000			02718nam a22002417a 4500
003			FT8853
005			20251205142113.0
008			251205b ||||| |||| 00| 0 eng d
041			_aengtag
050			_aT58 B45 2025
082			_a.
100	1		_aBejar, Maria Angeline B.; Gazzingan, Kylie Ann B.; Suarez, Niño Denzel C.
245			_aIoT enabled water tank monitoring for sustainable tilapia farming program using recirculating aquaculture system (RAS)
264		1	_a. _b. _cc2025
300			_bCapstone Project: (Bachelor of Science in Information Technology) - Pamantasan ng Lungsod ng Maynila, 2025
336			_2text _atext _btext
337			_2unmediated _aunmediated _bunmediated
338			_2volume _avolume _bvolume
505			_aABSTRACT: The goal of the study is to accomplish a Recirculating System (RAS) in a small-scale water tank setup for sustainable backyard/indoor fish farming for Nile tilapia fingerlings with alignment to Internet of Things (IoT) technology. The system improved water usage through filtration and reuse, maintaining ideal conditions for tilapia fingerlings. Several IoT components were used including MQ-135 Gas sensor for ammonia detection, DS18B20 Temperature sensor and PH-4502C Liquid PH-Sensor for monitoring. Also, the study featured automatic heating, cooling and aeration systems, and an automated feeding using DS1307 Real-Time Clock and servo motor. Early warning signs have been developed for real-time weather forecasting through the help of Open Weather API. These technologies work together to maintain optimal water conditions, ensure consistent feeding and adapt to weather changes, enhancing fish health and growth while conserving water. The implementation of this IoT-enhanced RAS addresses several critical challenges in small-scale aquaculture. By creating a closed-loop system, water usage reduced by approximately 90-95% compared to traditional flow-through systems, making fish farming viable in water-scarce regions. The automated monitoring system continuously tracks key water parameters (temperature, pH, ammonia levels) and triggers appropriate responses when values deviate from optimal ranges (26-300C for temperature, 6.5-8.0 for pH, and <0.05 ppm for ammonia). This reduces the risk of sudden mortality due to poor water quality while minimizing the need for constant human supervision. Furthermore, the system integrates real-time data analytics, allowing farmers to make informed decisions and optimize fish growth conditions efficiently. The use of IoT connectivity enables remote monitoring and control, ensuring timely interventions even when farmers are off-site
526			_aF
655			_aacademic writing
942			_2lcc _cMS
999			_c37288 _d37288