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Survey Paper on IoT based Smart Intelligent Toilet using SVM and Regression Algorithms

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2019
Authors:
Vasudha K., Yashaswini S., Ashwini K,
10.5120/ijca2019918588

Vasudha K., Yashaswini S. and Ashwini K and. Survey Paper on IoT based Smart Intelligent Toilet using SVM and Regression Algorithms. International Journal of Computer Applications 181(46):13-15, March 2019. BibTeX

@article{10.5120/ijca2019918588,
	author = {Vasudha K. and Yashaswini S. and Ashwini K and},
	title = {Survey Paper on IoT based Smart Intelligent Toilet using SVM and Regression Algorithms},
	journal = {International Journal of Computer Applications},
	issue_date = {March 2019},
	volume = {181},
	number = {46},
	month = {Mar},
	year = {2019},
	issn = {0975-8887},
	pages = {13-15},
	numpages = {3},
	url = {http://www.ijcaonline.org/archives/volume181/number46/30428-2019918588},
	doi = {10.5120/ijca2019918588},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

This paper proposes the concept of Machine Learning and Internet of Things (IoT) to implement a Smart Intelligent Toilet. Machine learning is used to regulate the formation of crucial models in order to enable algorithms to learn with the help of available data. IoT is regarding embedding system to the internet. Machine learning and IoT has experienced a boost in acceptance among many fields including the medical field. The modern and upgraded laboratory is very much necessary as diagnosis of a disease and analysis of a person’s health in a precise form is very much important. Artificial intelligence creates a platform to be precise in the measurement of any parameters using various algorithms. In this paper, we propose to apply Regression algorithm to predict the output values like urine test, based on input features such as urine sample from data sets fed in the system. The algorithm builds a model based on the features of the training dataset and also makes use of the model to predict value for new data. Support Vector Machine(SVM) is a machine learning algorithm used for both classification and regression challenges. IoT devices fail to function without artificial intelligence and artificial intelligence in turn needs IoT devices to be of better use for a smarter human kind. Both these technologies jointly hold the power to alter our lives to better standards.

References

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Keywords

SVM, regression, urine analyzer, Global System for Mobile(GSM), electrocardiogram, bio- impedance strategy , Raspberry pi microprocessor, aurdino board.