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Title	Machine Learning For Internet Of Things: A Recapitulation
ID_Doc	35964
Authors	Gangal R.; Johri P.; Kumar A.
Year	2021
Published	2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions), ICRITO 2021
DOI	http://dx.doi.org/10.1109/ICRITO51393.2021.9596071
Abstract	IoT is quickly becoming a popular field of IT and the digital world, presenting new research prospects in the ambit of devices and applications connected via internet. Several academics have previously proved their work in this field by employing Machine Learning techniques and algorithms as a subset of AI to fully implement large volumes of data. IOT is considered as a platform where devices are connected together through internet as a medium and by using sensors, data is captured which adds digital intelligence. Data can be access anytime and from anywhere. The need for such devices that can not only store data but also analyzeit and take quick action is growing by the day. Machine learning which makes smart system after adding intelligence to it, makes IOT more smart, responsive and action oriented. Using machine learning we can detect the slightest changes and warn against any type of malfunctioning. Predictive Analysis is added advantage which acts as gift from Machine learning to IOT. This analysis is done in real-time and the results can be displayed on the Smartphone in a few seconds. Though IOT and Machine leaning are powerful tools as an alone but combination of both the technologies is much more which is yet to be explored. © 2021 IEEE.
Author Keywords	IoT data Analytics; Machine Learning; Sensors; Smart cities and Predictive Analysis

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