A software development for medical with a multiple decision taking functionalities. (December 2022) - Aziz Butt, Shariq; Khalid, Abbas; Ali, Arshad
Abstract: Background: Smart devices including sensors and smartphones have grown exponentially during the past few years due to rapid growth in wireless sensor network (WSN) technology under IoT. In addition with smart city, concepts of smart traffic systems and smart health are also being developed. It enables remote connectivity of smart devices (i.e., mobiles, sensors) and medical smart software with the internet for monitoring. The availability of smart devices plays a remarkable role in the new era of mobile health (mHealth) monitoring. mHealth software is mostly used for humans who suffer from any chronic disease and need remote monitoring. In this case, such human needs smart medical software for careful monitoring from a distance due to their continuous movement and distance from any medical support. Existing Limitations: Nowadays, due to the frequent use and development of intelligent software for medical still, this domain has several limitations such as (i) not rescuing timely, (ii) no mechanism to assure that medical condition is abnormal or due to any other reason i.e. environmental effects, (iii) not a decision taking medical software for selection of multiple ontologies simultaneously, (iv) no acknowledgment process for enlisting the medical centers which can provide the medical facilities and (v) issues with assessing the environmental factors. These limitations make smart medical field less effective particularly for users who have severe situations. Proposed Solution: Therefore, this work has proposed a framework and developed medical software for humans. For the development of the software, we used the hardware including Arduino UNO board, for pulse values used a pulse sensor and for its connectivity with the mobile software used a Bluetooth module HC-05 module. Arduino and Android based software are linked via a Bluetooth module. Implementation: For testing the software, case studies are used with different scenarios. This study has revealed more valuable results in respect of human rescue and ensuring the severe condition of the human with current activities, examining the effects of the environmental factors on the health, preventing the system from false alert generation, and timely receiving of medical facilities. Conclusion: The developed software as per the suggested framework's features has overcome the mentioned challenges from remote monitoring. It potentially outperformed with easiness and in a better way towards smart health monitoring services.