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Internet of Things Enabled Device Fault Prediction System Using Machine Learning

  • Kotte Bhavana
  • Vinuthna Nekkanti
  • N. JayapandianEmail author
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 98)

Abstract

Internet of Things (IOT) started as a niche market for hobbyists and has evolved into a huge industry. This IoT is convergence of manifold technologies, real-time analytics, machine learning and Artificial Intelligence. It has given birth to many consumer needs like home automation, prior device fault detection, health appliances and remote monitoring applications. Programmed recognition and determination of different kinds of machine disappointment is a fascinating process in modern applications. Different sorts of sensors are utilized to screen flaws that is discovers vibration sensors, sound sensors, warm sensors, infrared cameras, light cameras, and other multispectral sensors. The modern devices are becoming ubiquitous and pervasive in day to day life. This device is need for reliable and predicate algorithms. This article is primarily emphases on the prediction of faults in real life appliances making our day to day life easier. Here, the database of the device includes previous faults which are restored in online by using cloud computing technology. This will help in the prediction of the faults in the devices that are to be ameliorated. It additionally utilizes Naïve Bayes calculation for shortcoming location in the gadgets. The proposed model of this article is involves the monitoring of each and every home appliance through internet and thereby detect faults without much of human intervention.

Keywords

Internet of Things Sensors Cloud computing Home appliance Machine learning Naive Bayes 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Kotte Bhavana
    • 1
  • Vinuthna Nekkanti
    • 1
  • N. Jayapandian
    • 1
    Email author
  1. 1.Department of Computer Science and EngineeringCHRIST (Deemed to Be University), Kengeri CampusBangaloreIndia

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