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All Journal Bulletin of Electrical Engineering and Informatics
Wahjoe Tjatur Sesulihatien
Politeknik Elektronika Negri Surabaya
Electrical & Electronics Engineering

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Mobile sensing in Aedes aegypti larva detection with biological feature extraction Dia Bitari Mei Yuana; Wahjoe Tjatur Sesulihatien; Achmad Basuki; Tri Harsono; Akhmad Alimudin; Etik Ainun Rohmah
Bulletin of Electrical Engineering and Informatics Vol 9, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (656.868 KB) | DOI: 10.11591/eei.v9i4.1993

Abstract

According to WHO, Dengue fever is the most critical and most rapidly mosquito-borne disease in the world over 50 years. Currently, the presence and detection of Aedes aegypti larvae (dengue-mosquitoes vector’s) are only quantified by human perception. In large-scale data, we need to automate the process of larvae detection and classification as much as possible. This paper introduces the new method to automate Aedes larvae. We use Culex larva for comparison. This method consists of data acquisition of recorded motion video, spatial movement patterns, and image statistical classification. The results show a significant difference between the biological movements of Aedes aegypti and Culex under the same environmental conditions. In 50 videos consisting of 25 Aedes larvae videos and 25 Culex larvae videos, the accuracy was 84%.
Co-Authors Achmad Basuki Akhmad Alimudin Dia Bitari Mei Yuana Etik Ainun Rohmah Tri Harsono