An Optimal Internet of Things-Driven Intelligent Decision-Making System for Real-Time Fishpond Water Quality Monitoring and Species Survival.

ABSTRACT: Smart fish farming faces critical challenges in achieving comprehensive automation, real-time decision-making, and adaptability to diverse environmental conditions and multi-species aquaculture. This study presents a novel Internet of Things (IoT)-driven intelligent decision-making system that dynamically monitors and optimizes water quality parameters to enhance fish survival rates across various regions and species setups. The system integrates advanced sensors connected to an ESP32 microcontroller, continuously monitoring key water parameters such as pH, temperature, and turbidity which are increasingly affected by climate-induced variability. A custom-built dataset comprising 43,459 records, covering ten distinct fish species across diverse pond environments, was meticulously curated.

SUBMITTER: Kanwal S 

PROVIDER: S-EPMC11644897 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature