شماره ركورد كنفرانس :
5488
عنوان مقاله :
Management of Internet of Things Challenges in Healthcare Environment by development of Intuitionistic Fuzzy SWARA and Intuitionistic Fuzzy COPRAS
پديدآورندگان :
Danesh Shakib Masoumeh ms_danesh.shakib@yahoo.com Department of industrial management, college of management and accounting, Qazvin branch, Islamic Azad University, Qazvin, Iran , Pishdar Mahsa mahsa.pishdar@ut.ac.ir Industrial Management Department, Faculty of Management and Accounting, Allameh Tabataba’i University, Dehkadeh-ye-Olympic (Campus), Tehran, Irana
كليدواژه :
Internet of things , Intuitionistic Fuzzy SWARA , Intuitionistic Fuzzy COPRAS , Healthcare
عنوان كنفرانس :
اولين كنفرانس بين المللي مديريت و مهندسي كيفيت و قابليت اتكا
چكيده فارسي :
Consumers’ expectations about high performance, high volume, and lower price have been increased all without a compromise on quality, pushing them to put efforts in new technologies applications such as Internet of Things (IOT). Albeit, different challenges show off through this application and this is the point that most of the previous studies paid less attention to while just paying attention to the advantages of these technologies. To overcome this defect, a multiple attribute decision making (MADM) model is developed to rank the challenges of IOT in healthcare environment, using intuitionistic fuzzy step-wise weight assessment ratio analysis (SWARA) to weight the challenges. Based on this, intuitionistic fuzzy complex proportional assessment of alternatives (COPRAS) is proposed to rank and select the challenges that should receive the first priority of attention. Analysis shows that the scores of challenges are close to each other and this shows that all the challenges really matters in taking advantages of IOT application in healthcare system. However, Loss of Integrity of data and transformation receives the first rank among the challenges since if it’s dealt with correctly; most of the benefits mentioned in the paper are realized. The challenge with the least score relates to big data management, since when all the other challenges are faced properly, the background would be ready to manage big data and extract efficient information of it.