Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/519941
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dc.coverage.spatialInvestigations on predictive maintenance for automobile industry using edge intelligence and blockchain
dc.date.accessioned2023-10-22T06:16:51Z-
dc.date.available2023-10-22T06:16:51Z-
dc.identifier.urihttp://hdl.handle.net/10603/519941-
dc.description.abstractnewlineAs technology advances quickly, businesses are attempting to incorporate it to increase production and efficiency. With the introduction of the fourth industrial revolution, also known as Industry 4.0, the boundaries of industry have extended. Businesses now have a wide range of possibilities in every imaginable way thanks to the integration of IoT and IIoT. It is believed that the predictive maintenance sector could benefit from its implementation. Industry 4.0 uses clever sensors and actuators to help collect a lot of data. These vast data sets can be examined by a variety of machine learning algorithms to yield informative results. Using data/readouts from numerous IIoT instruments, artificial intelligence can forecast the performance and health of a piece of equipment.
dc.format.extentxvii,193 p.
dc.languageEnglish
dc.relationp.171-192
dc.rightsuniversity
dc.titleInvestigations on predictive maintenance for automobile industry using edge intelligence and blockchain
dc.title.alternative
dc.creator.researcherGopalakrishnan S
dc.subject.keywordComputer Science
dc.subject.keywordComputer Science Information Systems
dc.subject.keywordEdge Intelligence
dc.subject.keywordEngineering and Technology
dc.subject.keywordIoT
dc.subject.keywordK-Means
dc.description.note
dc.contributor.guideSenthikumaran M
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.publisher.institutionFaculty of Information and Communication Engineering
dc.date.registered
dc.date.completed2022
dc.date.awarded2022
dc.format.dimensions21 cm.
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Faculty of Information and Communication Engineering

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01_title.pdfAttached File26.03 kBAdobe PDFView/Open
02_prelim_pages.pdf2.35 MBAdobe PDFView/Open
03_content.pdf269.93 kBAdobe PDFView/Open
04_abstract.pdf144.17 kBAdobe PDFView/Open
05_chapter 1.pdf843.86 kBAdobe PDFView/Open
06_chapter 2.pdf518.15 kBAdobe PDFView/Open
07_chapter 3.pdf841.22 kBAdobe PDFView/Open
08_chapter 4.pdf670.4 kBAdobe PDFView/Open
09_chapter 5.pdf599.82 kBAdobe PDFView/Open
10_chapter 6.pdf1.18 MBAdobe PDFView/Open
11_annexures.pdf1.09 MBAdobe PDFView/Open
80_recommendation.pdf119.36 kBAdobe PDFView/Open


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