Design and development of a database management system for aquatic research data

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Published: 2025-05-20
DOI: https://doi.org/10.70102/f9q8dg34
Keywords:
Computer-based information, Databases, Database management system

Main Article Content

Prerak Sudan
Centre of Research Impact and Outcome, Chitkara University, Rajpura, Punjab, India.
Aitha Srividya
Centre for Multidisciplinary Research, Anurag University, Hyderabad, Telangana, India.
Dr. Thiru Chitrambalam M
Professor, ISME, ATLAS SkillTech University, Mumbai, Maharashtra, India.
Dr. Prince Mary S
Professor, Department of Computer Science and Engineering, Sathyabama Institute of Science and Technology, Chennai, India.
Dr. Suman Sau
Associate Professor, Department of Computer Science and Information Technology, Siksha 'O' Anusandhan (Deemed to be University), Bhubaneswar, Odisha, India.
Dr. Murugan R
Professor, Department of CS & IT, Jain (Deemed-to-be University), Bangalore, Karnataka, India.
Dr. Awakash Mishra
Professor, Maharishi School of Engineering & Technology, Maharishi University of Information Technology, Uttar Pradesh, India.

Abstract

Enhancing and digitising aqua farming requires a framework for collecting databases and continuous observing of numerous functional parts of water cultivating. The security and development of customary aquatic cultivating, particularly in precipitous locales with supportable advancement objectives, can benefit from the application of cutting-edge technology that enable data collecting and real-time monitoring. The aqua resources' geotagging and geomapping will be crucial for tracking the species in the amphibian climate. These innovations can follow the wellbeing, position, and development of aquatic species in real time, as well as their feeding habits. Using geographical data, this study suggested an IoT-based architecture for managing the aqua resource for environmental sustainability. The development of a data set for water asset the executives and the electronic system for the fisheries industry based on geoinformation systems (GIS) and geopositioning systems (GPS) were also included in this study. The findings of the fishpond in the cloud server and the database creation for water asset the executives are point by point in the review. The framework incorporates machine learning (ML) to examine sensor and geospatial data in order to detect any deterioration in the quality of the water. This would give policymakers up-to-date information for crucial decisions on the continued development of aquatic species to boost the state's economy and aqua farmers' livelihoods.

Article Details

Issue

Volume 5, Issue 1 (January-June), 2025

Section

Articles

How to Cite

Design and development of a database management system for aquatic research data (P. Sudan, A. Srividya, D. T. C. M, D. P. M. S, D. S. Sau, D. M. R, & D. A. Mishra, Trans.). (2025). International Journal of Aquatic Research and Environmental Studies, 5(1), 215-220. https://doi.org/10.70102/f9q8dg34

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