Smart Monitoring System and Early Warning Water Level ―SMOORTY‖ using Raspberry Pi Technology

Chouwanto, Edward Arlis; Wongso, Rini; Yesmaya, Violitta

doi:10.46338/ijetae1221_18

Cited by 1 publication

(1 citation statement)

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“…Based on [15], they monitor the water's temperature, turbidity, pH level, dissolved oxygen, and conductivity. The hardware design used was the Raspberry PI B+ as a core controller.…”

Section: A Water Quality Monitoringmentioning

confidence: 99%

Analysis and Development of IoT-based Aqua Fish Monitoring System

Zamzari¹,

Kassim²,

Yusoff³

2022

IJETAE

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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. Keywords—water quality monitoring, ammonia, Internet of Things, ESP32, pH, temperature

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“…Based on [15], they monitor the water's temperature, turbidity, pH level, dissolved oxygen, and conductivity. The hardware design used was the Raspberry PI B+ as a core controller.…”

Section: A Water Quality Monitoringmentioning

confidence: 99%