Use Of Mobile Devices Research Articles

The Integration and Utilization of Mobile Application in Healthcare Consultation Services for Quirino Province

The use of mobile devices has been rapidly increasing because of its versatile and useful applications. As a result, its high-tech features and Users have ready-made and customizable alternatives thanks to open source platforms., making it particularly helpful for healthcare services at any time and from any location. Healthcare services for the rural areas are limited since hospitals are also limited and their location is also one of the problems in availing healthcare service in the province. The main objective of this study focuses on the integration and utilization of mobile application as an alternative solution for healthcare consultation services. The descriptive and survey method was used in the data gathered from the respondents which comprised a number of people from the six municipalities of the province specifically rural areas. A questionnaire-checklist was administered to determine the possibility of the integration of mobile application for healthcare consultation services. Statistical Package for the Social Sciences (SPSS) a statistical tool used to determine the number of interested respondents to avail such mobile platform and to determined economic aspect of the study. The study proves that there is a possibility for the integration of mobile application as an online platform for healthcare consultation services. This will be beneficial to Quirinians and nearby provinces.

Pattern of Mobile Phone Use in Children Diagnosed with Neuro-Developmental Disorders: A Retrospective Cross Sectional Study

Background: Digital technologies including mobile phone device have progressively become an integral part of the life of children and adolescents for communication as well as learning and playing. According to some authors, the use of mobile device constitutes a “passive” behavior or one-way communication, which takes the child away from other more useful learning processes.Objectives: To evaluate the pattern of mobile device use in children with Neurodevelopmental disorders in Bangladesh.Methods: This retrospective cross sectional type of study was conducted at Department of Paediatric Neurology, Bangabandhu Sheikh Mujib Medical University (BSMMU) from November 2022 to April 2023. Children aged 1-5 year with neurodevelopmental disorders eg; ASD, ADHD, Isolated speech delay, Epilepsy, GDD were selected and enrolled in this study. Then children were assessed thoroughly by taking detailed history and physical examination. Neurodevelopmental assessment was done by Rapid Neurodevelopmental Assessment (RNDA). In confirmed cases, parents were asked retrogradely regarding the pattern of use mobile phone of their child. Data were collected in pre-designed structured questionnaire after taking approval of Institutional review board. An informed written consent was taken from the parents or the legal guardians.Results: Total 100 children were included. Male were outnumbered (71%) than female. Isolated speech delay was the commonest neurodevelopmental disorder (33%) followed by ASD. Average screen used time were about 3-5 hours of one-third children (38%). Majority of the parents (42.4%) were involved in their household work at the time of mobile use. More than half of the children (57.8%) use mobile phone for watching cartoon. About 50% parents believe that mobile phone having decremental effect on child’s brain development. Maternal mobile was the prime source (65.5%) for using mobile device. Conclusion: Isolated speech delay was the most commonly encountered neurodevelopmental disorder in this study. Average screen used time were about 3-5 hours for one-third studied children. More than half of the neurodevelopmental disordered children use mobile phone for watching cartoon. About half of the parents belief that mobile device have definite decremental effects on child’s brain development.

Association between the Hopkins Falls grading scale and motor function tests in patients with multiple sclerosis.

One of the main complications of multiple sclerosis (MS) is imbalance and walking problems that can lead to falls. This study investigated the association between a fall measurement scale called the Hopkins Falls Grading Scale (HFGS) and motor function tests in patients with MS. This cross sectional study was conducted using convenience sampling on 85 patients referred to the MS Association of Mashhad, Iran, in 2023. The HFGS examined falls during the past year and divided them into 4 degrees, and the function test included the timed 25 foot walk (T25FW) test and the timed up and go (TUG) test. Kruskal-Wallis test and Spearman's correlation coefficient were used for data analysis. A statistically significant association was obtained between HFGS and functional tests (T25FW and TUG) (for both P < 0.0001). A significant association was observed between the variables of age (P = 0.006), duration of the disease (P = 0.03), the use of mobility devices (P = 0.05), and HFGS. Considering the association between HFGS and motor function tests in MS patients, clinical experts should pay attention to patients who have slower movement and evaluate them in terms of falling status when performing motor function tests.

Characteristics of the mobile problem based learning flipped classroom (mPBLFC) mathematics learning model: a systematic literature review

The problem and the aim of the study. The mPBLFC model combines elements of problem-based learning (PBL) and the flipped classroom, incorporating the use of mobile devices. Problems arise in developing the mPBLFC model, including the combination of PBL steps into a flipped classroom and the integration of mobile technology. This research aims to provide relevant references to serve as a guide for developing the mPBLFC model, specifically designed for mathematics learning. The objective of this study is to scrutinize the attributes of the mPBLFC learning model through a comprehensive literature review. Research methods. This research, conducted through a comprehensive literature review using the PRISMA method, investigates 46 selected articles that have passed through identification (1,000 papers), screening (247 papers), eligibility (90 papers), and inclusion stages (46 papers). These 46 articles provide a general description of the year of publication, research geography, research object, research subject, and the developed model. After obtaining a general overview of the articles, a more in-depth review is conducted regarding the various components of the learning models they have developed. Subsequently, the mPBLFC model is synthesized and can be implemented in mathematics learning. Results. An overview of articles reviewed from 2017–2023 based on geography reveals the following distribution: Southeast Asia (37.14% of the reviewed articles), East Asia (25.71%), the United States (2.86%), West Asia (11.43%), Australia (5.71%), and Europe (5.71%). The distribution of articles based on research objects indicates a focus on mathematics (26%), science (17%), social (7%), and other (50%). Furthermore, articles are distributed based on research subjects across elementary school/SD (6%), middle school/SMP (15%), high school (SMA)/vocational school (SMK) (33%), and higher education/PT (46%).The mPBLFC model is an innovative blend of mobile PBL techniques, incorporating learning activities both before, during, and after classes, all facilitated through mobile devices. The integral components of the learning model encompass (a) learning syntax, (b) support systems, (c) social systems, (d) the reaction principle, and (e) learning effects. Conclusion. These characteristics encompass (a) a targeted focus on mathematics education with the aim of enhancing high school students' critical, computational, and creative thinking skills; (b) a structured approach involving preclass, in-class, and out-of-class learning activities; (c) a fundamental principle emphasizing students' ability to gather, share, and explore various problem-solving strategies while comprehending the steps to solve problems; (d) preclass activities that encompass problem orientation, understanding key concepts, and exploring a variety of problem-solving resources, allowing students to engage independently with diverse learning materials; (e) classroom activities that include discussions, experiments, problem-solving sessions, collaborative information sharing, and presentations, with the teacher transitioning from facilitator and mentor preclass to guide and support students' activities in class; and (f) a positive impact on students, fostering their drive to seek, share, and apply various information while enhancing their problem-solving skills.

Different smartphone tasks and traffic complexity affect pedestrian awareness of co-existing road objects and cerebral oxygenation during shared space walking

Distraction, primarily owing to the widespread use of cell phones and mobile devices while walking, is a contributing factor to pedestrian injuries. Pedestrians distracted by smartphones exhibit decreased situational awareness, influenced by the nature of concurrent tasks. However, little is known about the neural correlations between smartphone use and pedestrian responses to safety–critical events in a walking environment. This study recruited 30 young adults to investigate pedestrians’ ability to selectively respond to road objects while using smartphones (texting and reading) while walking in an immersive virtual environment system. The level of traffic complexity for the road conditions was manipulated by varying the number of safety–critical road objects coexisting in the environment at any given time and the number of required responses to the number of objects. During each 7-min task condition, cerebral oxygenation was measured using functional near-infrared spectroscopy. Furthermore, smartphone task performance, response times to road objects, and perceived workload were also measured. The participants exhibited reduced texting speed and reading performance when responding sequentially to coexisting road objects. Compared with other road conditions, those requiring two responses to four objects resulted in an increased workload and longer object response times. Participants perceived a higher workload in conditions involving tasks with smartphones than those without smartphones. More importantly, increased concentrations of oxygenated hemoglobin in the prefrontal cortex were observed when participants were concurrently performing smartphone and pedestrian tasks. Compared to smartphone reading, smartphone texting induced greater cerebral oxygenation in the bilateral frontopolar cortex. These results suggest that continuously texting while walking may demand additional cognitive resources for executive function. The findings of this study represent an initial step towards elucidating the cognitive mechanisms underlying attentional impairments experienced during smartphone distraction and working towards a viable solution to mitigate pedestrian risk.

The Effect of Mobile Technology on Vocabulary Development of English Language Learners: A Case Study of A2 Adult Learners

In today's digital age, technology can provide many opportunities for language learners, and the widespread use of mobile devices may be a viable solution to their challenges. This study aimed to determine the effectiveness of Mobile Assisted Vocabulary Application (MAVA) in developing language learners’ vocabulary knowledge and their attitudes towards the vocabulary extension activities. To reach these aims a quasi-experimental study was followed with the data collected through pre-post tests and semi-structured interviews. The researcher designed vocabulary extension activities in two distinct formats to allow learners to practice the newly acquired vocabulary items as extracurricular tasks. The experimental group completed vocabulary extension activities on their mobile devices while the control group completed similar tasks using pen and paper. Pre- and post-tests were administered to both groups to assess their vocabulary knowledge before and after the intervention. The results indicated that there was no significant difference between the two groups in terms of achievement. The students from both groups exhibited relatively higher results on the post-test. Upon analysing the individual subsections of the pre-test and post-test, it became apparent that students in the experimental group displayed relatively higher scores in the reading and pronunciation subsections of the post-test, whereas the control group exhibited higher scores only in the reading subsection. It can be posited that the MAVA had a more positive effect on the students’ abilities to pronounce them correctly, in contrast to the effects observed with vocabulary worksheets. A semi-structured interview was conducted to determine the attitudes of the learners in experimental group towards MAVA. Qualitative data from the interview suggested that MAVA had superior features by allowing the learners to use it at their convenience and ubiquitously acquire new vocabulary items.

Impact of Levels of Perceived Stress Among Senior Nursing Undergraduates in Clinical Practice on Mobile Addiction: A Cross-Sectional Study

This cross-sectional study aimed to explore the relationship between levels of perceived stress by senior nursing undergraduates during clinical training and the extent of mobile addiction. The study was carried out at the nursing faculty, aligning with the tenets of the Helsinki Declaration and STROBE writing standards. Ninety-eight senior nursing undergraduate students participated in the research. Data collection involved the use of a "Descriptive Characteristics Information Form," the "Perceived Stress Scale for Nursing Students," and the "Mobile Addiction Scale." SPSS 24.0 was used to analyse the data. Among the participants, 62.9% (n=61) were female, with a mean age of 22.41±2.58 years. While 83% (n=83) expressed satisfaction with their department, 52.6% (n=51) reported frequent mobile device use, primarily for social media. On average, students spent 4.56±2.12 hours daily on mobile devices. The mean score for perceived stress was 66.51±22.32, and for mobile addiction, it was 67.72±20.34. The perceived stress level accounted for 12% of the variance in mobile addiction. The study revealed a significant impact of stress experienced during clinical practice on mobile addiction among senior nursing undergraduates. It reveals the significance of providing stress management training to improve students' coping mechanisms and increase their awareness of mobile addiction.

Gait Features in Different Environments Contributing to Participation in Outdoor Activities in Old Age (GaitAge): Protocol for an Observational Cross-Sectional Study.

The ability to walk is a key issue for independent old age. Optimizing older peoples' opportunities for an autonomous and active life and reducing health disparities requires a better understanding of how to support independent mobility in older people. With increasing age, changes in gait parameters such as step length and cadence are common and have been shown to increase the risk of mobility decline. However, gait assessments are typically based on laboratory measures, even though walking in a laboratory environment may be significantly different from walking in outdoor environments. This project will study alterations in biomechanical features of gait by comparing walking on a treadmill in a laboratory, level outdoor, and hilly outdoor environments. In addition, we will study the possible contribution of changes in gait between these environments to outdoor mobility among older people. Participants of the study were recruited through senior organizations of Central Finland and the University of the Third Age, Jyväskylä. Inclusion criteria were community-dwelling, aged 70 years and older, able to walk at least 1 km without assistive devices, able to communicate, and living in central Finland. Exclusion criteria were the use of mobility devices, severe sensory deficit (vision and hearing), memory impairment (Mini-Mental State Examination ≤23), and neurological conditions (eg, stroke, Parkinson disease, and multiple sclerosis). The study protocol included 2 research visits. First, indoor measurements were conducted, including interviews (participation, health, and demographics), physical performance tests (short physical performance battery and Timed Up and Go), and motion analysis on a treadmill in the laboratory (3D Vicon and next-generation inertial measurement units [NGIMUs]). Second, outdoor walking tests were conducted, including walking on level (sports track) and hilly (uphill and downhill) terrain, while movement was monitored via NGIMUs, pressure insoles, heart rate, and video data. A total of 40 people (n=26, 65% women; mean age 76.3, SD 5.45 years) met the inclusion criteria and took part in the study. Data collection took place between May and September 2022. The first result is expected to be published in the spring of 2024. This multidisciplinary study will provide new scientific knowledge about how gait biomechanics are altered in varied environments, and how this influences opportunities to participate in outdoor activities for older people. RR1-10.2196/52898.

Neck pain among russian students

Objective. This study aims to analyze the prevalence and developmental factors of neck pain among students of Russian higher education institutions, with an emphasis on the impact of this pain on quality of life, academic activities, and overall well-being of students.Materials and Methods. The study is based on data obtained from 780 students through a survey conducted on the Google Forms platform. Descriptive statistics and correlational analysis methods were applied, utilizing SPSS software for data processing.Results. A high prevalence of neck pain among students (75.4 %) was identified. The analysis revealed a connection between neck pain and various aspects of life, including physical activity, stress, the use of mobile devices, and levels of physical activity. A correlation between neck pain and the psychosocial health of students was also established, particularly with anxiety and depression.Conclusions. The study underscores the necessity of a comprehensive approach in the prevention and treatment of neck pain among students. The development of programs aimed at improving the physical and psychological health of students is recommended, including exercises for neck and back, lifestyle modification, and psychological support.

Recent advances of ECG monitoring and webserver health monitoring applications: A review

In response to recent improvements in mobile technology and cloud computing-based real-time monitoring systems, numerous cloud-based healthcare services and devices have been developed. In the cloud system, it is feasible to collect and distribute medical data immediately from anywhere to medical specialists, and patients can receive network-based feedback. This paper reviews the most recent developments and trends in wearable technology and biomedical equipment (mostly ECG), as well as the development of a cloud-based solution for mobile device and web browser users. The system contains ECG enhancement, ECG quality grading, and ECG parameter extraction methods. A use case was utilized to showcase the system, in which a web server processed ECG data from a mobile phone in real-time. The system has been proved to be functional, accurate, and efficient. We review the primary principles underlying the operation of the ECG and its fundamental operation, as well as the recording and transmission paradigm for ECG signals. Detailed processes were also provided for the system components, their configuration, and the employed technologies. In conclusion, we examine the complete study and the project's future scope.

Deep improved bidirectional long short‐term memory‐based antenna selection for multiple input multiple output software defined radio system

SummaryMultiple input multiple output (MIMO) constitutes a wireless approach that employs several senders and receivers in order to send numerous data at once. Due to the rapid increase of cellular mobile device usage and the limitation of computing power, antenna selection (AS) has attracted more and more attention recently. AS can keep a balance between communication performance and computational complexity. In this paper, a novel deep learning (DL)‐based AS for MIMO software defined radio (SDR) system is proposed. The main objective of this work is to select the optimal antennas in MIMO systems to balance the efficiency of communication and maximize the secrecy capacity in massive MIMOME channels. First, we set up a DL‐based AS‐aided MIMO SDR environment that ensures intelligent decisions for AS. Accordingly, the hybrid loss function induced in bidirectional long short term memory (HLFI‐Bi‐LSTM) model is proposed to build the decision server, in which it takes some estimated features as input. The features such as channel state information, received signal strength indicator (RSSI), signal‐to‐noise ratio (SNR), and antenna gain are considered accordingly as the input to HLFI‐Bi‐LSTM. The HLFI‐Bi‐LSTM model is the extended version of Bi‐LSTM, which is improved by inducing the hybrid loss function, which is the combination of two functions namely, combo loss and inverse mean square error. The proposed HLFI‐Bi‐LSTM attained the greater accuracy value of 0.968 at 80% for optimal selection of the antenna.

Unlocking the potential of artificial intelligence in electrocardiogram biometrics: age-related changes, anomaly detection, and data authenticity in mobile health platforms.

Mobile devices such as smartphones and watches can now record single-lead electrocardiograms (ECGs), making wearables a potential screening tool for cardiac and wellness monitoring outside of healthcare settings. Because friends and family often share their smart phones and devices, confirmation that a sample is from a given patient is important before it is added to the electronic health record. We sought to determine whether the application of Siamese neural network would permit the diagnostic ECG sample to serve as both a medical test and biometric identifier. When using similarity scores to discriminate whether a pair of ECGs came from the same patient or different patients, inputs of single-lead and 12-lead medians produced an area under the curve of 0.94 and 0.97, respectively. The similar performance of the single-lead and 12-lead configurations underscores the potential use of mobile devices to monitor cardiac health.

DWSP-MT: Discovery of workers sensing preferences to match tasks for improving data collection quality in MCS

Mobile CrowdSensing (MCS) is a new sensing paradigm that leverages the widespread use of mobile devices to collect data quickly and enable various key applications in the Internet of Things (IoT). Collecting high-quality data is essential for MCS to design and provide a high-quality service. However, it is difficult for the platform to detect dishonest workers who submit fake data. Therefore, MCS applications face a significant challenge. Although there are a number of studies on truth discovery, these studies mainly failed to consider the sensing preferences of workers, resulting in poor data quality enhancement. To overcome these issues, a Discovery of Workers Sensing Preferences to Match Tasks (DWSP-MT) scheme is proposed to improve the quality of MCS data collection. The DWSP-MT scheme primarily includes three components: 1) Unmanned Aerial Vehicles (UAVs) are employed to sense data as ground truth data and an unsupervised anomaly detection algorithm is adopted to identify the data truth of tasks submitted by unidentified workers. 2) The data truth of unidentified workers in historical tasks is evaluated to calculate their sensing preferences, which are used to identify trusted workers. 3) To improve the quality of data collection, a task assignment model based on the sensing preferences of trusted workers is proposed for the first time, which can ensure that tasks are assigned to their areas of most excellent expertise. At last, two open-access datasets were used to conduct experiments comparing the DWSP-MT scheme with existing truth discovery methods. The outcomes of these experiments indicate that our approach outperforms the state-of-the-art research and improves F1-score by 65.74 %, improves accuracy by 36.62 %, and reduces data bias by 60.61 %

Low adoption of mobility device in later life: Insights from the lens of intersectionality

ObjectivesTo investigate the utilization of mobility device, whether age and gender-related use disparities exist, and whether falls can further explain use disparities over time among Chinese older adults in need of devices. MethodsCommunity-dwelling older adults who needed mobility devices and completed four waves of the China Health and Retirement Survey 2011–2018 were included (N = 1,302). A categorical variable was created to represent respondents’ intersectionality of age (50–64, 65–74, and ≥75 years) and gender (men vs. women). ResultsThe baseline prevalence of device use was 18.2 % (n = 237). Overall, the device use increased over time. Intersectionality-wise, oldest-old women were 1.53 times more likely than youngest-old men to use devices over time. Respondents with falls were more likely to use devices over time. ConclusionsOlder adults with mobility impairment, especially the oldest-old women and those with falls, lag in mobility devices utilization, suggesting future tailored interventions to support these populations.

EHealth Data Security and Privacy: Perspectives from Diverse Stakeholders in Malawi

The development and adoption of eHealth in low- and middle-income countries has potential to advance the quality of care in healthcare settings that are challenged by weak infrastructure. Especially in the countries where HIV rates are high, there is need to implement electronic medical record systems to enhance care and improve treatment outcomes. Due to the sensitivity of HIV-related information, eHealth applications in HIV care necessitate the attention and prioritization of data security and privacy. We explored diverse stakeholders' views on data security and privacy in Malawi's public HIV care program to expand the understanding of gaps and opportunities in improving data protections. This work connects data security and privacy goals and practices with previous work on mobile device usage as well as global best practices for security and privacy in healthcare settings. A key finding articulated by stakeholders is the importance of establishing strong data security governance.

Digital Marketing of Starbucks in the New Retail Era in China

The background term digital marketing refers to the use of websites, apps, mobile devices, social media, search engines, and other digital means to promote and sell products and services. Digital marketing started to become popular with the widespread adoption of the Internet in the 1990s. Digital marketing involves many of the same principles as traditional marketing and is often considered an additional way for companies to approach consumers and understand their behavior. Companies often combine traditional and digital marketing techniques in their strategies. But digital marketing also comes with its own set of challenges. This paper chooses to focus on a company for the object of study which is called Starbucks to explore the effect of the challenge that digital marketing in the new retail era brings to for research questions. This paper looks for the data from the official website. The result that the research brings me is that digital marketing in the new retail era truly brings Starbucks a lot of new choices and a lot of questions exposed more obviously.

Identifying Strengths and Weaknesses in Mobile Education: A Gender-Informed Self-Assessment of Teachers’ Use of Mobile Devices

Mobile devices have the potential to transform education and society. Promoting mobile learning and enhancing teachers’ digital and entrepreneurial skills are essential in achieving this goal. This study analyses the conditions under which the use of mobile technology can support teachers in the design, implementation, and evaluation of teaching and learning processes. Data were collected using a quantitative method based on a self-assessment instrument (Cronbach’s alpha = 1.0046). A total of 327 educators filled out the survey, which included 67 items scored on a Likert scale. The self-assessment tool provided participants with feedback on their mobile device use for educational purposes and suggestions for improvement. The results indicate that the median score of the teachers was 7, which is regarded as satisfactory, with a gender gap of 3.5 points. In addition, three out of seven improvement dimensions were identified: technology learning spaces (54.74%), assessment (57.65%), and design activities (59.26%). In conclusion, the study enabled us to stratify and analyse teachers’ pedagogical perceptions of mobile learning and the significance of inference in certain training areas.

Mobile device screen time is associated with poorer language development among toddlers: results from a large-scale survey

BackgroundDespite young children’s widespread use of mobile devices, little research exists on this use and its association with children’s language development. The aim of this study was to examine the associations between mobile device screen time and language comprehension and expressive language skills. An additional aim was to examine whether three factors related to the domestic learning environment modify the associations.MethodsThe study uses data from the Danish large-scale survey TRACES among two- and three-year-old children (n = 31,125). Mobile device screen time was measured as time spent on mobile devices on a normal day. Measurement of language comprehension and expressive language skills was based on subscales from the Five to Fifteen Toddlers questionnaire. Multivariable linear regression was used to examine the association between child mobile device screen time and language development and logistic regression to examine the risk of experiencing significant language difficulties. Joint exposure analyses were used to examine the association between child mobile device screen time and language development difficulties in combination with three other factors related to the domestic learning environment: parental education, reading to the child and child TV/PC screen time.ResultsHigh mobile device screen time of one hour or more per day was significantly associated with poorer language development scores and higher odds for both language comprehension difficulties (1–2 h: AOR = 1.30; ≥ 2 h: AOR = 1.42) and expressive language skills difficulties (1–2 h: AOR = 1.19; ≥ 2 h: AOR = 1.46). The results suggest that reading frequently to the child partly buffers the negative effect of high mobile device screen time on language comprehension difficulties but not on expressive language skills difficulties. No modifying effect of parental education and time spent by the child on TV/PC was found.ConclusionsMobile device screen time of one hour or more per day is associated with poorer language development among toddlers. Reading frequently to the child may have a buffering effect on language comprehension difficulties but not on expressive language skills difficulties.

Ethical and legal aspects of cybersecurity in health

Background: With the emergence of eHealth and mHealth, the use of mental health apps has increased significantly as an accessible and convenient approach as an adjunct to promoting well-being and mental health. There are several apps available that can assist with mental health monitoring and management, each with specific features to meet different needs. The intersection of mental health and cyber technology presents a number of critical legal and ethical issues. As mental health monitoring apps and devices become more integrated into clinical practice, cybersecurity takes on paramount importance. Objective: To address the ethical and legal aspects of health cybersecurity related to applications in mental health monitoring and management. Methods: We carried out a thematic synthesis of the best scientific evidence. Results: These tools have the potential to significantly improve access to and quality of care for users with mental health conditions, but they also raise substantial concerns about privacy and informed consent. Cybersecurity in mental health is not only a matter of technology, but also of human rights. The protection of sensitive mental health information is critical, and legal and ethical measures to safeguard this information must be implemented in a robust and transparent manner. Conclusion: the use of information technologies and mobile devices is now part of the clinical reality and its future perspectives. It is important to mention that while these apps can be helpful for self-care and mental well-being management, they are not a substitute for the advice and support of a qualified mental health professional (psychologist or psychiatrist). As we move into the digital age, it is imperative that mental health monitoring and management apps are developed and used responsibly, ensuring the safety, dignity, and well-being of users.

Connection-Aware Heuristics for Scheduling and Distributing Jobs under Dynamic Dew Computing Environments

Due to the widespread use of mobile and IoT devices, coupled with their continually expanding processing capabilities, dew computing environments have become a significant focus for researchers. These environments enable resource-constrained devices to contribute computing power to a local network. One major challenge within these environments revolves around task scheduling, specifically determining the optimal distribution of jobs across the available devices in the network. This challenge becomes particularly pronounced in dynamic environments where network conditions constantly change. This work proposes integrating the “reliability” concept into cutting-edge human-design job distribution heuristics named ReleSEAS and RelBPA as a means of adapting to dynamic and ever-changing network conditions caused by nodes’ mobility. Additionally, we introduce a reinforcement learning (RL) approach, embedding both the notion of reliability and real-time network status into the RL agent. Our research rigorously contrasts our proposed algorithms’ throughput and job completion rates with their predecessors. Simulated results reveal a marked improvement in overall throughput, with our algorithms potentially boosting the environment’s performance. They also show a significant enhancement in job completion within dynamic environments compared to baseline findings. Moreover, when RL is applied, it surpasses the job completion rate of human-designed heuristics. Our study emphasizes the advantages of embedding inherent network characteristics into job distribution algorithms for dew computing. Such incorporation gives them a profound understanding of the network’s diverse resources. Consequently, this insight enables the algorithms to manage resources more adeptly and effectively.