AneezaDilawar

Work place: GC Woman University Sialkot / Department of Computer Science & Information Technology, Pakistan

E-mail: aneezadilawar786@gmail.com

Website:

Research Interests: Autonomic Computing, Computer Architecture and Organization, Computing Platform, Data Structures and Algorithms, Programming Language Theory

Biography

Aneeza Dilawar was born in Sialkot in 1998. She did her matriculation level in 2014 from, Quaid Public High School Sialkot in Computer Arts and her intermediate level (I.C.S) in 2016 from ILM college Sialkot. Now she is doing her BS (Hons) in Computer Science (CS) from GC WOMEN UNIVERSITY, Sialkot. Currently, she has been working on Research as final year project in Data Diversity inMedicalIoTtopic. Her main areas of research interest are Cloud Computing, and Programming Languages.

Author Articles
Managing Data Diversity on the Internet of Medical Things (IoMT)

By Iram Mehmood Sidra Anwar AneezaDilawar Isma zulfiqar Raja Manzar Abbas

DOI: https://doi.org/10.5815/ijitcs.2020.06.05, Pub. Date: 8 Dec. 2020

In the healthcare industry, the Internet of Medical  Services (IOMT) plays a vital role throughout the increasing performance, reliability, and efficiency of an electronic device. Healthcare is also characterized as being complicated due to its highly diverse and large number of shareholders. Data diversity refers to the continuum of various types of elements in the data. The integration of data is difficult where different sources can adopt different identification for the same entity, but there is no explicit connection. Researches are contributing to a digitized Health care system through interconnections available medical resources and health care services. This Research presents the contribution of IoT to people in the field of Healthcare, highlighting the issues in different data integration,  analysis of the existing algorithms and models, applications, and future challenges of IoT in terms of healthcare medical services. Big data analytics that incorporates millions of fragmented, organized, and unstructured sources of data will play a key role in how health care will be delivered in the future.

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