IoT based fall detection and ambient assisted system for the elderly

Chandra, Ishwar; Sivakumar, N.; Babu, Gokulnath Chandra; Parthasarathy, P.

doi:10.1007/s10586-018-2329-2

Cited by 49 publications

(12 citation statements)

References 21 publications

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“…Ms. Supriya Chandrakant Padwal and Mr. Suraj Vishnu Kurde (2016) displayed the practical outline and usage of a total WSN stage that can be utilized for a scope of long haul natural checking IoT applications. Their point towards the usage of WSN for condition observing in IoT by recommending answers for different issues confronted while executing WSN in genuine [ 32 ].…”

Section: Related Workmentioning

confidence: 99%

RETRACTED ARTICLE: Internet of Things Based Intelligent Transportation of Food Products During COVID

Alluhaidan

Alluhaidan²,

Basheer

2021

Wireless Pers Commun

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Section: Related Workmentioning

confidence: 99%

RETRACTED ARTICLE: Internet of Things Based Intelligent Transportation of Food Products During COVID

Alluhaidan

Alluhaidan²,

Basheer

2021

Wireless Pers Commun

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“…Another major challenge for such types of devices is identifying the human poses and detecting a change in a pose while detecting a fall event. In a recent study, this issue has been eliminated with the applications of convolutional neural network algorithms [78]. e authors have used a series of poses to differentiate between a fall event and a nonfall event.…”

Section: Activity Recognitionmentioning

confidence: 99%

The Internet of Things in Geriatric Healthcare

Sahu

Pradhan

Khasnobish

et al. 2021

Journal of Healthcare Engineering

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There is a significant increase in the geriatric population across the globe. With the increase in the number of geriatric people and their associated health issues, the need for larger healthcare resources is inevitable. Because of this, healthcare service-providing industries are facing a severe challenge. However, technological advancement in recent years has enabled researchers to develop intelligent devices to deal with the scarcity of healthcare resources. In this regard, the Internet of things (IoT) technology has been a boon for healthcare services industries. It not only allows the monitoring of the health parameters of geriatric patients from a remote location but also lets them live an independent life in a cost-efficient way. The current paper provides up-to-date comprehensive knowledge of IoT-based technologies for geriatric healthcare applications. The study also discusses the current trends, issues, challenges, and future scope of research in the area of geriatric healthcare using IoT technology. Information provided in this paper will be helpful to develop futuristic solutions and provide efficient cost-effective healthcare services to the needy.

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“…Ambient sensor based techniques exploit the recordings of audio and video and/or monitor vibrational data from the environment [19,21,57,60,62]. For instance, the approach described in [57] analyzes and verifies sensor-transmitted events through audio and video streams for object detection and tracking.…”

Section: Related Literaturementioning

confidence: 99%

A machine learning based sentient multimedia framework to increase safety at work

Bonifazi

Corradini

Ursino

et al. 2021

Multimed Tools Appl

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In the last few decades, we have witnessed an increasing focus on safety in the workplace. ICT has always played a leading role in this context. One ICT sector that is increasingly important in ensuring safety at work is the Internet of Things and, in particular, the new architectures referring to it, such as SIoT, MIoT and Sentient Multimedia Systems. All these architectures handle huge amounts of data to extract predictive and prescriptive information. For this purpose, they often make use of Machine Learning. In this paper, we propose a framework that uses both Sentient Multimedia Systems and Machine Learning to support safety in the workplace. After the general presentation of the framework, we describe its specialization to a particular case, i.e., fall detection. As for this application scenario, we describe a Machine Learning based wearable device for fall detection that we designed, built and tested. Moreover, we illustrate a safety coordination platform for monitoring the work environment, activating alarms in case of falls, and sending appropriate advices to help workers involved in falls.

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IoT based fall detection and ambient assisted system for the elderly

Cited by 49 publications

References 21 publications

RETRACTED ARTICLE: Internet of Things Based Intelligent Transportation of Food Products During COVID

RETRACTED ARTICLE: Internet of Things Based Intelligent Transportation of Food Products During COVID

The Internet of Things in Geriatric Healthcare

A machine learning based sentient multimedia framework to increase safety at work

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