• P.Venkateswarlu
• Sk.Shahil
• B.Sree Latha
• G.Himabindu
• Sk.shafi

IoT-Based Smart Bio floc Monitoring System for Fish Farming Using Machine Learning is designed to optimize aquaculture by continuously monitoring key water quality parameters in real-time. Using a Raspberry Pi as the central controller, the system integrates sensors including pH, temperature (Dallas temperature), turbidity, and TDS to assess water conditions in a fish farming environment. The collected data is processed and analyzed using machine learning algorithms, providing predictive insights into the health of the bio floc system. A relay module is incorporated to control a water pump based on sensor readings, ensuring automated water quality management. Alerts are sent via a GSM module when abnormal readings are detected, while a buzzer provides immediate notifications. Additionally, an LCD displays real-time data and system status, enabling farmers to make informed decisions. By leveraging IoT and machine learning, this system enhances decision-making, promotes healthier fish farming practices, and ensures a sustainable aquatic ecosystem through timely interventions and automated water quality optimization.

"IOT Based Smart Biofloc Monitoring System For Fish Farming Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 4, page no.l699-l701, April-2025, Available :http://www.jetir.org/papers/JETIR2504B86.pdf

"IOT Based Smart Biofloc Monitoring System For Fish Farming Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 4, page no. ppl699-l701, April-2025, Available at : http://www.jetir.org/papers/JETIR2504B86.pdf