RFID enabled smart data analysis in a smart warehouse monitoring system using iot

11Citations
Citations of this article
29Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

In this modern era, the world runs on various machines and technologies that make the life of a human beings simple, easy and convenient. One such proficient equipment that helps mankind is "MACHINE", which works as the most efficient, significant and integral part of any kind of industry. The machines assist the community termed as humans by performing several operations, beginning from the component preparation called the production till the generation of various products and necessary amenities for the aid and welfare of human beings. As known an industry or a warehouse plays a vital role in the above statement, the system deals with the complete machine state analysis coupled with RFID and IoT. The main objective of this system is to analyzeparameters of any machine with the help of Radio Frequency Identification (RFID) and sensors, that generates the desired data to the Internet of Things (IoT). If any flaw arises in the machine on any one of the parameters, the RFID that is continuously accessing the functioning levels of the machine, sends data constantly to the IoT. The buzzer gives an alert to the people around such asemployees, wing supervisorsand specialists. The fault detected by the stream of the sequential process, starting from the RFID tag which is used for accessing the sensors, then the Arduino, that then goes to the IoT with the help of RFID Reader and the Wi-Fi Modulegives information in a consistent manner and at last an alert is passed through the buzzer and the identified problem is immediately rectified easily by the respective officials to carry out the process without any hindrance.

Cite

CITATION STYLE

APA

Selvaraj, A. S., & Anusha, S. (2021). RFID enabled smart data analysis in a smart warehouse monitoring system using iot. In Journal of Physics: Conference Series (Vol. 1717). IOP Publishing Ltd. https://doi.org/10.1088/1742-6596/1717/1/012022

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free