Analysis and Development of IoT-based Aqua Fish Monitoring System

Water quality is critical in fish farming activities, where criteria must be measured to ensure water quality. Unwanted amounts of water quality factors will affect aquatic life. It has been discovered that some breeders fail to maintain their ponds, causing water quality to worsen and affecting fis...

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Bibliographic Details
Published in:International Journal of Emerging Technology and Advanced Engineering
Main Author: Zamzari N.Z.; Kassim M.; Yusoff M.
Format: Article
Language:English
Published: IJETAE Publication House 2022
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85141217339&doi=10.46338%2fijetae1022_20&partnerID=40&md5=a0817ee2b4dcc6bea4b22c4a17801612
id 2-s2.0-85141217339
spelling 2-s2.0-85141217339
Zamzari N.Z.; Kassim M.; Yusoff M.
Analysis and Development of IoT-based Aqua Fish Monitoring System
2022
International Journal of Emerging Technology and Advanced Engineering
12
10
10.46338/ijetae1022_20
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85141217339&doi=10.46338%2fijetae1022_20&partnerID=40&md5=a0817ee2b4dcc6bea4b22c4a17801612
Water quality is critical in fish farming activities, where criteria must be measured to ensure water quality. Unwanted amounts of water quality factors will affect aquatic life. It has been discovered that some breeders fail to maintain their ponds, causing water quality to worsen and affecting fish hibernation and mortality. Manual pond water quality testing was ineffective and time-consuming, causing the water quality to suffer. This study created a fishpond IoT system to monitor a pond's water quality, temperature, pH level, and ammonia toxicity. A real-time data analytics platform was created to collect data from the water temperature, pH level, and toxicity of ammonia sensors embedded into the IoT system. The NodeMCU ESP32 controller was used to process the data collected from all sensors, and real-time data may be viewed via mobile devices using the Blynk application. Three sensors are embedded to the system which are an ammonia gas sensor, an analog pH sensor, and a temperature probe sensor. As a result, a mobile fishpond monitoring system has been successfully created. The study reveals that the ammonia level is low at 0.021 ppm, the average temperature is 27.02°C, and the pH level is almost neutral at 6.85. It has been determined that the ammonia level is safe for fish hibernation. Temperature and pH had little effect on ammonia levels, while temperature and pH have a high association. This research is essential because it assists fish breeders in improving pond water quality, which supports aquatic life production and health. © 2022 The authors.
IJETAE Publication House
22502459
English
Article
All Open Access; Bronze Open Access
author Zamzari N.Z.; Kassim M.; Yusoff M.
spellingShingle Zamzari N.Z.; Kassim M.; Yusoff M.
Analysis and Development of IoT-based Aqua Fish Monitoring System
author_facet Zamzari N.Z.; Kassim M.; Yusoff M.
author_sort Zamzari N.Z.; Kassim M.; Yusoff M.
title Analysis and Development of IoT-based Aqua Fish Monitoring System
title_short Analysis and Development of IoT-based Aqua Fish Monitoring System
title_full Analysis and Development of IoT-based Aqua Fish Monitoring System
title_fullStr Analysis and Development of IoT-based Aqua Fish Monitoring System
title_full_unstemmed Analysis and Development of IoT-based Aqua Fish Monitoring System
title_sort Analysis and Development of IoT-based Aqua Fish Monitoring System
publishDate 2022
container_title International Journal of Emerging Technology and Advanced Engineering
container_volume 12
container_issue 10
doi_str_mv 10.46338/ijetae1022_20
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85141217339&doi=10.46338%2fijetae1022_20&partnerID=40&md5=a0817ee2b4dcc6bea4b22c4a17801612
description Water quality is critical in fish farming activities, where criteria must be measured to ensure water quality. Unwanted amounts of water quality factors will affect aquatic life. It has been discovered that some breeders fail to maintain their ponds, causing water quality to worsen and affecting fish hibernation and mortality. Manual pond water quality testing was ineffective and time-consuming, causing the water quality to suffer. This study created a fishpond IoT system to monitor a pond's water quality, temperature, pH level, and ammonia toxicity. A real-time data analytics platform was created to collect data from the water temperature, pH level, and toxicity of ammonia sensors embedded into the IoT system. The NodeMCU ESP32 controller was used to process the data collected from all sensors, and real-time data may be viewed via mobile devices using the Blynk application. Three sensors are embedded to the system which are an ammonia gas sensor, an analog pH sensor, and a temperature probe sensor. As a result, a mobile fishpond monitoring system has been successfully created. The study reveals that the ammonia level is low at 0.021 ppm, the average temperature is 27.02°C, and the pH level is almost neutral at 6.85. It has been determined that the ammonia level is safe for fish hibernation. Temperature and pH had little effect on ammonia levels, while temperature and pH have a high association. This research is essential because it assists fish breeders in improving pond water quality, which supports aquatic life production and health. © 2022 The authors.
publisher IJETAE Publication House
issn 22502459
language English
format Article
accesstype All Open Access; Bronze Open Access
record_format scopus
collection Scopus
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