| dc.description.abstract | This project report presents the development and implementation of a fish pond condition monitoring system (FPCMs) which incorporates pH, temperature, and turbidity sensors to collect real-time data. The data is then displayed on a web page in the form of line graphs to visualize the correlation between these environmental factors and changes in oxygen levels thereafter sending alerts to the user when critical oxygen levels are detected. The objective of this project was to create a flexible and efficient monitoring system that can help fish farmers worldwide maintain optimal conditions in their ponds thereby ensuring the well-being of their fish stock and overall increase in productivity. While implementing, we used an Arduino board which served as the main controller unit together with the pH, temperature, and turbidity sensors.
The FPCMS demonstrated in this project offers several advantages over traditional manual monitoring methods by providing real-time data collection, continuous monitoring, and immediate alerts, allowing fish farmers to address potential issues promptly. By maintaining optimal water quality parameters, fish farmers can enhance fish health, growth, and overall productivity.
Future enhancements to the system could include additional sensors for monitoring other crucial parameters, such as ammonia and nitrate levels, as well as automated recommendations to make the system more efficient. | en_US |
