IoT based Water Quality Monitoring System Architecture

This page describes IoT based Water Quality Monitoring System Architecture for lake, river and other water bodies. It mentions disadvantages of manual method and nodal network method and advantages of IoT based water quality monitoring system.

Introduction:
Water quality is deteriorating due to various environment changes and man made pollution. As a result, it has become essential to measure quality of the water at various water bodies. This helps in reducing water pollution and consecutively in saving aquatic life.

To monitor the quality of the water at regular interval of time, following methods are used.
• Manual Method
• Nodal network method
• IoT (Internet of Things) method

Manual Method of water quality monitoring

In manual method, water samples are collected manually from different parts of the water body. The collected water samples are sent to the laboratory for analysis of various parameters such as pH, dissolved oxygen, conductivity, chloride content and so on.

The limitations or drawbacks or disadvantages of manual method are as follows.
➤It is difficult to collect the water samples from all the area of the water body.
➤The cost of analysis is very high.
➤The lab testing and analysis takes some time and hence the lab results does not reflect real time water quality measurement due to delay in measurement.
➤The process is time consuming due to slow process of manual data collection from different locations of the water body.
➤The method is prone to human errors of various forms.

Nodal network method of water quality monitoring

In this method, wireless sensor nodes are installed at various regions of a river. The data collection is carried out by these sensors and uploaded to cloud storage using internet. The location of sensors and their position inside the water is fixed by the analysis team initially itself.

The limitations or drawbacks or disadvantages of Nodal network method are as follows.
➤The system is less effective as sensors are installed very deep inside the water and their positions are fixed.
➤The sensors are very expensive. Moreover their maintenance cost is also very high. This leads to higher cost on the regulatory body.
➤The sensors which work on power source may often required to be replaced in case of malfunctioning.
➤Mounted Sensors may get damage during natural disasters and often by aquatic animals.

IoT based Water Quality Monitoring System

IoT based water quality monitoring system

➤In IoT based method water boat housing ESP32 board with water sensors is used. ESP32 consists of wifi and bluetooth functionalities. In order to avail GSM/GPRS functionality in the system, GSM/GPRS board (SIM800A) is interfaced with ESP32 using UART interface. In case of Arduino Uno other than GSM board one has to interface wifi/BLE module also as arduino does not house wifi or BLE chip.
➤Water sensor kit consists of many sensors used to measure water quality. These include pH sensor, temperature sensor, conductivity sensor, dissolved oxygen sensor and so on.
➤The data collected by sensors from various locations of the water body such as river or lake are uploaded to cloud storage server using wifi or GSM.
➤The data are being analyzed using machine learning techniques and appropriate reports are being generated in different formats.
➤End users of the system can monitor the reports and results of water samples collected from various locations using mobile or web app developed. GPS coordinates of the collected samples are also integrated in the reports to understand level of contamination at particular locations.

Benefits or Advantages of IoT based Water Quality Monitoring System

Following are the benefits or advantages of IoT based Water Quality Monitoring System are as follows.
➤The boat is mobile in nature and hence large number of samples are easily collected from different locations in less time.
➤It is very easy to maintain the IoT based water quality monitoring system as all the electronic boards are available in the boat itself.
➤The system is very cheap as the hardware and software does not cost much.
➤Machine learning techniques have made it very easy to plot the data collected in various formats for proper analysis.
➤Cloud storage platforms such as adafruit, azure helps in storing the sensor data immediately and wirelessly to the robust servers.

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