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  Published Paper Details:

  Paper Title

Accident detection system using deep learning and edge computing

  Authors

  Nithyashree N,  Niveditha S,  Pramithashree KM,  Jyothi K,  Dr Suresha D

  Keywords

Edge Computing, Deep learning, CCTV, Video processing, CNN

  Abstract


- In this research, we present an innovative Accident Detection and Alert System that combines Deep Learning (DL) and Edge Computing technologies. The system is designed to process live video feeds from surveillance cameras using DL models to detect traffic accidents in real-time. By leveraging edge computing, the system performs data processing near the data source, which significantly reduces latency and enables faster response times. Upon detecting an accident, the system autonomously alerts emergency services, thereby improving the efficiency of rescue operations. This seamless integration of DL and edge computing enhances the accuracy and speed of accident detection, which is vital for reducing the severity of injuries and saving lives on the road.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2406193

  Paper ID - 263277

  Page Number(s) - b783-b787

  Pubished in - Volume 12 | Issue 6 | June 2024

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Nithyashree N,  Niveditha S,  Pramithashree KM,  Jyothi K,  Dr Suresha D,   "Accident detection system using deep learning and edge computing", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.12, Issue 6, pp.b783-b787, June 2024, Available at :http://www.ijcrt.org/papers/IJCRT2406193.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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