Date of Publication

8-14-2023

Document Type

Bachelor's Thesis

Degree Name

Bachelor of Science in Computer Science Major in Computer Systems Engineering

Subject Categories

Computer Sciences

College

College of Computer Studies

Department/Unit

Computer Technology

Thesis Advisor

Macario O. Cordel, II

Defense Panel Chair

Joel P. Ilao

Defense Panel Member

Judith J. Azcarraga
Jonathan Paul C. Cempron

Abstract/Summary

Shrimp is one of the most important export products of the Philippines, accounting for 20.5% of the country’s exports in aquaculture. Diseases with a high mortality rate, such as the White Spot Syndrome Virus (WSSV), pose a severe risk to the profitability and production of these shrimp farms. Early detection and diagnosis are critical to the rising problem of WSSV outbreaks. Current microbiological methods to detect WSSV require farm managers to bring a shrimp sample to a laboratory. However, because they rely on traditional knowledge and experience, some farm managers are unaware of the symptoms shrimp exhibit after viral infection. This scenario could delay proper disease management or even failure to report suspicion of infection, possibly causing a disease outbreak within the vicinity of the farm. The use of mobile devices has been shown to be effective in disease monitoring and surveillance. It is critical to investigate the role of image-based recognition for preliminary diagnosis at the community level, such as farm managers on-site, in improving the reporting of WSSV. Thus, this research aims to create a mobile application that allows farm managers to identify the potential presence of WSSV.

Abstract Format

html

Language

English

Format

Electronic

Physical Description

71 leaves

Keywords

Shrimps--Diseases; Mobile apps; Animal health surveillance

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Embargo Period

8-14-2024

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Available for download on Wednesday, August 14, 2024

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