Remote Patient Monitoring (RPM) is an emerging technology paradigm that helps reduce clinician workload by automated monitoring and raising intelligent alarm signals. High sensitivity and intelligent data-processing algorithms used in RPM devices result in frequent false-positive alarms, resulting in alarm fatigue. This study aims to critically review the existing literature to identify the causes of these false-positive alarms and categorize the various interventions used in the literature to eliminate these causes. That act as a catalog and helps in false alarm reduction algorithm design. A step-by-step approach to building an effective alarm signal generator for clinical use has been proposed in this work. Second, the possible causes of false-positive alarms amongst RPM applications were analyzed from the literature. Third, a critical review has been done of the various interventions used in the literature depending on causes and classification based on four major approaches: clinical knowledge, physiological data, medical sensor devices, and clinical environments. A practical clinical alarm strategy could be developed by following our pentagon approach. The first phase of this approach emphasizes identifying the various causes for the high number of false-positive alarms. Future research will focus on developing a false alarm reduction method using data mining.

The Internet of Things (IoT) plays a key role in digital transformation. However, in many cases, organizations realize that they already have a large fleet of legacy IoT devices that have been gradually deployed over the years. Many of these devices may not have been designed with security in mind. One of the biggest concerns of IoT is managing the risks associated with a growing number of IoT devices. Information security and privacy issues related to IoT devices have attracted global attention, because of the ability of these devices to interact with the physical world.

The Internet of Things plays a key role in digital transformation. However, in many cases, organizations realize that they already have a large fleet of legacy IoT devices that have been gradually deployed over the years. Many of these devices may not have been designed with security in mind. One of the biggest concerns of IoT is managing the risks associated with a growing number of IoT devices. Information security and privacy issues related to IoT devices have attracted global attention; these devices have the ability to interact with the physical world.