Innovative Systems and Solution in Healthcare Based on AI, Blockchain and IoT

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: 15 August 2025 | Viewed by 1016

Special Issue Editors


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Guest Editor
Department of Economics, Engineering, Society and Business Organization (DEIM), University of Tuscia, 01100 Viterbo, Italy
Interests: artificial intelligence; machine learning; neural networks; photogrammetry; digital elevation models; blockchain; anomaly detection; computer vision; healthcare; education
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Information Engineering (DII), Polytechnic University of Marche, 60131 Ancona, Italy
Interests: social network analysis; machine learning; blockchains; IoT
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The rapid advancement of emerging technologies such as Artificial Intelligence (AI), Blockchain, and the Internet of Things (IoT) is revolutionizing the healthcare sector. These transformative technologies offer unparalleled opportunities to enhance patient care, improve experts’ decisions, streamline operations, acquire and manage medical data, and analyse streams of information. Several studies, but also practical applications, have already shown the great potential of their (joint) use and paved the way to extremely interesting and promising innovations.

Artificial Intelligence has already demonstrated its potential in a wide variety of tasks that range from enhancing diagnostic accuracy and personalizing treatment plans to predicting patient outcomes with unprecedented precision. From machine learning algorithms that analyze complex datasets to natural language processing tools that interpret clinical notes, AI is constantly redefining how healthcare professionals approach challenges in medicine.

Blockchain technology, with its inherent characteristics of transparency, security, and immutability is capable of enabling the secure sharing of sensitive patient information, promoting trust in healthcare transactions, and fostering interoperability among disparate systems. Blockchain’s ability to facilitate decentralized and tamper-proof data management is particularly critical in addressing privacy concerns and compliance with regulatory standards.

The Internet of Things is empowering healthcare providers to collect real-time data through interconnected devices. Wearable health monitors and smart medical equipment are just some of the IoT-based devices that ensure continuous patient monitoring and the early detection of health anomalies. In addition, integrating IoT with AI and Blockchain creates an ecosystem that can deliver intelligent, scalable, and patient-centric solutions.

This Special Issue aims to explore the state of the art of AI, blockchain, and IoT developments while also examining the practical applications and main implications within the healthcare sector.

Topics of interest include but are not limited to:

  • AI-driven diagnostics and treatment recommendations;
  • Analysis of complex medical dataset;
  • Processing and interpreting clinical diagnosis and notes;
  • Blockchain-based solutions for secure and interoperable health data exchange;
  • Patient data privacy and consent management;
  • Decentralized healthcare systems and telemedicine solutions;
  • IoT-enabled remote patient monitoring;
  • Smart healthcare systems;
  • Integration of AI, Blockchain, and IoT for holistic healthcare solutions;
  • Ethical and regulatory implications in adopting these technologies in the medical sector.

Submissions should provide innovative insights into how AI, blockchain, and IoT (separately and in synergy) can address existing challenges in healthcare, highlight real-world implementations or theoretical advancements, and propose future directions for research and practices. This Special Issue also intends to foster interdisciplinary dialogue and collaboration among researchers, practitioners, and policymakers, driving a broader and yet thoughtful adoption and evolution of these technologies within the healthcare landscape.

Dr. Andrea Zingoni
Dr. Gianluca Bonifazi
Guest Editors

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Keywords

  • blockchain
  • healthcare
  • managing
  • data security
  • data privacy
  • transparency
  • IoT
  • decentralized systems
  • telemedicine
  • smart contracts

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Published Papers (1 paper)

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Research

22 pages, 7409 KiB  
Article
Integrated Low Cost, LoRa-Based, Real Time Fluid Infusion Flask Monitoring System
by Spyridon Mitropoulos, Dimitrios Rimpas, Stylianos Katsoulis, George Hloupis and Ioannis Christakis
Electronics 2025, 14(5), 869; https://doi.org/10.3390/electronics14050869 - 22 Feb 2025
Viewed by 743
Abstract
Manual intravenous (IV) monitoring delays, put patients at risk, as the reaction time of nursing staff can be critical to the patient’s health. The widespread use of LoRa networks today is a reality. The deployment of devices and applications based on LoRa networks [...] Read more.
Manual intravenous (IV) monitoring delays, put patients at risk, as the reaction time of nursing staff can be critical to the patient’s health. The widespread use of LoRa networks today is a reality. The deployment of devices and applications based on LoRa networks in healthcare environments, such as hospital facilities, is of great interest and can offer both time savings for medical and nursing staff and improvements in medical care. In this work an integrated low-cost, real-time monitoring system for fluid infusion based on a LoRa network is presented. The measured (monitoring) data are the weight of the fluid infusion flask and the number of fluid drops. The design of the system and the affordability of the materials (low-cost devices) give the possibility for immediate application in healthcare environments. As the system consists of low-cost sensors, and given that it is intended for health purposes, extensive research has been carried out on the evaluation and reliability of the measurements. The proposed system is intended for medical care; in this sense it should have the lowest possible measurement error. The evaluation of the system has revealed a polynomial equation as a corrective factor for weight and shows an improvement of the error from 2% of the raw measurements to 0.6% of the corrected measurements, while regarding the calculation of the weight from the measurement of the droplets, it shows an error of 1.6%. The proposed system contributes directly to both the valuable time of the medical staff and the improvement of patient care. The evolution of technology should be applied to the health sector and low-cost and internet of things (IoT) devices can be applied to healthcare after thorough evaluation and calibration procedures. Full article
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