Underground Cable Fault Detection Using Internet of Things
+91-7667918914 iarjset@gmail.com 0 Items International Advanced Research Journal in Science, Engineering and Technology A Monthly Peer-Reviewed Multidisciplinary Journal ISSN Online 2393-8021 ISSN Print 2394-1588 Since 2014 Home About About IARJSET Aims and Scope Editorial Board Editorial Policies Publication Ethics Publication Policies Indexing and Abstracting Citation Index License Information Authors How can I publish my paper? Instructions to Authors Benefits to Authors Why Publish in IARJSET Call for Papers Check my Paper status Publication Fee Details Publication Fee Mode FAQs Author Testimonials Reviewers Topics Peer Review Current Issue & Archives Indexing FAQ’s Contact Select Page Underground Cable Fault Detection Using Internet of Things Sathana.B, Jaissandiya.R, Divyadarshni.S, Ast.Prof. Poonguzhali.E
Abstract: Internet of Things is an Internet-connected object system that can store and transmit data on a wireless network without human interference. Internet of Things is a wireless system. IoT has its major contribution in fault diagnosis and prediction of the physical devices by analyzing the device without the knowledge of the physical manufacturing system Underground cables, due to underground stresses, wear and tear, rodents, etc, are subject to a variety of defects. It is also difficult to detect fault sources. To inspect and repair the failure, the whole line has to be dug. We, therefore, propose an Underground Cable Fault Detector using IoT that detects the exact position of the defect and simplifies the repair. To locate the root of the problem, the repairmen know which component is defective and only the region must be dug. This saves a lot of time, money, and effort and enables simple underground cable maintenance. This saves a great deal of time, money, and effort and allows for easy cable maintenance in the underground. We use Ohm's law principle and Blavier's test to detect and verify failures over the internet by authorities, here the Arduino board that is an IoT component functions as a machine brain and handles the sensor data. The machine detects errors by using the future cable-wide divisor network. When a failure occurs when two lines are cut, a certain voltage will be generated according to a combination of the resistance network. The microcontroller senses this voltage and is modified. The information the consumer receives is the distance that corresponds to this voltage. The microcontroller collects fault line data and displays it over an LCD monitor so that this data is transferred to the internet for online access. Keywords- Underground cables, Ohm's Law, Arduino, Blavier's test. Downloads: | DOI: 10.17148/IARJSET.2021.8709 How to Cite: [1] Sathana.B, Jaissandiya.R, Divyadarshni.S, Ast.Prof. Poonguzhali.E, "Underground Cable Fault Detection Using Internet of Things," International Advanced Research Journal in Science, Engineering and Technology (IARJSET), DOI: IARJSET.2021.8709 Copy Citation Call for Papers Rapid Publication 24/7 April 2026 Submission: eMail paper now Notification: Immediate Publication: Immediately with eCertificates Frequency: Monthly Downloads Paper Format Copyright Form Submit to iarjset@gmail.com or editor@iarjset.com Submit My Paper Author CenterHow can I publish my paper? Publication Fee Why Publish in IARJSET Benefits to Authors Guidelines to Authors FAQs (Frequently Asked Questions) Author Testimonials IARJSET ManagementAims and Scope Call for Papers Editorial Board DOI and Crossref Publication Ethics Editorial Policies Publication Policies Subscription / Librarian Conference Special Issue Info ArchivesCurrent Issue & Archives Conference Special Issue Copyright © 2026 IARJSET This work is licensed under a Creative Commons Attribution 4.0 International License. Open chat
How to Cite:
[1] Sathana.B, Jaissandiya.R, Divyadarshni.S, Ast.Prof. Poonguzhali.E, “Underground Cable Fault Detection Using Internet of Things,” International Advanced Research Journal in Science, Engineering and Technology (IARJSET), DOI: 10.17148/IARJSET.2021.8709
