Software Product Line for IoT Enabled Healthcare Applications
By Asad Abbas, Student Member IEEE, Isma Farah Siddiqui, Scott Uk-Jin Lee, Ali Kashif Bashir, Senior Member IEEE, Nawab Muhammad Faseeh Qureshi
IEEE Internet Initiative eNewsletter, September 2017
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A Software Product Line (SPL) is beneficial for the development of a family of software that shares common and variable features that increase the reusability of existing resources. Reusability of existing features makes it easier to modify and update the next generation of software applications. Health-based software applications require modifications and upgrades as technology advances exponentially. In the health sector, run time data processing and communication between multiple devices to exchange that data enhance the efficiency to care for patients.
The Internet of Things (IoT) is used to acquire and incorporate the sensory data in e-Healthcare architecture with software engineering applications. IoT-based software applications are needed to be upgraded with less time and cost and higher productivity according to environmental requirements, such as heat sensors at multiple branches (for indoor and outdoor patients) of hospitals. Feature modeling is the best paradigm to choose the feature requirements according to end-user specification. Feature models are tree type structures that consist of common and variable features (alternative, Optional, and OR groups) used to manage the core assets of SPL for high reusability of existing features which can affect low cost and time development of the software applications. The impact of feature modeling on IoT-based software applications is to increase the reusability of features and to exchange data that enhances the efficiency of patient care of basic clinical care functions, such as blood pressure monitoring.
Organizations adopt different approaches for the development of IoT applications, such as sequential approach that always starts the development from scratch for every IoT application which requires higher cost and time with quality challenges. Moreover, if minor changes are required or need to be updated then the complete application needs to be changed. Therefore, this approach is not suitable where applications are needed to be developed in less time and with lower budget, such as heat sensors for indoor and outdoor in e-Health.
Figure 1: e-Health IoT-based System
In our study, we have adopted SPL feature modeling for e-Healthcare IoT-based application to increase the reusability of features by handling variabilities, such as alternative (indoor, outdoor sensors), Optional and OR groups features. An e-Healthcare system consists of multiple layers of software, and sensors can be installed on IoT devices, gateway, or at the user interface to present data etc., as shown in Figure 1. However, we are considering the sensors variabilities (e.g., layer 1 of the IoT-based e-Healthcare system) with feature modeling. The software application of temperature sensors is different with respect to the environment on same sensor devices. Pulse Oximetry Sensors (SPO2) are used according to performance, quality, and cost savings to measure the pulse rate of diverse categories of patients, such as adults and children. Breathing sensors are used to measure the breathing effects on chest and stomach and are different for child and adult healthcare centers. Table 1 shows the different sensor types with different functionalities.
Table 1: e-Health Sensor types and Properties
For e-Healthcare systems, we consider three types of sensors for each sensing such as temperature sensor, SPO2 sensor, and breathing sensor. Table 1 shows the variabilities of sensors in different environments and attributes. To develop the software application of these sensors with the environmental selection, we adopted the SPL feature model at the architecture level to achieve high reusability. As per the definition of SPL, these sensors need to be operational with a software application that is called core asset development and for complete e-Healthcare system development, these core assets are reused in various products. Therefore, feature modeling is required to categorize the variabilities for each product development.
Figure 2 shows the feature model of e-Healthcare sensors where four variation points indicate the variabilities of products. During each application development, these variation points must be satisfied. If any variation point is violated, then application leads to failing at the end-user level. Variation point1 (Vp1) indicates that at least one sensor must be part of the e-Healthcare application, Vp2 indicates that only one temperature sensor can be used, Vp3 indicates that multiple SPO2 sensors can be used general healthcare center (e.g., for adults and kids) and, Vp4 indicates that only one breathing sensor can be used in each product derivation. The purpose of this study is to enhance the reusability of features of e-Healthcare systems with less cost, fast development, and up-gradation of existing systems.
Figure 2: e-Healthcare Sensor Feature Model
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Asad Abbas received his BS (Information Technology) degree from “University of the Punjab” Pakistan in 2011. He Joined MS-leading to PhD program in Department of Computer Science and Engineering in Hanyang University ERICA campus at Ansan, South Korea, funded by Higher Education Commission of Pakistan in 2014. His research interests include Software Product Line, Software Requirement Traceability and IoT Applications.
Isma Farah Siddiqui
Isma Farah Siddiqui received her B.E degree in Software Engineering from Mehran University of Engineering and Technology, Pakistan, in 2006 and M.E degree in Information Technology from Mehran University of Engineering and Technology, Pakistan, in 2008. Currently, she is working for her Ph.D. in Department of Computer Science and Engineering at Hanyang University ERICA, South Korea, funded by Higher Education Commission, Pakistan. Since 2006, she has been with the Department of Software Engineering at Mehran University of Engineering and Technology, where she is currently designated as Assistant Professor. Her research interests include Smart Environment, Semantic Web, IoT and Big Data.
Scott Uk-Jin Lee
Scott Uk-Jin Lee received his B.E degree in software engineering and Ph.D. degree in computer science from the University of Auckland, New Zealand. After the doctoral degree, he worked as post-doctoral research fellow at Commissariat à l'énergieatomique et aux énergies alternatives (CEA), France. Dr. Lee has been with the Department of Computer Science and Engineering, Hanyang University, South Korea since 2011. He is serving as the head of Department of Software for Emerging Technology major. He has served as editor, technical chair and committee member for several journals and conferences. He is also a member of the Korean Institute of Information Scientists and Engineers and the Korean Society of Computer and Information. His research interests include Software Engineering, Formal Methods, Web, and IoT.
Dr. Ali Kashif Bashir
Dr. Ali Kashif Bashir is an Associate Professor of Department of Science and Technology, University of the Faroe Islands, Faroe Islands, Denmark. In the past, he has held positions at Osaka University, Japan, Nara National College of Technology, Japan, National Fusion Research Institute, Korea, and Korea Electric Power Co. Ltd. He received his PhD in Computer Science from Korea University. He also is a research consultant on some international projects, a mentor for few bodies, an Editor of Journal of Computer Networks, IEEE Access, Science and Education Publishing. He has given many invited talks across the globe and has chaired conference sessions. He is a senior member of IEEE. He is serving as editor in chief of IEEE Internet Policy and IEEE Future Directions on Ethics and Policy in Technology Newsletters. His research interests include: cloud computing (NFV/SDN), network virtualization, IoT, network security, wireless networks, etc.
Nawab Muhammad Faseeh Qureshi
Nawab Muhammad Faseeh Qureshi received the B.E degree in Software Engineering in 2006 and M.E degree in Information Technology in 2013, both from Mehran University of Engineering and Technology, Pakistan. He completed his Ph.D. in Department of Computer Science and Engineering at Sungkyunkwan University, South Korea in 2017. Currently he is a researcher at Sungkyunkwan University, South korea. His research interests include Big Data platform, IoT and cloud computing.
Susan Hyon Parker
Susan Hyon Parker received her B.S in Computer Science from Robert Morris University. She received her engineering education jointly through Carnegie Mellon University and Massachusetts Institute of Technology. She is currently pursuing her PhD in Nanotechnology. Presently, she is a visiting student at Oxford University.
She has been an instructor with the Carnegie Mellon Open Learning Initiative since its inception in 2001. She is an active member of the IEEE Internet Initiative, IEEE Nanotechnology, IEEE Cybersecurity, IEEE Smart Grid Power & Energy Society. She has been a contributor to the IEEE ETAP Forum and Conferences and has been reviewing papers for the National Academy of Engineering - Engineer Girl Essay Contest.
Her research interests include Sensor and Ad hoc networks, Robotics, Artificial Intelligence, Cyber Physical Systems, Vehicular Communications, Graphene, Renewable Energy, IoT and Future Internet as well as Propulsion and Aerospace Systems.
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