Automated Vision Based Surveillance System To Detect Drowning Activities

Registration ID: IJNRD_196236

Published ID: IJNRD2305709

DOI: Click Here to Get

Aryan Bisht , Dr. Chhaya Dalela , Abhishek Rawat , Ankur Sood

Raspberry pi, Drowning Detection, Alert System,Real -Time image processing

Nowadays drowning incidents are growing at significant level. In spite of the fact that there have been different guidelines established to decrease suffocating mishaps in certain nations, networks actually experience many suffocating occurrences. A framework is proposed to distinguish the suffocating exercises and forestall it utilizing PC vision and AI methods. Raspberry Pi, a Pixy camera, a hooter, a power source, a drive, and other components make up the framework. The device then warns the lifeguards after being discovered. An experiment has been developed, carried out, and tried in order to evaluate the presentation of the suggested framework. Test results show that the framework has an intriguing ability to screen and follow swimmers, which enables it to reduce and regulate the number of passings by smothering.

Published Paper   E-Certificate

Aryan Bisht, Dr. Chhaya Dalela, Abhishek Rawat, & Ankur Sood (May-2023). Automated Vision Based Surveillance System To Detect Drowning Activities. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(5), h68-h70. https://ijnrd.org/papers/IJNRD2305709.pdf

Volume 8 Issue 5, May-2023

Pages : h68-h70

Paper Reg. ID: IJNRD_196236

Published Paper Id: IJNRD2305709

Downloads: 000121980

Research Area: Electronics & Communication Engg. 

Country: New delhi, DELHI, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2305709.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2305709

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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