Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/363676
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.coverage.spatial | ||
dc.date.accessioned | 2022-02-18T05:39:10Z | - |
dc.date.available | 2022-02-18T05:39:10Z | - |
dc.identifier.uri | http://hdl.handle.net/10603/363676 | - |
dc.description.abstract | This newlinework has presented an end-to-end IoT system that uses a smartphone-based sensor network to newlinedetect a vehicle accident and notify to the emergency services and family. In addition to the newlinesuccessful communication and automatic vehicle accident detection, accident classification and newlineseverity assessment can be very helpful in saving the lives of accident victims. As far as automatic accident detection is concerned, two models are presented for vehicle collision detection, newlineand one model is presented for vehicle fall-off detection from an altitude. Assessing the severity newlineof a vehicle accident can pave the way to estimate the intensity of medical delivery. A model newlinehas been presented to classify the severity of a fall-off accident as mild, moderate, and severe. newlineAvailability of a vehicle accident detection and classification (ADC) system can play a vital role newlinein the commencement of a focused rescue operation with right kind of rescue equipment. A newlinecomparative evaluation of various ADC models has also been carried out to identify the best newlineperforming model among them. These models can classify the vehicle accidents as collision, newlinerollover, fall-off, and no-accident. newline | |
dc.format.extent | ||
dc.language | English | |
dc.relation | ||
dc.rights | university | |
dc.title | Vehicle Accident Detection and Classification System using Internet of Things | |
dc.title.alternative | ||
dc.creator.researcher | Kumar, Nikhil | |
dc.subject.keyword | Automation and Control Systems | |
dc.subject.keyword | Computer Science | |
dc.subject.keyword | Engineering and Technology | |
dc.description.note | ||
dc.contributor.guide | Lohani, Divya and Acharya, Debopam | |
dc.publisher.place | Greater Noida | |
dc.publisher.university | Shiv Nadar University | |
dc.publisher.institution | Department of Computer Science and Engineering | |
dc.date.registered | 2017 | |
dc.date.completed | 2022 | |
dc.date.awarded | 2022 | |
dc.format.dimensions | ||
dc.format.accompanyingmaterial | DVD | |
dc.source.university | University | |
dc.type.degree | Ph.D. | |
Appears in Departments: | Department of Computer Science and Engineering |
Files in This Item:
File | Description | Size | Format | |
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80_recommendation.pdf | Attached File | 152.58 kB | Adobe PDF | View/Open |
bibliography.pdf | 217.6 kB | Adobe PDF | View/Open | |
certificate.pdf | 505.95 kB | Adobe PDF | View/Open | |
chapter-1.pdf | 286.78 kB | Adobe PDF | View/Open | |
chapter-2.pdf | 151.14 kB | Adobe PDF | View/Open | |
chapter-3.pdf | 1.47 MB | Adobe PDF | View/Open | |
chapter-4.pdf | 1.01 MB | Adobe PDF | View/Open | |
chapter-5.pdf | 1.27 MB | Adobe PDF | View/Open | |
chapter-6.pdf | 1.14 MB | Adobe PDF | View/Open | |
chapter-7.pdf | 1.74 MB | Adobe PDF | View/Open | |
chapter-8.pdf | 116.79 kB | Adobe PDF | View/Open | |
preliminary_page.pdf | 823.03 kB | Adobe PDF | View/Open | |
title_page.pdf | 67.16 kB | Adobe PDF | View/Open |
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