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Transforming the Lives of Socially Dependent to Self-dependent Using IoT

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Machine Learning and Information Processing

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1311))

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Abstract

Internet of Things (IoT) explores the new sensor-based wearable devices and technologies that can be used in day-to-day life. It has opened up a wide range of new dimensions in elderly care, disability care and patient care through real-time monitoring and life supports. This new paradigm has reformed the lifestyle of the socially dependent individuals for the better. It has helped set high standards in the healthcare domain by enabling smart and high technology devices. It has bestowed a self-dependent life to the differently-abled and elderly individuals. Another appealing aspect about IoT is such devices are being made cost-effective in terms of their development so that large number of users look up to these devices for daily usage and whole mankind takes maximum benefit out of the technology. IoT, indeed has got a lot to serve to the society on various aspects, only if mankind is ready to accept it wholeheartedly. This paper briefly summarizes the role of IoT in healthcare and life support and highlights its novel utilities for betterment of socially dependents. Features of some of the IoT solutions have also been discussed thoroughly for instantiating the care that can be imparted by these devices in transforming the socially dependent lives to self-dependent ones. Also, a feature comparison has been provided to stress on the fact that IoT devices can indeed be upgraded at a fast pace which is not to be abdicated but rather be availed for the greater good.

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Acknowledgements

This work is funded by OSHEC, Department of Higher Education, Govt. of Odisha under the OURIIP scheme at Rama Devi Women’s University, Bhubaneswar, India.

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Correspondence to Sony Snigdha Sahoo .

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Swain, D., Sahoo, S.S. (2021). Transforming the Lives of Socially Dependent to Self-dependent Using IoT. In: Swain, D., Pattnaik, P.K., Athawale, T. (eds) Machine Learning and Information Processing. Advances in Intelligent Systems and Computing, vol 1311. Springer, Singapore. https://doi.org/10.1007/978-981-33-4859-2_18

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