Dew computing-inspired health-meteorological factor analysis for early prediction of bronchial asthma

Abstract

Bronchial asthma is one of the most common chronic diseases of childhood and considered as a major health problem globally. The irregularity in meteorological factors has become a primary cause of health severity for the individuals suffering from asthma. In the presented research, a dew-cloud assisted cyber-physical system (CPS) is proposed to analyze the correlation between the meteorological and health parameters of the individuals. The work is primarily focused on determining the health adversity caused by the irregular scale of meteorological factors in real-time. IoT-assisted smart sensors are utilized to capture ubiquitous information from indoor environment that make a vital impact on the health of the individual directly or indirectly. The data is analyzed over the cyber-space to quantify the probable irregular health events by utilizing the data classification efficiency of Weighted-Naïve Bayes modeling technique. Moreover, the relationship between meteorological and health parameters is estimated by utilizing the Adaptive Neuro-Fuzzy Inference System (ANFIS) and calculate a unifying factor over the temporal scale. To validate the monitoring performance, the proposed model is implemented in the four schools of Jalandhar, India. The experimental evaluation of the proposed model acknowledges the performance efficiency through several statistical approaches. Furthermore, the comparative analysis is evaluated with state-of-the-art decision-making algorithms that demonstrate the effectiveness of the proposed solution for the targeted application.

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:

• To develop a novel dew computing-inspired real-time monitoring solution to analyze the impact of meteorological factors on the human body.

• To utilize the selected health and meteorological factors for the early identification of the risks on health of the individual suffering from bronchial asthma.

• To deliver the predictive outcomes with the cautioning alarms to the concerned caregivers and medical specialists for providing ideal assistive and medical care environment.

• 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.