WATER QUALITY MONITORING SYSTEM WITH IOT

ROSE NEEZAR BIN ROSE ZAIDI

UNIVERSITI TEKNOLOGI MALAYSIA

WATER QUALITY MONITORING SYSTEM WITH IOT

ROSE NEEZAR BIN ROSE ZAIDI

A project report submitted in partial fulfilment of the

requirements for the award of the degree of

Master of Engineering (Mechatronics and Automatic Control)

Faculty of Electrical Engineering

Universiti Teknologi Malaysia

JUNE 2018

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Thanks to ALLAH S.W.T and his Prophet Muhammad S.A.W.

Especially dedicated to my beloved mother who have prayed, supported, encouraged,

guided and inspired me throughout my journey of education.

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ACKNOWLEDGEMENT

First and foremost, “Syukur Alhamdulillah” to Allah, the Most Gracious and

Most Merciful for ensuring myself to be healthy to carry out my study and to

complete this project.

Secondly, I would like to express my warmest gratitude to my project

supervisor, Assoc Prof Ir Dr Mohd Ridzuan Ahmad for his guidance, professional

advice, encouragement and support throughout the period in completing this project.

His remarkable ideas and suggestions will be much appreciated in the long run of my

career.

My sincere appreciation also goes to my family especially my mother

Rafidah Binti Othman who has been so tolerant and supportive in all years either

morally or financially. Thanks for her continuous encouragement, love and

emotional supports that she had given to me all this while.

I also would like to gratefully thank to all my lecturers and all my friends

who had given me helps technically and mentally throughout my journey in

completing my project.

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ABSTRACT

This project proposed an improved method to provide an early detection

system at Semangar water treatment plant as many pollution cases occurred within

the past years had left many housing area without water supply for days. The solution

is based on the idea of developing an alert system, and also a real time database that

can store data ammonia, turbidity and pH. The approach has several notable merits,

namely cost efficient, not changing the existing system as it only act as an additional

feature and higher safety. The idea is proven based on two subsystems. First the early

detection system is based on notification through a mobile application. It provides

user with notification every time the ammonia reading is above 2 parts per million

threshold. Second, The real time database saves the ammonia parameter reading data

every 10 seconds in Google Spreadsheet. The current reading of the chemicals can

also be viewed using a web server which can then be connected through a mobile

application. Database application is not only by Google Spreadsheet but also using

Firebase application which can also be viewed through the mobile application. The

method proposed in this project can be used for any water treatment plant in

Malaysia that’s requires data to be stored and view at any given time.

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ABSTRAK

Projek ini mencadangkan penambahbaikan kaedah untuk menyediakan sistem

pengesanan awal pada loji rawatan air Semangar kerana banyak kes pencemaran

yang berlaku dalam tahun-tahun yang lalu telah menyebabkan banyak kawasan

perumahan tanpa bekalan air selama beberapa hari. Penyelesaian ini didasarkan pada

idea untuk membangunkan sistem amaran, dan juga pangkalan data masa nyata yang

boleh menyimpan data ammonia, kekeruhan dan pH. Pendekatan ini mempunyai

beberapa merit yang jelas, iaitu kos yang efisien, tidak mengubah sistem yang sedia

ada kerana ia hanya bertindak sebagai ciri tambahan dan keselamatan yang lebih

tinggi. Idea ini terbukti berdasarkan dua subsistem. Pertama sistem pengesanan awal

didasarkan kepada pemberitahuan melalui aplikasi mudah alih. Ia memberikan

pengguna pemberitahuan setiap kali bacaan ammonia melebihi 2 bahagian per juta

ambang. Kedua, pangkalan data masa nyata menyimpan data bacaan parameter

ammonia setiap 10 saat dalam Google Spreadsheet. Bacaan bahan kimia semasa juga

boleh dilihat menggunakan pelayan web yang kemudiannya boleh dihubungkan

melalui aplikasi mudah alih. Aplikasi pangkalan data bukan sahaja oleh Google

Spreadsheet tetapi juga menggunakan aplikasi Firebase yang juga dapat dilihat

melalui aplikasi mudah alih. Kaedah yang dicadangkan dalam projek ini boleh

digunakan untuk mana-mana loji rawatan air di Malaysia yang memerlukan data

yang akan disimpan dan dilihat pada bila-bila masa.

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TABLE OF CONTENTS

CHAPTER TITLE PAGE

DECLARATION ii

DEDICATION iii

ACKNOWLEDGEMENT iv

ABSTRACT v

ABSTRAK vi

TABLE OF CONTENTS vii

LIST OF TABLES x

LIST OF FIGURES xi

LIST OF ABBREVIATIONS xiii

LIST OF APPENDICES xiv

1 INTRODUCTION 1

1.1 Introduction 1

1.2 Motivation of Study 1

1.3 Problem Statement 2

1.4 Research Objectives 3

1.5 Research Scopes 3

1.6 Thesis Outline 4

2 LITERATURE REVIEW 6

2.1 Introduction 6

2.2 Technologies within IoT 7

2.2.1 Zigbee Protocol in Internet of Things 8

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2.2.2 WiFi Protocol in Internet of Things 8

2.2.3 Comparison between WiFi and Zigbee Protocol 10

2.3 Platforms used with Internet of Things 10

2.3.1 Arduino in Internet of Things 11

2.3.2 Raspberry Pi in Internet of Things 11

2.3.3 Mobile Application in Internet of Things 12

2.4 Cloud Computing Databases 12

2.4.1 SQL Databases 13

2.4.2 NoSQL Databases 14

2.4.3 Comparison between SQL and NoSQL 15

2.5 Applications in Internet of Things 18

2.5.1 Case Study 1: Real-Time Monitoring via Patch- 18

Type Piezoelectric Force Sensors for Internet of

Things Based Logistics

2.5.2 Case Study 2: Real-Time Safety Early Warning 21

System for Cross Passage Construction in Yangtze

Riverbed Metro Tunnel Based on The Internet of

Things

2.5.3 Case Study 3: Internet of Things Enabled Real 25

Time Water Quality Monitoring System

2.5.4 Case study 4: Architecting an IoT-Enabled 29

Platform for Precision Agriculture and Ecological

Monitoring

2.5.5 Case study 5: IoT and iTV for 34

Interconnection, Monitoring, and Automation

of Common Areas of Residents

2.6 Case Study synthesize 38

2.7 Limitation of Past Researches 39

2.8 Summary 39

3 RESEARCH METHODOLOGY 40

3.1 Introduction 40

3.2 Design Specification 42

3.3 Hardware Specification 43

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3.4 Internet of Things: IFTTT 44

3.5 Internet of Things: Firebase 48

3.6 Summary 50

4 RESULTS AND DISCUSSION 51

4.1 Introduction 51

4.2 Real Time Database with IFTTT 51

4.3 Push Notification with IFTTT 53

4.4 Web Server with Firebase 54

4.5 Firebase Database 55

4.6 Mobile Application with Firebase 56

4.7 Summary 58

5 CONCLUSION AND RECOMMENDATION 59

5.1 Conclusion 59

5.2 Future work and Recommendation 60

REFERENCES 61

APPENDICES 65

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LIST OF TABLES

TABLE NO. TITLE PAGE

2.1 Comparison between ZigBee and WiFi protocol 9

2.2 Comparison between SQL and NoSQL 16

2.3 Case study classification 38

3.1 Design specification 41

3.2 Hardware specification 42

3.3 Middleware comparison 45

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LIST OF FIGURES

FIGURE NO. TITLE PAGE

2.1 IoT architecture 7

2.2 Block diagram of the WSN system 9

2.3 System architecture of Arduino and Raspberry Pi 12

2.4 Diagram of framework 13

2.5 SELECT queries comparison of SQL and NoSQL 17

2.6 INSERT queries comparison of SQL and NoSQL 17

2.7 Patch type piezoelectric sensor 19

2.8 Micro controller with Bluetooth and its block diagram 19

2.9 In-vehicle Infotainment System showing the App (iTape) 20

and the online cloud monitoring

2.10 Architecture of an Iot-based safety early warning system 21

2.11 FBG at freezing pipes for frozen soil and at segment surface 22

2.12 Safety information transmitting layer 22

2.13 RFID location 23

2.14 Real-time tracking result in Iot based safety early warning 24

system

2.15 Circuit diagram of the system 26

2.16 Database layout of Ubidots cloud database application 27

2.17 Widgets for parameter monitoring 28

2.18 Alert events of Ubidots 29

2.19 Message sent from cloud database to smart phone 29

2.20 Context view of agriculture employing Iot technology 31

2.21 Illustration of sensor data to JSON API 31

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2.22 System components from implementation perspective 32

2.23 Smart agriculture node 33

2.24 Sensor data of the IoT node at the field 34

2.25 Smart residents Architecture 35

2.26 Sensor data stored in channels by ThingSpeak 36

2.27 Smart resident application interface 37

2.28 Smart resident inspect the temperature sensor data 37

3.1 Flowchart of the overall project 41

3.2 Overall architecture of IoT implementation 44

3.3 IFTTT setup 46

3.4 CRUD function 47

3.5 Flowchart of connecting to Firebase 48

3.6 Firebase database 49

3.7 Podfile connecting to Firebase 50

4.1 Online database via google spreadsheets 52

4.2 Push notification of the device 53

4.3 Web server html file 54

4.4 Web server 55

4.5 Firebase database 56

4.6 Overall application layout 57

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LIST OF ABBREVIATIONS

IoT - Internet of Things

WQI - Water Quality Index

ML - Machine Learning

IFTTT - If This Then That

ESP32 - Espressif 32 bit architecture

RMSE - Root Mean Square Error

MLP - Multilayer Perceptron

GB - Gigabytes

MB - Megabyte

ROM - Read Only Memory

PWM - Pulse Width Modulation

CRUD - Create Read Update Delete

BLE - Bluetooth Low Energy

LED - Light Emitting Diode

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LIST OF APPENDICES

APPENDIX TITLE PAGES

A Arduino code for IFTTT 65

B Arduino code for Firebase 69

CHAPTER 1

INTRODUCTION

1.1 Background of study

The purpose of this project is to translate the information given from the

sensor reading towards the internet for cloud computing and classify the data based

on capacitance reading from ammonia. Water is an essential natural resources for all

human kind. But rapid development projects and human activities has caused

contamination to the water resources. In today’s technology, the method used to test

the water quality is to have operators perform the duty of collecting a sample of the

water resources a few times per day and conduct the testing for the sample in a lab.

This process is tedious and time consuming as it does not monitor the water

resources continuously but only at certain time frame of the day. Furthermore, this

can cause problems if a contamination were to occur during the time when testing

was not being conducted. Internet of Things (IoT) technologies provide a solution to

this as it can monitor the water quality at all times and bring about data which can be

used for analysis purposes in real time on the cloud. This system can provide an early

warning system for which if a contamination were to occur [1].

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1.2 Motivation of Study

Water is an essential part of life. Contaminated water is also the leading cause

of death, higher than any act of violence including war. In Malaysia, water treatment

plants supply the water supply to the residential and industrial areas. If the water

treatment plants were to be closed, the said areas will not have any water. The water

treatment plants will be closed due to polluted water from the river. Valves controls

the flow of water connecting the water treatment plant and the said areas. If the valve

is closed before the contaminated water reach the water tank then said areas would

still have water. What this project do to solve this problem is to create an early

monitoring system with cloud computing in order to prevent the valves from being

closed too late.

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1.3 Problem Statement

The main problem with the IoT is the storage system. A typical IoT device

can accumulate thousands of data, thus a large storage systems needed. Notification

on how to use push is also a topic of discussion. When to alert user based on the

water status is also a problem that needs to be solved.

Current practices implemented at the water treatment plant is also an issue

when doing this project. The way things work now with respect to checking the

water source status whether it is high in ammonia content or not is that technicians

check the site every 2 hours. If the water is deemed high in ammonia, there would be

no real treatment to it, the plant would need to stop operation and allow the water to

naturally lower its ammonia content.

3

The water treatment plants purpose was only to get the chemical compound

reading of the water and sent it to Bakal Setia Air Johor (BAKAJ), for BAKAJ is the

one that decides what the next step is going to be taken. Stopping the plant operation

requires BAKAJ approval even if the technician confirms the water is polluted.

BAKAJ action is not immediate when they receive information knowing that the

water is polluted. They would wait around a few hours to half a day to really confirm

the water is polluted then only they would instruct the water treatment plant to stop

operation. With the time wasted, polluted water would already be in the residential

water supply tank thus would prevent people from getting their water. This project

needs to close this gap to prevent this situation from ever happening again.

1.4 Research Objectives

The objective of this project can be divided into three main objectives that are:

i. To implement real time cloud computing database function onto the

existing device to allow for backlogging capability.

ii. To implement an alerting system for when the water condition is declared

polluted based on ammonia level from the sensor.

iii. To compare between Firebase and IFTTT middleware based on their

features.

1.5 Research Scope

The scopes of this project are:

i. ESP32 is used to read from micro-fludic sensor based on capacitance

value.

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ii. Middleware IFTTT with WiFi protocol is used to bridge the sensor and

cloud communication.

iii. Real time database and alerting notification can be viewed through

mobile phones.

iv. Experiment is done in a lab environment with controlled (100 mililitre

syringe) amount of water test samples.

v. Apple development program was used as the mobile platform.

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1.6 Thesis Outline

This thesis consists of five chapters. Chapter 1 introduces the motivation of

the study, problem statement, objective of this project, scope of project and the

overall thesis outline.

Chapter 2 focuses on literature reviews related to this project based on

journals and other references. An introduction on IoT and databases was explained

based on their applications towards data storage and monitoring features.

Chapter 3 mainly discussed the methodology of the project. The method to

connect to If This Then That (IFTTT) server then use the notification feature and

Google Spreadsheet database. Web server used to connect to the IOS application for

Firebase was also discussed and explained.

Chapter 4 presents the results of the project. The discussion focused on the

difference in features provided by the IFTTT and Firebase. The result of the project

is based largely on the finished application and the features ability in fulfilling the

objectives of this project.

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Chapter 5 concludes the project as a whole. The recommendation for future

works was also suggested in this.

REFERENCES

[1] T. Perumal, N. Sulaiman, and C. Y. Leong, “Internet of Things ( IoT )

Enabled Water Monitoring System,” 2015 IEEE 4th Glob. Conf. Consum.

Electron. Internet, pp. 86–87, 2015.

[2] S. Madakam, R. Ramaswamy, and S. Tripathi, “Internet of Things (IoT): A

Literature Review,” J. Comput. Commun., vol. 3, no. 5, pp. 164–173, 2015.

[3] C.-W. Tsai, C.-F. Lai, and A. V. Vasilakos, “Future Internet of Things: open

issues and challenges,” Wirel. Networks, vol. 20, no. 8, pp. 2201–2217, 2014.

[4] J. E. Ibarra-Esquer, F. F. González-Navarro, B. L. Flores-Rios, L. Burtseva,

and M. A. Astorga-Vargas, “Tracking the evolution of the internet of things

concept across different application domains,” Sensors (Switzerland), vol. 17,

no. 6, pp. 1–24, 2017.

[5] H. Y. Kim and J. M. Kim, “A load balancing scheme based on deep-learning

in IoT,” Cluster Comput., vol. 20, no. 1, pp. 873–878, 2017.

[6] X. Yi, Z. Jia, N. Chen, W. Zhu, and Z. Wu, “The research and

implementation of ZigBee protocol-based internet of things embedded

system,” 2010 2nd Int. Symp. Inf. Eng. Electron. Commer. IEEC 2010, pp.

341–344, 2010.

[7] Chunxiao Fan, Zhigang Wen, Fan Wang, and Yuexin Wu, “A middleware of

Internet of Things (IoT) based on ZigBee and RFID,” IET Int. Conf.

Commun. Technol. Appl. (ICCTA 2011), pp. 732–736, 2011.

[8] H. G. C. Ferreira, E. Dias Canedo, and R. T. De Sousa, “IoT architecture to

enable intercommunication through REST API and UPnP using IP, ZigBee

and arduino,” Int. Conf. Wirel. Mob. Comput. Netw. Commun., pp. 53–60,

2013.

62

[9] T. Thaker, “ESP8266 based implementation of wireless sensor network with

Linux based web-server,” 2016 Symp. Colossal Data Anal. Networking,

CDAN 2016, 2016.

[10] R. K. Kodali and A. Naikoti, “ECDH based security model for IoT using

ESP8266,” 2016 Int. Conf. Control Instrum. Commun. Comput. Technol.

ICCICCT 2016, pp. 629–633, 2016.

[11] G. Barbon, M. Margolis, F. Palumbo, F. Raimondi, and N. Weldin, “Taking

Arduino to the Internet of Things: The ASIP programming model,” Comput.

Commun., vol. 89–90, pp. 128–140, 2016.

[12] B. Jo and Z. Baloch, “Internet of things-based arduino intelligent monitoring

and cluster analysis of seasonal variation in physicochemical parameters of

Jungnangcheon, an urban stream,” Water (Switzerland), vol. 9, no. 3, 2017.

[13] M. Ibrahim, A. Elgamri, S. Babiker, and A. Mohamed, “Internet of things

based smart environmental monitoring using the Raspberry-Pi computer,”

2015 Fifth Int. Conf. Digit. Inf. Process. Commun., pp. 159–164, 2015.

[14] S. Chang and K. Jeong, “A mobile application for fine dust monitoring

system,” Proc. - 18th IEEE Int. Conf. Mob. Data Manag. MDM 2017, pp.

336–339, 2017.

[15] A. Joseph, B. Shrestha, A. Joseph, K. J. Singh, and K. R. P, “Web and

Android based Automation using IoT Web and Android based Automation

using IoT,” IEEE Int. Conf. Collab. Comput. Networking, Appl. Work ,pp.

214-228, 2017.

[16] D. Bruneo, S. Distefano, F. Longo, G. Merlino, A. Puliafito, and A. Zaia,

“Head in a Cloud : an Approach for Arduino YUN Virtualization,” Proc.

2017 5th ICT Int. Student Proj. Conf. ICT-ISPC 2017, pp. 120–134, 2017.

63

[17] H. Fatima and K. Wasnik, “Comparison of Sql , Nosql and New Sql

Databases in Light of Internet of Things – a Survey,” Procedia Comput. Sci.,

vol. 110, no. January, pp. 2–5, 2016.

[18] S. Rautmare and D. M. Bhalerao, “MySQL and NoSQL database comparison

for IoT application,” 2016 IEEE Int. Conf. Adv. Comput. Appl. ICACA 2016,

pp. 235–238, 2016.

[19] P. T. A. Mai, J. K. Nurminen, and M. Di Francesco, “Cloud databases for

internet-of-things data,” Proc. - 2014 IEEE Int. Conf. Internet Things, iThings

2014, 2014 IEEE Int. Conf. Green Comput. Commun. GreenCom 2014 2014

IEEE Int. Conf. Cyber-Physical-Social Comput. CPS 20, no. iThings, pp.

117–124, 2014.

[20] Y. J. Heo, S. M. Oh, W. S. Chin, and J. W. Jang, “A lightweight platform

implementation for Internet of things,” Proc. - 2015 Int. Conf. Futur. Internet

Things Cloud, FiCloud 2015 2015 Int. Conf. Open Big Data, OBD 2015, pp.

526–531, 2015.

[21] A. Daramas, S. Pattarakitsophon, K. Eiumtrakul, T. Tantidham, and N.

Tamkittikhun, “HIVE: Home Automation System for Intrusion Detection,”

Proc. 2016 5th ICT Int. Student Proj. Conf. ICT-ISPC 2016, pp. 101–104,

2016.

[22] J. Boman, J. Taylor, and A. Ngu, “Flexible IoT Middleware for Integration of

Things and Applications,” Proc. 10th IEEE Int. Conf. Collab. Comput.

Networking, Appl. Work., pp. 481–488, 2014.

[23] M. A. G. Maureira and L. Teernstra, “ThingSpeak – an API and Web Service

for the Internet of Things,” 2011 Fifth Int. Conf. Digit. Inf. Process.

Commun., pp. 140–149, 2011.

[24] C. H. Chuang, W. C. Weng, W. J. Chang, and D. H. Lee, “Real-time

monitoring via patch-type piezoelectric force sensors for Internet of Thing in

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logistics,” 2016 IEEE 11th Annu. Int. Conf. Nano/Micro Eng. Mol. Syst.

NEMS 2016, vol. 17, no. 8, pp. 325–328, 2016.

[25] L. Y. Ding et al., “Real-time safety early warning system for cross passage

construction in Yangtze Riverbed Metro Tunnel based on the internet of

things,” Autom. Constr., vol. 36, pp. 25–37, 2013.

[26] S. Geetha and S. Gouthami, “Internet of things enabled real time water

quality monitoring system,” Smart Water, vol. 2, no. 1, p. 1, 2016.

[27] F. Karim, F. Karim, and A. Frihida, “Monitoring system using web of things

in precision agriculture,” Procedia Comput. Sci., vol. 110, pp. 402–409,

2017.

[28] T. Popović, N. Latinović, A. Pešić, Ž. Zečević, B. Krstajić, and S.

Djukanović, “Architecting an IoT-enabled platform for precision agriculture

and ecological monitoring: A case study,” Comput. Electron. Agric., vol. 140,

pp. 255–265, 2017.

[29] H. Sánchez, C. González-Contreras, J. Agudo, and M. Macías, “IoT and iTV

for Interconnection, Monitoring, and Automation of Common Areas of

Residents,” Appl. Sci., vol. 7, no. 7, p. 696, 2017.

[30] M. Di Francesco, N. Li, M. Raj, and S. K. Das, “A storage infrastructure for

heterogeneous and multimedia data in the Internet of Things,” Proc. - 2012

IEEE Int. Conf. Green Comput. Commun. GreenCom 2012, Conf. Internet

Things, iThings 2012 Conf. Cyber, Phys. Soc. Comput. CPSCom 2012, pp.

26–33, 2012.