About | Contact Us | Register | Login
ProceedingsSeriesJournalsSearchEAI
IoT 24(1):

Research Article

An IoT Integrated Smart Prediction of Wild Animal Intrusion in Residential Areas Using Hybrid Deep Learning with Computer Vision

Download95 downloads
Cite
BibTeX Plain Text
  • @ARTICLE{10.4108/eetiot.4976,
        author={Senthil G. A. and R Prabha and N Aishwarya and R M Asha and S Prabu},
        title={An IoT Integrated Smart Prediction of Wild Animal Intrusion in Residential Areas Using Hybrid Deep Learning with Computer Vision},
        journal={EAI Endorsed Transactions on Internet of Things},
        volume={10},
        number={1},
        publisher={EAI},
        journal_a={IOT},
        year={2024},
        month={1},
        keywords={Deep Learning, Internet of Things, Prediction, DenseNet 201, ResNet50 Algorithm, You Only Look Once, YOLO Algorithm, Rectified Linear Unit, ReLU},
        doi={10.4108/eetiot.4976}
    }
    
  • Senthil G. A.
    R Prabha
    N Aishwarya
    R M Asha
    S Prabu
    Year: 2024
    An IoT Integrated Smart Prediction of Wild Animal Intrusion in Residential Areas Using Hybrid Deep Learning with Computer Vision
    IOT
    EAI
    DOI: 10.4108/eetiot.4976
Senthil G. A.1,*, R Prabha2, N Aishwarya2, R M Asha2, S Prabu3
  • 1: Agni College of Technology
  • 2: Sri Sai Ram Institute of Technology
  • 3: SRM Institute of Science and Technology
*Contact email: senthilga@gmail.com

Abstract

INTRODUCTION: The conversion of forests into human lands causes the intrusion of wild animals into the residential area. There is a necessity to prevent the intrusion of such wild animals which causes damage to properties and harm or kill humans. Human population growth leads to an increase in the exploitation of forest areas and related resources for residential and other settlement purposes. There is a need for a system to detect the entry of such animals into habitats. OBJECTIVES: This paper proposes that conversion of forests into human lands causes the intrusion of wild animals into the residential area. METHODS: Deep learning technology combined with Internet of Things (IoT) devices can be deployed in the process of restricting the entry of wild animals into residential areas. The proposed system uses deep learning techniques with the use of various algorithms like DenseNet 201, ResNet50 and You Only Look Once (YOLO). These deep-learning algorithms predict wild animals through image classification. This is done using IoT devices placed in such areas. The role of IoT devices is to transmit the computer vision images to the deep learning module, receive the output, and alarm the residents of the area. RESULTS: The main results are implementation prediction of animals for image processing Datasets used for the prediction and classification indulge the use of cloud modules. It stores the dataset for the prediction process and transfers it whenever needed. As the proposed system is a hybrid model that uses more than one algorithm, the accuracy obtained from the prediction for DenseNet 201, ResNet50 and You Only Look Once (YOLO) algorithm is 82%,92%, and 98%. CONCLUSION: The prediction of those animals is done by a deep learning model which comprises three algorithms are DenseNet 201, ResNet50 and YOLOv3. Comparing the accuracy of an algorithm with higher accuracy is considered efficient and accurate.

Keywords
Deep Learning, Internet of Things, Prediction, DenseNet 201, ResNet50 Algorithm, You Only Look Once, YOLO Algorithm, Rectified Linear Unit, ReLU
Received
2023-11-08
Accepted
2024-01-20
Published
2024-01-30
Publisher
EAI
http://dx.doi.org/10.4108/eetiot.4976

Copyright © 2024 Senthil G. A. et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.

EBSCOProQuestDBLPDOAJPortico
EAI Logo

About EAI

  • Who We Are
  • Leadership
  • Research Areas
  • Partners
  • Media Center

Community

  • Membership
  • Conference
  • Recognition
  • Sponsor Us

Publish with EAI

  • Publishing
  • Journals
  • Proceedings
  • Books
  • EUDL