Back to Search
Start Over
Secure IoT Analytics for Fast Deterioration Detection in Emergency Rooms
- Source :
- IEEE Access, Vol 8, Pp 215343-215354 (2020)
- Publication Year :
- 2020
- Publisher :
- IEEE, 2020.
-
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.
- Subjects :
- Authentication
General Computer Science
Knowledge representation and reasoning
Event (computing)
Computer science
business.industry
knowledge representation
General Engineering
Access control
event modeling
Computer security
computer.software_genre
role-based and event-based access control
Task (project management)
IoT data analytics
Analytics
Health care
ICU
Task analysis
General Materials Science
video surveillance
lcsh:Electrical engineering. Electronics. Nuclear engineering
business
computer
lcsh:TK1-9971
Subjects
Details
- Language :
- English
- ISSN :
- 21693536
- Volume :
- 8
- Database :
- OpenAIRE
- Journal :
- IEEE Access
- Accession number :
- edsair.doi.dedup.....8ce83f7d81c462373f438d056e968291