Iots Water Quality Monitoring System

Full of technology a new emerging technology IoT playing an important role in making our life easier with the help of sensors, that allows device communication possible. IoT make everything thing smart from personal to professional life. IoT saves time and money and allow automation and control. Wat

Project Title

Iots Water Quality Monitoring System

Project Area of Specialization

Internet of Things

Project Summary

Full of technology a new emerging technology IoT playing an important role in making our life easier with the help of sensors, that allows device communication possible. IoT make everything thing smart from personal to professional life. IoT saves time and money and allow automation and control. Water is most important component for life because water is life, without water life is impossible. With rapid growth in population and factories polluting the environment with harmful chemicals, gases, exhaust substances and other destructive particles. All these contaminate the water that affects the human health badly. Smart Water Quality Monitoring System using IoT is developed using IoT to test the quality of drinking water; excellent, good and poor to avoid the water diseases. For this, three water parameters are monitored using pH, turbidity and temperature sensor with Arduino UNO microcontroller to read the values from the sensors. Later we need to store this data, to save it we use PLX- DAQ to save the sensed data into excel sheet. To make our system smart, a supervised learning machine algorithm; Decision Tree make the system intelligent. Decision tree working based on information gain and gain ratio. This is achieved by using RapidMiner tool, in which different operators are used to train and built the decision tree. After the training and testing the implemented system gives 90.24% accuracy to check the drinking water quality.

Project Objectives

Overuse of water and rapidly growing populace leads world to lack of water and on the other side human activities are the reason of million people’s deaths every year because the usage of contaminated water. Due to this serious problem, there is need a system to real time monitor the water quality properly. Through the Smart Water Quality Monitoring System using IoT, we can overcome the problem by taking earlier steps towards contamination and scarcity of water:

1. A system for real time monitoring to ensure drinking water quality

1. A system for measuring water quality parameters (turbidity, temperature and pH) in a cost- effective way through user friendly method.

1. To design and develop a system to overcome health hazards and give alert message of increasing pollution levels.

1. Make easy access of water quality data through mobile application for people.

1. It can be used for commercial and domestic purpose.

Project Implementation Method

We are using ML algorithm for the classification of quality to make our system intelligent. In the existing researches, they use costly sensors for measuring the quality of water.

This system is comprised of three basic units: data collection, data transmission, machine learning algorithm and final trained model. In data collection, we use three sensors pH, turbidity & temperature with other hardware components to read and collect the data. Machine learning algorithm that is used for learning is decision tree. After the implementation of trained model is testing to unknown values to identify the quality of water.

Sensors:

pH sensor is used to check the water is basic or acidic, turbidity to check the clarity of water and last one temperature sensor is used to check the water temperature and it is very important parameter because it effects the above two sensors values.

1. Data Collection:

Data is collected from different water samples or including other solutions into it with the help of above three sensors using Arduino. In this system, we collected 110 instances of Excellent, 110 instances for Good and 110 for Poor water quality.

2. Data Processing:

For data processing, it is necessary that the data is in a proper format that is accepted by the tool we are using. Data is collected with of Arduino using sensors but that data is shown is serial monitor. To the transmission of data is performed using PLX-DAQ that transferred sensed data into excel sheet, through this we can save it and use for data processing.

3. Data Cleansing:

Data cleansing is used to normalize the collected data. We normalize each attribute value by handing raw, missing, incomplete or duplicate values. For example, the range of pH is 0 – 14, so in cleansing we make sure that the pH value not exceed from that range like that turbidity value not cross the limit value 5.

4. Data Analysis:

In data analysis, some validation methods are applied on the dataset for processing of data. We use decision tree algorithm for classification of water quality. Also, we find the information gain and gain ratio of each attribute to split the data.

4. ML Algorithm:

In this project, we use one of the common Machine Learning Algorithm that is Decision Tree. Decision Tree is just like a tree model that uses decision analysis, it creates a tree model that predicts the target (unknown) data for the classification of water quality.

6. Data Prediction:

After the development of decision tree algorithm tree, the trained decision tree model is applied to test dataset to predict the class of the water and shows the accuracy of the model.

Benefits of the Project

Smart water quality monitoring system is efficient and performed well. We built the decision tree on the classes of water i.e. excellent, good, poor on three parameters of water, pH, temperature & turbidity.

• Physical conditions such as temperature, erosion and flow offer valuable insight while biological measurements regarding plant and animal life indicate the health of aquatic ecosystems. At the end of the day, water quality monitoring is an essential part of keeping the planet healthy and sustainable.

• With the World Water Assessment Programme reporting that every day a staggering two million tons of human waste is disposed into water courses, keeping tabs on quality is critical! At its core, the practice serves five major purposes. Results are used to pinpoint any changes or trends that appear in water bodies over a period of time. These can be short of long term developments.

  Regularly monitoring water quality is a crucial part of identifying any existing problems, or any issues that could emerge in the future. 

Technical Details of Final Deliverable

The main idea and objective of this project was to check the quality of drinking water by measuring quality parameter of the water and that was achieved successfully through IoT technology using sensors pH, turbidity and temperature. This thesis consists of the detail of the work done in this project and how we did it. It includes the sensors, microcontroller used in this project. System architecture of the smart water quality monitoring system is given and the how to create the connections between them a full fledge summary of interface with Arduino and how PC get the values through them is provided. And the result can be seen at the serial monitor or at excel sheet with the help of PLX-DAQ with the read values of turbidity, pH and temperature. In this thesis, we perform the calibration of the sensors to achieve the accuracy. We perform some of the tests using different liquid solution to check that the parameters are working correctly or not. After the satisfaction of the sensor we put the sensors into different water sample in different temperatures to get the dataset.

The pH and temperature shown the values as they are expected in their ranges and unit, pH unit and degree Celsius unit respectively: but turbidity is not designed to show the actual turbidity value in NTU, so we measure the turbidity in the form of voltage and provide the relationship between them. To make our system intelligent a supervised learning algorithm decision tree is used that works on gain ratio that choose high weighted feature to split the tree. This project is successfully implemented and tested to check the quality of water, it is used as in testing and training and shown 90.24 accuracy. The overall information of each hardware or software used are given.

Finally, we successfully conduct our research through measuring the quality of drinking water using standard parameters pH, temperature and turbidity that is easy, low cost and automatic.

Final Deliverable of the Project

HW/SW integrated system

Core Industry

IT

Other Industries

Food

Core Technology

Internet of Things (IoT)

Other Technologies

Artificial Intelligence(AI)

Sustainable Development Goals

Clean Water and Sanitation

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com