Secure IoT Analytics for Fast Deterioration Detection in Emergency Rooms

Abstract

IoT data analytics can potentially bring benefits to several critical application domains, especially in healthcare. In fact, especially in emergency rooms the detection of critical patients can be a critical task when the number of patients to be monitored is high with respect to the available medical personnel. However, it is also necessary to pay attention to ethics, privacy, and security issues, aiming to prevent attacks and unauthorized access to sensitive data of patients, guaranteeing the correct functioning of the system in a secure environment. To this end, this article presents a knowledge representation framework enabling the intelligent video surveillance of patients, which can be used in combination with IoT-based systems to enhance the detection of critical patients in emergency rooms, while dealing with ethics, privacy, and security issues. These are guaranteed by means of an event-based visual access control specification method, constraining the access to both devices and users. We also describe a clinical scenario related to the early treatment of sepsis in an emergency room, showing how the proposed framework can enhance the detection of such critical disease while guaranteeing ethics, privacy, and security.

Keywords

• IoT data analytics
• video surveillance
• role-based and event-based access control
• event modeling
• ICU
• knowledge representation