Artificial Intelligence and IoT-Based Nurse Alert Systems for Real-Time Emergencies: A Review

Prof. Dr. Gabriel Makuei Deng Makuei
Corresponding Author
Dr. John Garang Memorial University of Science and Technology, South Sudan
Email: leek123deng@gmail.com

Abstract

Traditional methods of patient monitoring are largely manual and take time to record, report and alert when emergencies occur. Modern digital technologies – increasingly combining the Internet of Things (IoT) with artificial intelligence (AI) – can make these alert systems respond rapidly, efficiently and cost-effectively. This paper aimed to review various IoTbased nurse alert systems for real-time emergencies. Two research questions were framed to facilitate the selection of papers. They related to the various available IoT-based patient monitoring systems that can be used for nurse alerts, and the benefits and challenges encountered when implementing any of these systems in a given context. From Google Scholar, 25 papers suitable for answering the two research questions were selected based on defined inclusion and exclusion criteria. The papers identified from Google Scholar were repeatedly screened and selected using the PRISMA process. The search for papers was stopped when the target of 25 papers was achieved. The results of the review showed that, overall, there is sufficient support from the literature for answers to the two research questions. In answer to the first question, the literature provides several IoT-based nurse alert systems for implementation in different contexts, several of which incorporate AI and machine learning for prediction and decision support. Many benefits and challenges have also been reported in the literature in answer to the second research question. Some limitations of this review are mentioned at the end.

Keywords: artificial intelligence, IoT, cloud, patient monitoring, nurse alerts, real-time emergency