Citation

Zaw, Thein Oak Kyaw (2024) Design science approach towards the development of a Bluetooth low energy contact and smart tracing index. PhD thesis, Multimedia University.

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Abstract

The human race has penetrated into the smart healthcare period where it is a buildup from the substance of smart city towards making solutions in the healthcare to be smart. Although there are significant progress in the smart healthcare solutions, large number of countries including Malaysia, were caught off guard for smart contact tracing solutions in managing the Covid-19 pandemic. Even though four main contact tracing solutions were developed and implemented nationwide, there is still no solution yet to made available for the front liners in preventing human-tohuman Covid-19 infection. Thus, this study serves as an applied research in providing closure to the real-life problem stated. It is accomplished by the development of Bluetooth Low Energy (BLE) Internet of Things (IOT) digital surveillance contact tracer that utilizes low calibrated transmission power (Tx) and signal captures. Addition to that, an exploratory research in developing smart contact tracing index which is non-existent at the moment, was conducted as well. Development of the solution artefact utilizes design science methodology adopting normative theory, TOGAF framework and interviews of stakeholders as its foundation. As for the analysis for close contact tracing, confusion matrix along with a developed algorithm were utilized. While for the development of smart contact tracing index, systematic literature review (SLR) combined with Delphi methodology were used together applying weighted average method for the weights’ calculation. Results have shown that for proof of concept (POC), the approach has an accuracy of 88.46% was for two users, 75% accuracy for five users and 80% accuracy for nine users. While for the pilot test, 95% accuracy was obtained for true positives for five users experiment in a law firm and 100% accuracy for true positives for nine users in a university hall room. Similar accuracy for true positives of 100% were also observed in house setting experiment of five and nine users. As for the testing of the limit for the artefact, it has 80% accuracy for true negatives for fifteen users and 92.31% accuracy for true negative for twenty users. Last but not least, experiment in a private hospital for five days towards total of twenty people was at 100% accuracy for close contact identification (CCI). As for smart contact tracing index, a total of 28 items were obtained separated into five segments.

Item Type:	Thesis (PhD)
Additional Information:	Call No.: R859.7.I59 T44 2024
Uncontrolled Keywords:	Internet of things—Medical applications
Subjects:	R Medicine > R Medicine (General) > R858-859.7 Computer applications to medicine. Medical informatics
Divisions:	Faculty of Management (FOM)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	02 Oct 2025 01:51
Last Modified:	02 Oct 2025 01:51
URII:	http://shdl.mmu.edu.my/id/eprint/14656

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