Dew computing-inspired health-meteorological factor analysis for early prediction of bronchial asthma
Introduction
Effective administration of the patients is considered as a major issue of the smart healthcare domain (Comparative data about respiratory diseases). Bronchial Asthma (BA) is considered as one of the serious health issues and almost 18% of the population is suffering from the same (Global Initiative for Asthma, 2019). From the survey conducted by the Centers for Disease Control and Prevention (CDC), it is analyzed that BA is influencing around 8.3% of the populace (6.1 million individuals) under the age of 18 in the US. Moreover, the yearly budget of the US for dealing with this issue is around 3.2 billion dollars (Zahran et al., 2018; Weiss et al., 2000). The same ratio can be observed from the other nations as well. Even, it is termed as the third-ranking cause of childhood hospitalization and a leading reason for the absentee count in school (The Centers for Disease C, 2015). It is also expected that the effective control of teenage asthma is generally transient and it may develop into stable adult asthma later. Several previous experiments and examinations (D'amato et al., 2015; Newell and Swafford, 1963; da Silva et al., 2019; Hu et al., 2020; Yousif and Al Muhyi, 2019; Zhao et al., 2019; Tikkakoski et al., 2019; Eschenbacher et al., 1992; Deng et al., 2020) have revealed the relationship between the meteorological factors such as humidity, temperature, wind speed, barometric pressure and the epidemiology of asthma in children. The analysts in Spain and America (Hervás et al., 2015; Jayawardene et al., 2013) have also designed several artificial models to evaluate the impact of meteorological factors on the health.
Meteorological factors such as air pollution, tobacco smog, allergies, and airway infections are considered as the most common factors in the eminent of pediatric asthma exacerbations (Mendez and Van den Hof, 2013). The correlation between an individual's physiological responses and the measurement of exposure metrics is also considered as a significant shortcoming in the determination of the cause of asthma (Xu et al., 2018; Rodopoulou et al., 2015; Alhanti et al., 2016). Relationship between the asthma morbidity and meteorological factors are evident to an extent, however, not clearly defined. Amongst meteorological factors, the temperature is considered as one of the most primary factors in time-series studies. After reviewing several proposed studies, it is considered that the solutions for the determination of the health adversity by evaluating the relationship between meteorological and health parameters are limited.
The data acquisition and processing efficiency of the Internet of Things (IoT) can provide an effective solution for the above-discussed issue. Several IoT-cloud based real-time monitoring solutions (Thakar and Pandya, 2017; He et al., 2012) have been developed (He et al., 2012). Though multiple real-time solutions are being developed, the data heterogeneity is considered as the most challenging issue in these solutions. These underlying reasons cause transmission delay and communication overhead (He et al., 2012). To deal with these issues, the dew computing-inspired (Ray, 2017) framework is proposed that helps to maintain scalability. Moreover, dew computing platform provides flexibility, interoperability, and usability. The data processing efficiency of dew computing not only provides the ability to store and retrieve the health information from the cloud, but It also helps the system to process the data in the case of the unavailability of internet connectivity (Rindos and Wang, 2016). In this manner, effective data computation with instant decision-making capability with lesser resource utilization is the most considerable advantages of dew computing over fog computing.
By considering the advantages of dew computing and cyber-physical platform, a dew computing-inspired real-time monitoring framework is proposed for the early prediction of the symptoms of bronchial asthma. The underlying motive behind this proposed study is to explore the correlation among daily variations in meteorological factors such as average humidity, air quality index, and daily average temperature, with the health factors such as heart rate, respiration rate, and muscle tightness. The conceptual architecture of the proposed framework is illustrated in Fig. 1 that is intended for achieving the following objectives:
- 1.
To develop a novel dew computing-inspired real-time monitoring solution to analyze the impact of meteorological factors on the human body.
- 2.
To utilize the selected health and meteorological factors for the early identification of the risks on health of the individual suffering from bronchial asthma.
- 3.
To deliver the predictive outcomes with the cautioning alarms to the concerned caregivers and medical specialists for providing ideal assistive and medical care environment.
- 4.
To ensure data privacy with respect to the sensitive information of the individual under monitoring.
The article structure is organized as follows: Section 2 investigates some of the imperative proposed studies related to the domain of environment and health monitoring. Section 3 provides the complete detail of the proposed cyber-physical system for real-time health assessment. Section 4 explains the experimental setup of the proposed system with performance evaluation. Finally, the conclusive remarks with possible future aspects are provided in Section 5.
Section snippets
Related work
As the capability of data processing makes IoT and dew computing more demanding, it helps to reduce the rate of latency by increasing the response rate. This section provides insight by discussing some imperative work in the domain of IoT-based health and environment monitoring.
Proposed system
The proposed approach is broadly divided into physical and cyber space as presented in Fig. 2. The complete working process of the proposed CPS is as follows:
Performance evaluation
The experimental setup of the proposed framework with its performance is evaluated in this section by segmenting into five subsections. Each subsection related to the experimental evaluation is discussed as follows:
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Data collection
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Irregular event classification analysis
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Health-Meteorological relationship analysis
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Real-time alert-based decision-making efficiency
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Overall performance analysis
Conclusion and future scope
The tri-logical technology of IoT-dew-cloud has been able to offer various types of assistance in the medicinal services industry. In this study, dew-cloud inspired cyber physical system is proposed for evaluating the effect of meteorological factors on the health of the individuals experiencing bronchial asthma. All the aspects of health monitoring and early cause prediction of bronchial asthma are organized in the proposed intelligent healthcare system. The framework utilizes dew computing
Ethical approval
All the performed procedures in the study involving human participation were strictly in accordance with the ethical standards of institution and or national research committee together with 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Credit author statement
Ankush Manocha: Conceptualization, Methodology, Software. Munish Bhatia.: Data curation, Writing – original draft preparation. Gulshan Kumar.: Formal analysis, Investigation, Supervision.
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
ANKUSH MANOCHA received the Ph.D. degree in computer science from Lovely Professional University (L.P.U.), Punjab, India. He is currently working as an Assistant Professor with the School of Computer Applications, L.P.U. He has published research papers in reputed journals like ELSEVIER, SPRINGER, and IEEE. His current research interests include cyber physical systems, edge, fog and cloud computing.
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ANKUSH MANOCHA received the Ph.D. degree in computer science from Lovely Professional University (L.P.U.), Punjab, India. He is currently working as an Assistant Professor with the School of Computer Applications, L.P.U. He has published research papers in reputed journals like ELSEVIER, SPRINGER, and IEEE. His current research interests include cyber physical systems, edge, fog and cloud computing.
MUNISH BHATIA is working as Assistant Professor in CSE Department of LPU, Punjab, India. Previously he worked as Project Researcher at IIT Mandi. He has published research papers in reputed journals like ACM, ELSEVIER, SPRINGER, IEEE, WILEY, IOS.
GULSHAN KUMAR (Member, IEEE) received the Ph.D. degree in computer science from Lovely Professional University (L.P.U.), Punjab, India. He is currently working as an Assistant Dean and an Associate Professor with the Division of Research and Development, L.P.U. He has authored and coauthored more than 35 research articles including international journals (IEEE INTERNET OF THINGS JOURNAL, IEEE ACCESS, the IEEE SENSORS JOURNAL, and IJDSN) and conferences. His current research interests include cyber physical systems, blockchain, edge, and cloud computing. He is a member of various technical organizations, such as ISCA and so on.