A Smart Approach Towards Reliable Disaster Detection System Using YOLO-V5
Mukundan.A.S
, J. Koushik Ram , R. Rakeshwaran , Mr. R. Arunkumar
Natural hazards, Internet of Things, Artificial Intelligence, Disaster detection, Cognitive analysis.
In recent years the number of natural disasters happening in the country is kept increasing. Landslides are considered as one of the major natural disasters happening in the country leading to major human life losses comparing with other disasters. The reason behind the landslide is due to continuous degradation in the environmental resources. Accurate prediction and mitigation strategies are important to understand an create awareness to the people around the mountains. The presented system is focused on creating an effective framework which detects the landslide scenarios in the early stages through YOLOv5 as the primary model. The presented study focused on deep learning based automated landslide detection using satellite images and aerial images. YOLOv5 is one of the advanced architectures consists of in-built convolution layers. The landslide starts with unique features such as debris flow, falling of massive rocks, sudden changes in the surface of the mountains, failures in slopes etc. The proposed approach considers reliable dataset which holds various real time images of landslides enhances the quality of training process involved in YOLOv5 model. By interfacing real time datasets to the models, the quality of prediction is getting enhanced. The scalability of the system is increased through massive dataset collection. The presented system is designed as lightweight cloud configurable model with high accuracy and data speed for communication. It provides valuable alerts towards landslides and major disasters comparing with geospatial analysis.
"A Smart Approach Towards Reliable Disaster Detection System Using YOLO-V5", TIJER - TIJER - INTERNATIONAL RESEARCH JOURNAL (www.TIJER.org), ISSN:2349-9249, Vol.12, Issue 4, page no.b284-b291, April-2025, Available :https://tijer.org/TIJER/papers/TIJER2504176.pdf
Volume 12
Issue 4,
April-2025
Pages : b284-b291
Paper Reg. ID: TIJER_157671
Published Paper Id: TIJER2504176
Downloads: 000271
Research Area: Science and Technology
Country: Chennai, Tamil Nadu, India
ISSN: 2349-9249 | IMPACT FACTOR: 8.57 Calculated By Google Scholar | ESTD YEAR: 2014
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.57 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: TIJER (IJ Publication) Janvi Wave
