MosquitoMiner: A Light Weight Rover for Detecting and Eliminating Mosquito Breeding Sites

In this paper, we present a novel approach to the development and deployment of an autonomous mosquito breeding place detector rover with the object and obstacle detection capabilities to control mosquitoes. Mosquito-borne diseases continue to pose significant health threats globally, with conventional control methods proving slow and inefficient. Amidst rising concerns over the rapid spread of these diseases, there is an urgent need for innovative and efficient strategies to manage mosquito populations and prevent disease transmission. To mitigate the limitations of manual labor and traditional meth-ods, our rover employs autonomous control strategies. Leveraging our own custom dataset, the rover can autonomously navigate along a pre-defined path, identifying and mitigating potential breeding grounds with precision. It then proceeds to eliminate these breeding grounds by spraying a chemical agent, effectively eradicating mosquito habitats. Our project demonstrates the effectiveness that is absent in traditional ways of controlling and safeguarding public health. The code for this project is available on GitHub at -https://github.com/faiyazabdullah/MosquitoMiner

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Publication Details

Published
2024-09-27
DOI
https://doi.org/10.1109/tensymp61132.2024.10752222
Primary Topic
Mosquito-borne diseases and control
Type
article
Field-Weighted Citation Impact
0.00
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article

MosquitoMiner: A Light Weight Rover for Detecting and Eliminating Mosquito Breeding Sites

Jannatul Ferdous Deepti, Md. Faiyaz Abdullah Sayeedi, Safrin Sanzida Islam, Md. Adnanul Islam et al.
Mosquito-borne diseases and control
article

MosquitoMiner: A Light Weight Rover for Detecting and Eliminating Mosquito Breeding Sites

Jannatul Ferdous Deepti, Md. Faiyaz Abdullah Sayeedi, Safrin Sanzida Islam, Md. Adnanul Islam, Fahim Hafiz, Shahanur Rahman Bappy
article en

Abstract

In this paper, we present a novel approach to the development and deployment of an autonomous mosquito breeding place detector rover with the object and obstacle detection capabilities to control mosquitoes. Mosquito-borne diseases continue to pose significant health threats globally, with conventional control methods proving slow and inefficient. Amidst rising concerns over the rapid spread of these diseases, there is an urgent need for innovative and efficient strategies to manage mosquito populations and prevent disease transmission. To mitigate the limitations of manual labor and traditional meth-ods, our rover employs autonomous control strategies. Leveraging our own custom dataset, the rover can autonomously navigate along a pre-defined path, identifying and mitigating potential breeding grounds with precision. It then proceeds to eliminate these breeding grounds by spraying a chemical agent, effectively eradicating mosquito habitats. Our project demonstrates the effectiveness that is absent in traditional ways of controlling and safeguarding public health. The code for this project is available on GitHub at -https://github.com/faiyazabdullah/MosquitoMiner

United International University (BD)
Openalex Percentile: Top 68%
Mosquito-borne diseases and control
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