Khazar University

19 May, 2022Article co-authored by Department Coordinator in “Materials Today: Proceedings”

28 March, 2022The chapter co-authored by the department head is in a book by Springer Publishing

18 Feb, 2022Article by Khazar University Staff Members in the Collection of “V-INTERNATIONAL EUROPEAN CONFERENCEON INTERDISCIPLINARY SCIENTIFIC RESEARCH”

17 Feb, 2022Article by Khazar University Staff Members in the Collection of “7th International Zeugma Scientific Conference”

16 Feb, 2022An article co-authored by the department head in BMC Veterinary Research

28 Jan, 2022Article by Faculty Member of Languages and Literature Department in "Folklore/Literature" Journal

28 Jan, 2022Article by Faculty Member of Languages and Literature Department in “Uluslararası Halkbilim Araştırmaları Dergisi” (International Journal of Folklore Studies)

13 Jan, 2022Article by Khazar University staff members in “Lecture notes in Network and systems”

20 Dec, 2021An article co-authored by Faculty Dean and MBA graduate was published in the book titled "Universities, Entrepreneurial Ecosystems, and Sustainability"

08 Dec, 2021A scholarly article by the Department of Economics and Management published in Emerging Science Journal

Article by Khazar University scholar published in International Scientific Journal

An article entitled “Event-driven IoT architecture for data analysis of reliable healthcare application using complex event processing”, authored by Dr. Amir Rahmani, Professor of Computer Science at Khazar University was published in Cluster computing, an ISI-indexed journal from Springer collection.

Internet of Things (IoT) is enhancing the intelligence of the societies through a rapid transition to a smarter, automatic, responsive world due to the dramatic increase in the number of sensors deployed around the world. Complex Event Processing (CEP) is a data stream tracking method used to extract the meaningful data obtained from the network results in real-time decision making. In this paper, an event-driven IoT architecture is presented for data analysis of reliable healthcare applications, including context, event, and service layers. Dependability parameters are considered in each layer, and the CEP method as a novel solution and automated intelligence is applied in the event layer. Implementation results showed that the CEP method increased reliability, reduced costs, and improved healthcare quality.

The article can be found at this link:

https://link.springer.com/article/10.1007/s10586-020-03189-w