Smart Assistance of Elderly Individuals in Emergency Situations at Home

Reddy, Anu Radha; Ghantasala, G. S. Pradeep; Patan, Rizwan; Manikandan, R.; Kallam, Suresh

doi:10.1007/978-3-030-63937-2_6

Cited by 14 publications

(6 citation statements)

References 31 publications

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“…Bayesian methods, Logic-Based classifiers, Support Vector Machines, for instance the Random Forest algorithm, and a few other unsupervised, semi-supervised methods used for breast image classification are used to detect cancer cells in a microscopic image (Reddy et al, 2021;CADe, 2020). Tumor Marker Test, Complete Blood Count, and image into multiple regions are also important to detect cancer cells in a microscopic image.…”

Section: Models and Methodsmentioning

confidence: 99%

Machine Learning Research On Breast And Lung Cancer Detection

Rao

2023

IJIE

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As the diagnosis of these cancer cells at late stages causes greater pain and raises the likelihood of death, the initial-state cancer finding is crucial to giving the patient the proper care and reducing the risk of dying from cancer. The publication offers a chance to research breast and lung cancer detection techniques as well as various algorithms for cancer early detection. With the aid of various image kinds and test results data sets, hybrid approaches are utilized to identify lung and breast cancer based on the size and form of the cells. The basic concept of breast and lung cancer block diagram is also explained in this study, with an emphasis on the difficulties and potential future applications of cancer detection and diagnosis techniques.

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Section: Models and Methodsmentioning

confidence: 99%

Machine Learning Research On Breast And Lung Cancer Detection

Rao

2023

IJIE

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“…Such as remote rehabilitation using wearable muscle sensors and Kinect ( 22 ). Accidental injury, unlike common diseases, is physical injuries outside of everyday situations, and the prevention aims to provide personalized assistance services for the older adults in emergency situations ( 23 ). Falls tend to be the main cause of fatal and non-fatal injuries in the older adults ( 24 ), and remote fall monitoring allows the older adults to receive timely assistance ( 25 ).…”

Section: Literature Overviewmentioning

confidence: 99%

Determinants of intention with remote health management service among urban older adults: A Unified Theory of Acceptance and Use of Technology perspective

Gui

Luo

et al. 2023

Front. Public Health

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BackgroundAlthough older adults health management systems have been shown to have a significant impact on health levels, there remains the problem of low use rate, frequency of use, and acceptance by the older adults. This study aims to explore the significant factors which serve as determinants of behavioral intention to use the technology, which in turn promotes actual use.MethodsThis study took a total of 402 urban older adults over 60 years to explore the impact of the use behavior toward remote health management (RHM) through an online questionnaire. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT), the author adds four dimensions: perceived risk, perceived value, perceived interactivity and individual innovation, constructed an extended structural equation model of acceptance and use of technology, and analyzed the variable path relationship.ResultsIn this study, the factor loading is between 0.61 and 0.98; the overall Cronbach's Alpha coefficients are >0.7; The composite reliability ranges from 0.59 to 0.91; the average variance extraction ranges from 0.51 to 0.85, which shows the good reliability, validity, and discriminant validity of the constructed model. The influencing factors of the behavioral intention of the older adults to accept the health management system are: effort expectation, social influences, perceived value, performance expectation, perceived interactivity and perceived risk. Effort expectation has a significant positive impact on performance expectation. Individual innovation positively impacts performance expectation and perceived interactivity. Perceived interactivity and behavioral intention have a significant positive effect on the use behavior of the older adults, while the facilitating conditions have little effect on the use behavior.ConclusionsThis paper constructs and verifies the extended model based on UTAUT, fully explores the potential factors affecting the use intention of the older adult users. According to the research findings, some suggestions are proposed from the aspects of effort expectation, performance expectation, perceived interaction and perceived value to improve the use intention and user experience of Internet-based health management services in older adults.

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“…These components are consistently bound together with day-by-day protests and related through a worldwide organization stage. Adaptability, independence, and pragmatic client collaboration are the principal prerequisites to accomplish innovative conditions [5]. Moreover, assuring connection among essential [6] develop a flexible structure that uses the artificial Application Protocol over a framework of IPv6 low-power remote individual region organization and authentic state move (REST) to ease correspondence among these respecting advances.…”

Section: A Smart Environmentmentioning

confidence: 99%

Smart Cities: An In-Depth Study of AI Algorithms and Advanced Connectivity

Yaswanth,

Babu,

Vineetha

et al. 2023

IJRITCC

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The goal of smart city development is to improve the quality of life by incorporating technology into daily activities. Artificial intelligence (AI) is critical to the ongoing development of future smart cities. The Internet of Things (IoT) idea connects every internet-enabled device for improved access and control. AI in various domains has changed ordinary towns into highly equipped smart cities. Machine learning and deep learning algorithms have proven indispensable in a variety of industries, and they are now being implemented into smart city concepts to automate and improve urban activities and operations on a large scale. IoT and machine learning technology are frequently used in smart cities to collect data from various sources. This article delves deeply into the significance, scope, and developments of AI-based smart cities. It also addresses some of the difficulties and restrictions associated with smart cities powered by AI. The goal of the study is to inspire and encourage academics to create original smart city solutions based on AI technologies.

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Smart Assistance of Elderly Individuals in Emergency Situations at Home

Cited by 14 publications

References 31 publications

Machine Learning Research On Breast And Lung Cancer Detection

Machine Learning Research On Breast And Lung Cancer Detection

Determinants of intention with remote health management service among urban older adults: A Unified Theory of Acceptance and Use of Technology perspective

Smart Cities: An In-Depth Study of AI Algorithms and Advanced Connectivity

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