| 1. |
- Ghayvat, Hemant, et al.
(author)
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Guest Editorial AIoPT (Artificial Intelligence of Paediatric Things) : Informatics in Meeting Paediatric Needs and Patient Monitoring
- 2023
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In: IEEE journal of biomedical and health informatics. - : IEEE. - 2168-2194 .- 2168-2208. ; 27:6, s. 2600-2602
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Journal article (other academic/artistic)abstract
- Medical (health) informatics broadly encompasses the cognitive, information processing, and communication tasks inherent in medical practice, education, and research, with a particular emphasis on the development of computer-based patient records, decision support systems, information standards, data aggregation systems, communication systems, and educational programs for patients and health providers. In addition, this rapidly growing area is confronted with developing technological solutions sensitive to special populations' specific requirements, i.e., Preventive, Assistive, and Medical Children Health Informatics . First, children have distinct physiology, come from diverse backgrounds, and are disproportionately affected by illnesses. Thus, children are not little adults, as a famous adage among child health experts. These distinctions have been extensively discussed and are frequently called the four D's. Second, children depend on their parents and extended relatives to access necessary health care. Thus, plans must include gathering and distributing information to many patients. Third, childhood is defined by a developmental trajectory marked by fast change and the emergence of capacities for health information utilization. Fourth, children's health is defined by distinct epidemiology characterized by fewer significant chronic diseases, a high prevalence of acute illnesses, and reliance on preventative interventions. Finally, since children are the poorest and most varied in our society, they exhibit distinct demographic trends.
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| 2. |
- Ghayvat, Hemant, et al.
(author)
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Smart Aging System : Uncovering the Hidden Wellness Parameter for Well-Being Monitoring and Anomaly Detection
- 2019
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In: Sensors. - : MDPI. - 1424-8220. ; 19:4
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Journal article (peer-reviewed)abstract
- Background: Ambiguities and anomalies in the Activity of Daily Living (ADL) patterns indicate deviations from Wellness. The monitoring of lifestyles could facilitate remote physicians or caregivers to give insight into symptoms of the disease and provide health improvement advice to residents; Objective: This research work aims to apply lifestyle monitoring in an ambient assisted living (AAL) system by diagnosing conduct and distinguishing variation from the norm with the slightest conceivable fake alert. In pursuing this aim, the main objective is to fill the knowledge gap of two contextual observations (i.e., day and time) in the frequent behavior modeling for an individual in AAL. Each sensing category has its advantages and restrictions. Only a single type of sensing unit may not manage composite states in practice and lose the activity of daily living. To boost the efficiency of the system, we offer an exceptional sensor data fusion technique through different sensing modalities; Methods: As behaviors may also change according to other contextual observations, including seasonal, weather (or temperature), and social interaction, we propose the design of a novel activity learning model by adding behavioral observations, which we name as the Wellness indices analysis model; Results: The ground-truth data are collected from four elderly houses, including daily activities, with a sample size of three hundred days plus sensor activation. The investigation results validate the success of our method. The new feature set from sensor data fusion enhances the system accuracy to (98.17% +/- 0.95) from (80.81% +/- 0.68). The performance evaluation parameters of the proposed model for ADL recognition are recorded for the 14 selected activities. These parameters are Sensitivity (0.9852), Specificity (0.9988), Accuracy (0.9974), F1 score (0.9851), False Negative Rate (0.0130).
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| 3. |
- Sodhro, Ali Hassan, et al.
(author)
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A Lightweight Security Scheme for Failure Detection in Microservices IoT-Edge Networks
- 2022
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In: Sensing Technology. - Cham : Springer. ; , s. 397-409
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Book chapter (pop. science, debate, etc.)abstract
- Nowadays, microservices-based applications such as E-Business, E-Healthcare, 3D-Gaming, and Augmented Reality have latterly drawn attention in the research area. The microservices enabled applications are different from traditional monolithic applications with high demand of security and fault detection, therefore, a lightweight secure and failure detection enabled schemes widely required for the new applications. This paper proposes a new lightweight microservices mobile cloud (Mob-Cloud) framework that replaces the heavyweight virtual machine (VM) based on mobile cloud computing (MCC). The study devises MFHE (Modified Fully Homomorphism Encryption) and WATFA (Workload Assignment Transient Fault Aware) schemes to deal with security and failures. Simulation results show that the proposals are practical for the considered problem.
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