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Survey towards Human Activity Recognition using IoT Domain

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2021
Shreyas Gawande, Praveda Bansode, Sayali Dukandar, Jyoti Deshmukh

Shreyas Gawande, Praveda Bansode, Sayali Dukandar and Jyoti Deshmukh. Survey towards Human Activity Recognition using IoT Domain. International Journal of Computer Applications 183(12):21-24, June 2021. BibTeX

	author = {Shreyas Gawande and Praveda Bansode and Sayali Dukandar and Jyoti Deshmukh},
	title = {Survey towards Human Activity Recognition using IoT Domain},
	journal = {International Journal of Computer Applications},
	issue_date = {June 2021},
	volume = {183},
	number = {12},
	month = {Jun},
	year = {2021},
	issn = {0975-8887},
	pages = {21-24},
	numpages = {4},
	url = {},
	doi = {10.5120/ijca2021921429},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


This task presents a novel framework dependent on the Internet of Things (IOT) to Human Activity Recognition (HAR) by observing fundamental signs distantly. Here it is use raspberry pi, wearable sensors, computational psychiatry. Also have used AI calculations to decide the movement done inside four pre-set up classes (walk, climbing and run). With an increased availability in wearable sensors we explore a better understanding of human needs. Then, it can give input during and after the movement is performed, utilizing a distant checking segment with far off perception and programmable alerts. This framework was effectively executed.


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Raspberry Pi, Location, Activity Detection, Wearable sensors, Machine learning, Deep learning, Long-Short term memory loss, Conditional random field, Computational psychiatry.