Automatic Body Fall Detection System for Elderly People using Accelerometer and Vision Based Technique

,; Turkane*, S. M.; Vikhe, Swapnil J.; ,; Kadu, C. B.; ,; Vikhe, P. S.; ,

doi:10.35940/ijrte.c5922.118419

Cited by 3 publications

(2 citation statements)

References 2 publications

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“…An IoT-enabled attendance tracker automates and tracks learners using radio frequency identification (RFID) or fingerprint sensor technology at the perception layer of the IoT-based framework (Al Tarshia et al, 2020;Sittampalam & Ratnarajah, 2019). As an extra perfect attendance measure, modern IoT-based attendance trackers use a camera installed in the classroom to detect images of learners and simultaneously match their faces against a class database (El Mrabet & Ait Moussa, 2020; Turkane et al, 2019). The students' attendance reports are subsequently saved in connected folders with notifications to parents and school administration.…”

Section: Figure 4 Smart Classroommentioning

confidence: 99%

Internet of Things (IoT) Applications in Education: Benefits and Implementation Challenges in Ghanaian Tertiary Institutions

Kwasi Dake,

Kudjo Bada,

Ekow Dadzie

2023

JITE:Research

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Aim/Purpose: The Internet of Things (IoT) application modules have covered diverse sectors, and the educational domain is no exception. In this survey, we discuss the specific application benefits of IoT in education and further examine implementation challenges in Ghanaian tertiary institutions. Background: This survey examines pertinent applications for IoT benefits in education and offers present and future opportunities to enhance educational outcomes. The survey includes anticipated IoT technologies that will have a significant impact on education. Each module contains concise definitions accompanied by analysis and application-specific relevance. Methodology: In order to accomplish the objectives of the survey, a search review was conducted across relevant databases, including Scopus, Hindawi, IEEE, MPDI, ScienceDirect, Informing Science Institute, Springer, and Wiley. In addition, a thorough search was carried out using Google Scholar to cover all relevant repositories. The phrases and keywords for the search were made up of five categories. The literature search resulted in 300 articles, of which 200 were considered relevant for the survey. Of the 200 articles, 95 of them shared common themes and discussed the same application integration and challenges. Contribution: This paper discusses the revolution involving IoT deployments in education and covers many aspects of the educational domain. Findings: IoT integration in education will transform Education 4.0 and improve learning outcomes significantly. Recommendations for Practitioners: Educational institutions are to embrace IoT integrations even with the emerging Education 4.0 and Industry 4.0 use cases. Recommendation for Researchers: Educational IoT is the next big thing and research directions on unique use cases for educational institutions are eminent with 5G and other disruptive technologies. Impact on Society: Effective IoT implementation in education will positively affect all stakeholders in the educational ecosystem and create a society with much access to information, connectivity, and convenience. Future Research: To survey the integration of blockchain-based IoT applications in education.

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Section: Figure 4 Smart Classroommentioning

confidence: 99%

Internet of Things (IoT) Applications in Education: Benefits and Implementation Challenges in Ghanaian Tertiary Institutions

Kwasi Dake,

Kudjo Bada,

Ekow Dadzie

2023

JITE:Research

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“…The usage of machine learning to attain high accuracy rate is also deeply discussed. Turkane et al [19] designed a fall detection system for aged persons employing 3 axis accelerator and video camera as its significant components. The system used support vector machine (SVM) which is an artificial intelligence technique in its implementation to derive precise prediction.…”

Section: A Related Workmentioning

confidence: 99%

Digital Companion for Elders in Tracking Health and Intelligent Recommendation Support using Deep Learning

Tamilselvi¹,

Lakshmi²,

Lavanya³

et al. 2023

IJRITCC

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Ambient assisted living (AAL) facilitates the daily routines of elderly people, particularly those who have clinical difficulties or physical limitations. The latest technologies like distributed compuring,internet of things (IoT) and machine learning pave the ground for the creation of an effective automated tracker which aids elder citizens to live independently. The suggested system is attempted to design a wearable that monitors the blood glucose level through sweat. To achieve high accuracy, the proposed system uses ambient sensing and deep learning based techniques. It places a strong emphasis on calculating the health index by taking into account numerous disease-related characteristics or vitals such as heart rate, blood pressure, SpO2, blood glucose level, respiration rate, sweat rate, uric acid, and temperature. From the wearable device designed the vital signs are gathered, further environmental sensors and camera fixed around the person continually monitors the behavioral pattern along with physiological signals. This ensures the improved accuracy of health state prediction from its conventional models in place. The key advantage of this device is that it may be held and operated anyplace without interrupting their day-to-day tasks because the device is to be cheap, reliable and speedy.

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Iot based fall detection system for the elderly people

Nandal,

Rao,

Mandava

et al. 2024

14th International Conference on Materials Processing and Characterization 2023

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Automatic Body Fall Detection System for Elderly People using Accelerometer and Vision Based Technique

Cited by 3 publications

References 2 publications

Internet of Things (IoT) Applications in Education: Benefits and Implementation Challenges in Ghanaian Tertiary Institutions

Internet of Things (IoT) Applications in Education: Benefits and Implementation Challenges in Ghanaian Tertiary Institutions

Digital Companion for Elders in Tracking Health and Intelligent Recommendation Support using Deep Learning

Iot based fall detection system for the elderly people

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