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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Issue: March 2026
Volume 11 | Issue 3
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
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| Paper Title: | IOT-Based Underwater Ecosystem For Pisciculture Monitoring System |
| Authors Name: | k. Krishna prasad , k. Sree Akarsh , k. Naresh Kumar Thapa |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_201861
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| Published Paper Id: | IJRTI2503233 |
| Published In: | Volume 10 Issue 3, March-2025 |
| DOI: | |
| Abstract: | The sustainability and productivity of pisciculture are significantly influenced by water quality, as it directly impacts fish health, growth rates, and overall aquatic ecosystem balance. This paper presents the design and implementation of an Internet of Things (IoT)-based water monitoring system aimed at enhancing the management and optimization of water conditions in pisciculture. The proposed system utilizes a network of sensors to continuously monitor key parameters such as pH, temperature, and Turbidity in real time. These parameters serve as critical indicators of water quality, and their fluctuations can lead to adverse effects on fish health and yield. By integrating IoT technology, the system enables seamless data processing and analysis, allowing fish farmers to make informed and proactive decisions. Pisciculture plays a significant role in the aquaculture industry, requiring precise environmental monitoring to ensure optimal fish growth and yield. This paper presents an IoT-based monitoring system integrating various sensors to measure critical water parameters such as Temperature, pH, Turbidity, Ammonia and Total dissolved solids (TDS). The system leverages Arduino Uno for data processing and GSM technology for cloud communication, enabling real-time monitoring and control through a mobile application. The proposed system ensures optimal water quality conditions, reducing fish mortality and improving yield efficiency. The implementation includes cloud based data storage and real-time alert mechanisms that notify users of any deviations from optimal water conditions, thereby minimizing risks associated with water quality deterioration. The results demonstrate the system’s capability to maintain water quality within optimal thresholds, reducing the likelihood of fish mortality and improving overall operational efficiency. |
| Keywords: | Ammonia sensor, Pisciculture, Sensors, GSM technology, Real-time Data Processing, motor |
| Cite Article: | "IOT-Based Underwater Ecosystem For Pisciculture Monitoring System", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 3, page no.c218-c222, March-2025, Available :http://www.ijrti.org/papers/IJRTI2503233.pdf |
| Downloads: | 000641 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2503233
Registration ID:201861
Published In: Volume 10 Issue 3, March-2025
DOI (Digital Object Identifier):
Page No: c218-c222 Country: Chennai, Tamil Nadu, India Research Area: Electronics & Communication Engg. Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2503233 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2503233 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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