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DC Field | Value | Language |
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dc.contributor.author | Rachana V V | - |
dc.contributor.author | Jinu, A, (Guide) | - |
dc.date.accessioned | 2025-05-12T06:12:45Z | - |
dc.date.available | 2025-05-12T06:12:45Z | - |
dc.date.issued | 2025 | - |
dc.identifier.uri | http://14.139.181.140:8080/xmlui/handle/123456789/2062 | - |
dc.description.abstract | This study developed and implemented an IoT-based automated aquaponics system designed to optimize water quality management and reduce manual intervention. The aquaponics system utilized a NFT grow bed, with a 1:2 ratio between the fish tank and grow bed size. 500 L fish tank was selected to accommodate 25 fishes, and a 1 m2 grow bed area was used for 48 plants. To ensure a sustainable nutrient cycle, a filter was installed to convert fish waste ammonia into nitrate, which serves as a vital nutrient for plant growth. Water was circulated using a pump with a head height of 2.7 m, and actuators were employed to regulate critical parameters such as pH, temperature, EC, and DO. IoT technology was integrated into the system to monitor water quality parameters. IoT sensors continuously monitored the critical water parameters which are essential for the health of fish and plants. A PIC microcontroller facilitated automated data acquisition, transmitting real-time data via a GSM module to the ThingSpeak cloud platform. Based on predefined thresholds, automatic adjustments were made through solenoid valves, aerators, and pH regulators to maintain optimal conditions. Alerts were also sent to the user's smartphone when abnormal values were detected. Over a three month period, the system effectively maintained water quality within the optimal ranges (DO >5.5 mg L-1, pH 6.5-7.5, temperature 22-32°C and EC <2 dS cm-1), ensuring a stable environment for both fish and plant growth. Despite fluctuations in water quality due to fish respiration and excretion, the automated system consistently managed to prevent fish mortality and ensured efficient nutrient absorption by plants. The aquaponics system achieved a total fish yield of 5.198 kg and a plant yield of 9.57 kg, demonstrating the effectiveness of the automated system. Hence, it is concluded that, the IoT based real time monitoring and control significantly improved water efficiency, reduced human error, and enhanced the alignment of fish and plant growth. This scalable and sustainable aquaponics system offers a promising solution for integrated farming practices, contributing to future food security and resource-efficient agriculture. | en_US |
dc.publisher | Department of Soil and Water Conservation Engineering | en_US |
dc.relation.ispartofseries | M.Tech;T 643 | - |
dc.title | Development Of IoT based automated aquaponics system for water quality monitoring and control | en_US |
dc.type | Thesis | en_US |
Appears in Collections: | Thesis-SWCE |
Files in This Item:
File | Description | Size | Format | |
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01_title-1.pdf | 61.11 kB | Adobe PDF | View/Open | |
02_prelim pages.pdf | 411.31 kB | Adobe PDF | View/Open | |
03_content.pdf | 21.71 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 238.81 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 144.28 kB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 240.85 kB | Adobe PDF | View/Open | |
07_chapter 3.pdf Restricted Access | 2.67 MB | Adobe PDF | View/Open Request a copy | |
08_chapter 4.pdf Restricted Access | 2.46 MB | Adobe PDF | View/Open Request a copy | |
09_chapter 5.pdf Restricted Access | 108.99 kB | Adobe PDF | View/Open Request a copy | |
10_references.pdf | 190.85 kB | Adobe PDF | View/Open | |
80_recommendations.pdf | 2.5 MB | Adobe PDF | View/Open |
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