernize human healthcare. This Special Issue will focus on innovative research that leverages smart sensors to collect real-time health data and employ AI techniques such as machine learning, deep learning, natural language processing, predictive analytics and computer vision to classify and process health information to achieve early diagnosis and treatment. We welcome contributions to innovative approaches related to all aspects of smart healthcare for implementing these technologies in early disease detection and diagnosis, early intervention, personalized healthcare, disease prediction, human-centric disease management, and telemedicine and home healthcare. In addition, studies addressing the integration of AI with wearable sensors, internet-based health monitoring smart systems, healthcare robotics, and the inclusion of robots in the clinical and health sciences for enhancing health professionals’ decision-making and patient outcomes are also invited. Contributions can be original research, review articles, or case studies that emphasize the key roles of AI-driven sensors in improving the efficiency of healthcare services, their accuracy in determining anomalous physiological events, and the reduction in burden on clinical analysis findings.

Dr. Basheer Qolomany
Dr. Jacques Bou Abdo
Prof. Dr. Liaquat Hossain
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • smart sensors in healthcare
  • artificial intelligence in healthcare
  • predictive healthcare analytics
  • wearable health technologies
  • remote patient monitoring
  • personalized medicine

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Published Papers (1 paper)

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Research

18 pages, 1379 KiB  
Article
An Algorithm for Mining the Living Habits of Elderly People Living Alone Based on AIoT
by Jiaxuan Wu, Yuxin Lu and Yueqiu Jiang
Sensors 2025, 25(7), 2299; https://doi.org/10.3390/s25072299 - 4 Apr 2025
Viewed by 294
Abstract
With the global aging population on the rise, the health and safety of elderly individuals living alone have become increasingly critical. This study introduces a novel AIoT-based habit mining algorithm designed to enhance activity monitoring in smart home environments. The proposed method integrates [...] Read more.
With the global aging population on the rise, the health and safety of elderly individuals living alone have become increasingly critical. This study introduces a novel AIoT-based habit mining algorithm designed to enhance activity monitoring in smart home environments. The proposed method integrates a one-dimensional U-Net neural network for accurate behavioral classification and an FP-Growth-based temporal association rule analysis for uncovering meaningful living patterns. By leveraging environmental sensor data, the algorithm first classifies daily activities and then uses timestamps to detect time-sensitive dependencies in behavior sequences, identifying the long-term habits of the elderly. Experimental validation on CASAS datasets (ARUBA and MILAN) demonstrates superior performance, achieving a precision of 84.77%. Compared to traditional techniques, this approach excels in behavior recognition and habit mining, offering a precise and adaptive framework for AIoT-driven smart home safety and health monitoring systems. The results highlight its potential to improve the quality of life and safety for elderly individuals living alone. Full article
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