PP-SPA: Privacy Preserved Smartphone-Based Personal Assistant to Improve Routine Life Functioning of Cognitive Impaired Individuals

Javed, Abdul Rehman; Sarwar, Muhammad Usman; Rehman, Saif Ur; Khan, Habib Ullah; Al‐Otaibi, Yasser D.; Alnumay, Waleed S.

doi:10.1007/s11063-020-10414-5

Cited by 41 publications

(32 citation statements)

References 34 publications

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“…Throughout the world, countries have not only developed mobile phone applications to tackle coronavirus disasters but are also using data gathered from it to make their decisions about lockdowns in a smart way [14]. Australia 4 , China 5 , South Korea 6 , and Singapore 7 , are the countries which have taken leading steps by advising their citizens to install these applications for surveillance purpose, in India, an application called Aorogya-set was designed for this purpose 8 . However, such procedures undertaken by governments lack the needed privacy protections in their mechanisms, which risks people's data.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Standard operating procedures are to be developed and followed to ensure protection with activities being carried on within them. Smartphone consists of multiple sensors and actuators (i.e., GPS, accelerometer, gyroscope, magnetometer, Bluetooth) [5][6][7][8]. Some of the countries tackled the situation by using smartphone technologies such as Bluetooth and GPS, which enables people to have awareness about those who met the infected ones (so that they can keep their distance).…”

Section: Introductionmentioning

confidence: 99%

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RETRACTED ARTICLE: Blockchain and ANFIS empowered IoMT application for privacy preserved contact tracing in COVID-19 pandemic

Aslam

Javed

Chakraborty

et al. 2021

Pers Ubiquit Comput

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Life-threatening novel severe acute respiratory syndrome coronavirus (SARS-CoV-2), also known as COVID-19, has engulfed the world and caused health and economic challenges. To control the spread of COVID-19, a mechanism is required to enforce physical distancing between people. This paper proposes a Blockchain-based framework that preserves patients' anonymity while tracing their contacts with the help of Bluetooth-enabled smartphones. We use a smartphone application to interact with the proposed blockchain framework for contact tracing of the general public using Bluetooth and to store the obtained data over the cloud, which is accessible to health departments and government agencies to perform necessary and timely actions (e.g., like quarantine the infected people moving around). Thus, the proposed framework helps people perform their regular business and day-to-day activities with a controlled mechanism that keeps them safe from infected and exposed people. The smartphone application is capable enough to check their COVID status after analyzing the symptoms quickly and observes (based on given symptoms) either this person is infected or not. As a result, the proposed Adaptive Neuro-Fuzzy Interference System (ANFIS) system predicts the COVID status, and K-Nearest Neighbor (KNN) enhances the accuracy rate to 95.9% compared to state-of-the-art results.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

RETRACTED ARTICLE: Blockchain and ANFIS empowered IoMT application for privacy preserved contact tracing in COVID-19 pandemic

Aslam

Javed

Chakraborty

et al. 2021

Pers Ubiquit Comput

Self Cite

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“…However, a service user may face a situation where it discovers that its own private data had been routed by a service provider, without prior permission for doing so, this hinders user’s data privacy ( Deepa et al, 2020 ; Talal & Quan, 2013 ). A data privacy leakage is known as a security threat, where it can lead to cyber-attacks, social issues, or cause user robbery by different means ( Javed et al, 2021 ; Iwendi et al, 2020 ; Vasani & Chudasama, 2018 ). To monitor such service provider actions, a service user sends a complain message “ ” to the CSM, against the suspected service provider including an evidence for this incident.…”

Section: Proposed Integrated Three-tier Trust Management Frameworkmentioning

confidence: 99%

An integrated three-tier trust management framework in mobile edge computing using fuzzy logic

Mansour

Abdelkader

Hashem

et al. 2021

PeerJ Computer Science

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Mobile edge computing (MEC) is introduced as part of edge computing paradigm, that exploit cloud computing resources, at a nearer premises to service users. Cloud service users often search for cloud service providers to meet their computational demands. Due to the lack of previous experience between cloud service providers and users, users hold several doubts related to their data security and privacy, job completion and processing performance efficiency of service providers. This paper presents an integrated three-tier trust management framework that evaluates cloud service providers in three main domains: Tier I, which evaluates service provider compliance to the agreed upon service level agreement; Tier II, which computes the processing performance of a service provider based on its number of successful processes; and Tier III, which measures the violations committed by a service provider, per computational interval, during its processing in the MEC network. The three-tier evaluation is performed during Phase I computation. In Phase II, a service provider total trust value and status are gained through the integration of the three tiers using the developed overall trust fuzzy inference system (FIS). The simulation results of Phase I show the service provider trust value in terms of service level agreement compliance, processing performance and measurement of violations independently. This disseminates service provider’s points of failure, which enables a service provider to enhance its future performance for the evaluated domains. The Phase II results show the overall trust value and status per service provider after integrating the three tiers using overall trust FIS. The proposed model is distinguished among other models by evaluating different parameters for a service provider.

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“…Machine learning has been applied to multiple healthcare fields, including diabetes, cancer, cardiology, and mental health (14)(15)(16)(17). Most of the machine learning models and tools developed in the research environment has studied the potential of prognosis, diagnosis, or clinical componentization, thus demonstrating the prospect of developing computerized decision support tools (18,19).…”

Section: Introductionmentioning

confidence: 99%

A Machine Learning Model for Accurate Prediction of Sepsis in ICU Patients

Wang

Sun

et al. 2021

Front. Public Health

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Background: Although numerous studies are conducted every year on how to reduce the fatality rate associated with sepsis, it is still a major challenge faced by patients, clinicians, and medical systems worldwide. Early identification and prediction of patients at risk of sepsis and adverse outcomes associated with sepsis are critical. We aimed to develop an artificial intelligence algorithm that can predict sepsis early.Methods: This was a secondary analysis of an observational cohort study from the Intensive Care Unit of the First Affiliated Hospital of Zhengzhou University. A total of 4,449 infected patients were randomly assigned to the development and validation data set at a ratio of 4:1. After extracting electronic medical record data, a set of 55 features (variables) was calculated and passed to the random forest algorithm to predict the onset of sepsis.Results: The pre-procedure clinical variables were used to build a prediction model from the training data set using the random forest machine learning method; a 5-fold cross-validation was used to evaluate the prediction accuracy of the model. Finally, we tested the model using the validation data set. The area obtained by the model under the receiver operating characteristic (ROC) curve (AUC) was 0.91, the sensitivity was 87%, and the specificity was 89%.Conclusions: This newly established machine learning-based model has shown good predictive ability in Chinese sepsis patients. External validation studies are necessary to confirm the universality of our method in the population and treatment practice.

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PP-SPA: Privacy Preserved Smartphone-Based Personal Assistant to Improve Routine Life Functioning of Cognitive Impaired Individuals

Cited by 41 publications

References 34 publications

RETRACTED ARTICLE: Blockchain and ANFIS empowered IoMT application for privacy preserved contact tracing in COVID-19 pandemic

RETRACTED ARTICLE: Blockchain and ANFIS empowered IoMT application for privacy preserved contact tracing in COVID-19 pandemic

An integrated three-tier trust management framework in mobile edge computing using fuzzy logic

A Machine Learning Model for Accurate Prediction of Sepsis in ICU Patients

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