Affiliations: [a]
Department of Physics, GC University, Lahore, Pakistan
| [b] Deparment of Computer Engineering, The University of Lahore, Lahore, Pakistan
| [c]
Department of Computer Science, Superior University, Lahore, Pakistan
Correspondence:
[*]
Corresponding author. Shahzadi Tayyaba, Deparment of Computer Engineering, the University of Lahore, Pakistan. E-mail: shahzadi.tayyaba@hotmail.com and Muhammad Waseem Ashraf, Department of Physics (Electronics), GC University, Lahore, Pakistan. E-mail: dr.waseem@gcu.edu.pk.
Abstract: IoT systems base devices are considered an excellent research domain owning to its expertise and applications in wide range of areas. IoT in health care domain is gaining attention due to its better access to the doctor and paramedical staff as well as sensor based studies which results in less man to man interacting and less fault in the data. The health care provider can easily access the vitals and various other medical parameters by even staying miles away from the patient. However, large amount of data transfer over various communication mediums results in more data traffic. This data transfer will require more power which will be utilized to transfer the data. To reduce this data traffic issues, an efficient method is used in this work in which only the data that is predominantly important to be send to the health care provider is send via the communication medium. Rule based fuzzy logic tool is used in this work for an elder patient having cardiac issues. Blood sugar (After eating), Blood pressues (systolic), Blood pressure (Diastolic) and cholesterol level are taken as the parameter that are examined for the patient and the medical treatment required is calculated. The rules are set on the basis of real time data and human knowledge. The results from the fuzzy logic interference shows that the health care provider will be alarmed using communication medium only when active or emergency medical treatment of the patient is required. A comparative study between the power utilized in normal data driven method and fuzzy method shows that the fuzzy method utilize 8 times less power than the normal method. The simulated and MAMDANI model calculated values shows less than 1% error which shows the accuracy of the work in health care domain.
Keywords: Fuzzy logic, healthcare system, Internet of Things
