Technical Paper by Yazid Idzmir
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This document describes a wireless sensor network project to remotely monitor an artificial aquatic ecosystem. The network uses Mote-IRIS sensor nodes connected to a base station via a MIB520 interface board. Sensors measure pH, temperature, and humidity to evaluate water quality. Data is analyzed using a Water Quality Index method. Results from testing different water samples showed the network could accurately assess water quality levels from excellent to poor. The project aims to develop a robust monitoring system to better understand aquatic ecosystems and water quality issues.
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![A WIRELESS SENSOR NETWORK (WSN) TO REMOTELY
MONITOR AN ARTIFICIAL AQUATIC ECOSYSTEM
Muhammad Yazid Idzmir
Electrical And Electronic Engineering
University Technology Of Petronas
Tronoh, Perak
myi.perfect@gmail.com
Abstract— A Wireless Sensor Network (WSN) to remotely
monitor an artificial aquatic ecosystem in this project was to
discover a new technology using embedded devices. This new
technology was implemented using Mote-IRIS 2.4GHz
connecting to the network. Current methods used nowadays for
monitoring aquatic ecosystems are less efficient and unable to
solve the water quality expectation. Water with pollution became
one of the biggest the world wide issued to lead for the fresh
water supply. For solving these problems, a development with a
new technologies using Mote-Iris for a proper of collecting data
and for making data analysis can be make for the aquatic
ecosystem. Sampled water will be collected to measured
parameters that involved in collecting data are pH, Temperature
and Humidity. All this parameter is crucial to identify the quality
of the aquatic ecosystem. A proper set of tools and software need
to be use in this project such as Transmitter, Receiver, Integrated
Board (XM-300) and also sensor from MEMSIC company .The
tools and software required to evaluate the parameters to be
measure in the aquatic ecosystem. The analyze data will be
recorded and data collection were made based on Water Quality
Index (WQI) Method.
Keywords — Wireless Sensor Network (WSN), Transmitter,
Receiver, Integrated Board, pH, Temperature and Humidity
I. INTRODUCTION
Communities which rely on each other and also based on
their living environment consist in a body of water that
divided into two; freshwater and marine are called aquatic
ecosystem. The change in the ecosystem of rivers influences
the water quality of these rivers. As the water quality
deteriorates so does the sustainability of the aquatic animals
and plants. Therefore, it is important for tracking and
understanding the causes that affect the water quality using a
reliable system. The focus of this project is to use a wireless
sensor network to monitor the change in the water quality. A
wireless sensor network has been proposed for monitoring the
change in ecosystem because it can operate unattended while
providing fewer disturbances to animals than other
conventional data logger methods. However, deployment and
implementation of WSN in rivers are challenging as the WSN
has to be robust to climate change such as water-proof, has a
reliable data delivery and must be able to conserve the limited
energy supply.
II. LITERATURE REVIEW
A. Wireless Sensor Network (WSN)
WSN communicates using sensor nodes that consists three
main parts; base station, gateways and sensor nodes
[2].According to research paper, mostly the wireless nodes
have limited range from 15 meters length up to 30 meters to
communicate. So, in fact to make a wide distance
communication, the sensor nodes need to communicate from
gateways to transmit data to the base station and then the
gateways will forward those data to the base station and vice
versa [4].
As example, WSN had been used on variety of sensing
input as a medium for collecting data such as lightning
condition, noise levels, temperature, PH, pressure, humidity or
absence of an object, direction and size of an object. The
reason for choosing WSN because of it broadly applications
which it only requires transmission of small power signals. The
cooperative capabilities are by contributing a lot to
environment monitoring application which usually used as
pollution monitoring system by identified the presence of
foreign chemical over air or in the water. This kind of
application is suitable for WSN compared to larger size of
other wireless devices [3].
With main capability, WSN sensor nodes can collaborate
each other and sending data to the remote monitoring center by
the base station using GPRS. Furthermore, if any sudden
change in water quality it is also able to compute back simple
computation in order to get back the data and to reduce data
traffic in transmission by transmitting the only necessary
processed data or data that needed for more higher level
computation [3] .
WSN design comes in small size, battery power
consumption and capabilities, computation capabilities and the
memory storage are limited. It gives more accurate result as
the higher number of sample data been collected with the
sensor node capabilities, a dense deployed are possible unlike](https://cdn.statically.io/img/image.slidesharecdn.com/e603d1d0-9773-439b-ba79-b8591b78800d-150416213122-conversion-gate01/85/Technical-Paper-by-Yazid-Idzmir-1-320.jpg)
![other wireless communication, such as blue-tooth and Infrared
the WSN sensor nodes better in data packaging, collect data,
more efficient in operating linearization, parameter
memorizing and routing to a base station [3] .
The technique to cover larger collectable data area, the
sensor nodes must be between the base station and other further
reachable sensor nodes that will transmit data with multi-hop
communication. It is because the transmission range of each
sensor node is very small due to frequencies rate and length of
transmission rate. So to overcome this problem, the multi-hop
communication will surpass the range of point-to-point
communication with very effective data transmission [3].
B. Water Quality Index (WQI)
Based on journal article, the quality of water in any
ecosystem can be simply reflect as a simple numeric
expression known as a Water Quality Index (WQI).There are
two steps to carry out data analysis; by performing for each of
the variable using analysis of variance (ANOVA) and WQI
method. To consider each variable for ANOVA, a factorial
treatment design 12 * 3 which factor A with 12 levels ( the
sampling hours) and three different level depth (0.1 m, 0.3 m
and 0.5 m) as a factor B with level of significant 0.05 (α=
0.05).For WQI with a general mean of 2.1,is indicating the
water in excellent quality [1]. The following Equation show
how WQI was calculated.
WQI =
∑ 𝑃𝑖∗𝑊𝑖𝑛
𝑖=1
∑ 𝑃𝑖𝑛
𝑖=1
𝐾 [1]
where:
WQI = water quality index.
Wi = specific weight of each variable (1-4)
Parameters Units Wi* Pi* Range
Tolerance
pH - 4 1 6.5 - 8.5
2 <6.5
Humidity % 3 1 >100
2 <100
Temperature ˚C 4 1 20 - 25
2 <20
2 >25
Table 1. Value Assigned for water quality parameters
In this experiment, three variables that to be measured;
potential hydrogen (pH), temperature (T) and humidity
measured with Ph-BTA Probe sensor from Vernier Software
and Technology Company. The pH level is measured in pH
units, Humidity in % and Temperature in Celsius degree
(˚C).The scale for the assessment and analysis of water quality
shown in the table below.
Value of WQI Classification Water Quality
95 - 100 I Excellent
80 - 94 II Good
65 - 79 III Quite Good
45 - 64 IV Poor
0 - 44 V Polluted
Table 2. The scale for the assessment of water quality by
WQI
III. HARDWARE AND SOFTWARE
A. MIB520 USB Interface Board
MIB520 is a base station for Wireless Sensor Networks;
USB Port Programming for IRIS/MICAz/MICA2 Hardware
platforms and USB Bus Power. The MIB520CB provides
USB connectivity to the IRIS and MICA family of Motes
for communication and In-system programming. Any IRIS/
MICAz /MICA2 node can be function as a base station
when mated to the MIB520CB USB interface board .In
addition to data transfer, the MIB500CB also provides a
USB programming interface [7].
Fig. 1 MIB520CB with attached Mote [7]
Fig. 2 MIB520CB Block Diagram [7]
The MIB520CB offers two separate ports; one dedicated to
in-system Mote programming and a second for data
communication over USB.USB Bus power eliminates the
need for an external power source.
B. MDA300 Data Acquisition Board
MDA300 board is a multi-Function Data Acquisition
Board supported via MEMSIC’s MoteView user interface
with Temp, PH and Humidity as a sensor which suitable for](https://cdn.statically.io/img/www.slideshare.net/data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
Technical Paper by Yazid Idzmir
- 1. A WIRELESS SENSOR NETWORK (WSN) TO REMOTELY MONITOR AN ARTIFICIAL AQUATIC ECOSYSTEM Muhammad Yazid Idzmir Electrical And Electronic Engineering University Technology Of Petronas Tronoh, Perak myi.perfect@gmail.com Abstract— A Wireless Sensor Network (WSN) to remotely monitor an artificial aquatic ecosystem in this project was to discover a new technology using embedded devices. This new technology was implemented using Mote-IRIS 2.4GHz connecting to the network. Current methods used nowadays for monitoring aquatic ecosystems are less efficient and unable to solve the water quality expectation. Water with pollution became one of the biggest the world wide issued to lead for the fresh water supply. For solving these problems, a development with a new technologies using Mote-Iris for a proper of collecting data and for making data analysis can be make for the aquatic ecosystem. Sampled water will be collected to measured parameters that involved in collecting data are pH, Temperature and Humidity. All this parameter is crucial to identify the quality of the aquatic ecosystem. A proper set of tools and software need to be use in this project such as Transmitter, Receiver, Integrated Board (XM-300) and also sensor from MEMSIC company .The tools and software required to evaluate the parameters to be measure in the aquatic ecosystem. The analyze data will be recorded and data collection were made based on Water Quality Index (WQI) Method. Keywords — Wireless Sensor Network (WSN), Transmitter, Receiver, Integrated Board, pH, Temperature and Humidity I. INTRODUCTION Communities which rely on each other and also based on their living environment consist in a body of water that divided into two; freshwater and marine are called aquatic ecosystem. The change in the ecosystem of rivers influences the water quality of these rivers. As the water quality deteriorates so does the sustainability of the aquatic animals and plants. Therefore, it is important for tracking and understanding the causes that affect the water quality using a reliable system. The focus of this project is to use a wireless sensor network to monitor the change in the water quality. A wireless sensor network has been proposed for monitoring the change in ecosystem because it can operate unattended while providing fewer disturbances to animals than other conventional data logger methods. However, deployment and implementation of WSN in rivers are challenging as the WSN has to be robust to climate change such as water-proof, has a reliable data delivery and must be able to conserve the limited energy supply. II. LITERATURE REVIEW A. Wireless Sensor Network (WSN) WSN communicates using sensor nodes that consists three main parts; base station, gateways and sensor nodes [2].According to research paper, mostly the wireless nodes have limited range from 15 meters length up to 30 meters to communicate. So, in fact to make a wide distance communication, the sensor nodes need to communicate from gateways to transmit data to the base station and then the gateways will forward those data to the base station and vice versa [4]. As example, WSN had been used on variety of sensing input as a medium for collecting data such as lightning condition, noise levels, temperature, PH, pressure, humidity or absence of an object, direction and size of an object. The reason for choosing WSN because of it broadly applications which it only requires transmission of small power signals. The cooperative capabilities are by contributing a lot to environment monitoring application which usually used as pollution monitoring system by identified the presence of foreign chemical over air or in the water. This kind of application is suitable for WSN compared to larger size of other wireless devices [3]. With main capability, WSN sensor nodes can collaborate each other and sending data to the remote monitoring center by the base station using GPRS. Furthermore, if any sudden change in water quality it is also able to compute back simple computation in order to get back the data and to reduce data traffic in transmission by transmitting the only necessary processed data or data that needed for more higher level computation [3] . WSN design comes in small size, battery power consumption and capabilities, computation capabilities and the memory storage are limited. It gives more accurate result as the higher number of sample data been collected with the sensor node capabilities, a dense deployed are possible unlike
- 2. other wireless communication, such as blue-tooth and Infrared the WSN sensor nodes better in data packaging, collect data, more efficient in operating linearization, parameter memorizing and routing to a base station [3] . The technique to cover larger collectable data area, the sensor nodes must be between the base station and other further reachable sensor nodes that will transmit data with multi-hop communication. It is because the transmission range of each sensor node is very small due to frequencies rate and length of transmission rate. So to overcome this problem, the multi-hop communication will surpass the range of point-to-point communication with very effective data transmission [3]. B. Water Quality Index (WQI) Based on journal article, the quality of water in any ecosystem can be simply reflect as a simple numeric expression known as a Water Quality Index (WQI).There are two steps to carry out data analysis; by performing for each of the variable using analysis of variance (ANOVA) and WQI method. To consider each variable for ANOVA, a factorial treatment design 12 * 3 which factor A with 12 levels ( the sampling hours) and three different level depth (0.1 m, 0.3 m and 0.5 m) as a factor B with level of significant 0.05 (α= 0.05).For WQI with a general mean of 2.1,is indicating the water in excellent quality [1]. The following Equation show how WQI was calculated. WQI = ∑ 𝑃𝑖∗𝑊𝑖𝑛 𝑖=1 ∑ 𝑃𝑖𝑛 𝑖=1 𝐾 [1] where: WQI = water quality index. Wi = specific weight of each variable (1-4) Parameters Units Wi* Pi* Range Tolerance pH - 4 1 6.5 - 8.5 2 <6.5 Humidity % 3 1 >100 2 <100 Temperature ˚C 4 1 20 - 25 2 <20 2 >25 Table 1. Value Assigned for water quality parameters In this experiment, three variables that to be measured; potential hydrogen (pH), temperature (T) and humidity measured with Ph-BTA Probe sensor from Vernier Software and Technology Company. The pH level is measured in pH units, Humidity in % and Temperature in Celsius degree (˚C).The scale for the assessment and analysis of water quality shown in the table below. Value of WQI Classification Water Quality 95 - 100 I Excellent 80 - 94 II Good 65 - 79 III Quite Good 45 - 64 IV Poor 0 - 44 V Polluted Table 2. The scale for the assessment of water quality by WQI III. HARDWARE AND SOFTWARE A. MIB520 USB Interface Board MIB520 is a base station for Wireless Sensor Networks; USB Port Programming for IRIS/MICAz/MICA2 Hardware platforms and USB Bus Power. The MIB520CB provides USB connectivity to the IRIS and MICA family of Motes for communication and In-system programming. Any IRIS/ MICAz /MICA2 node can be function as a base station when mated to the MIB520CB USB interface board .In addition to data transfer, the MIB500CB also provides a USB programming interface [7]. Fig. 1 MIB520CB with attached Mote [7] Fig. 2 MIB520CB Block Diagram [7] The MIB520CB offers two separate ports; one dedicated to in-system Mote programming and a second for data communication over USB.USB Bus power eliminates the need for an external power source. B. MDA300 Data Acquisition Board MDA300 board is a multi-Function Data Acquisition Board supported via MEMSIC’s MoteView user interface with Temp, PH and Humidity as a sensor which suitable for
- 3. environmental data collection, general data collection and logging [5]. Fig. 3. MDA300C Block Diagram [5] The MDA300’s easy access micro-terminals also make it an economical solution for a variety of applications and a key component in the next generation of low-cost wireless weather stations as part of a standard mesh network [5]. C. MoteView 2.1 Software MoteView is developed to be an interface between a user and a deployed network of wireless sensors. MoteView provides the tools to simplify deployment and monitoring. It also makes it easy to connect to a database, to analyze, and for graph sensor readings [6]. Figure 4. MoteView 2.1 Software Setup The framework to deploy a sensor network is divided into 3parts; Mote layer to program with XMESH/ TinyOS for tracking asset, instruction detection and monitoring; Server for data logging and as for sensor readings to base station MIB510 board and MDA300 and Tier as the third part for interpret sensor data and software tools to provide visualization, monitoring and analysis tools [6]. Figure 5. MDA300 Sensor Board Configuration IV. METHODOLOGY A. Research Methodology In order to achieve the objectives of this project, research and analysis are done on the MoteView 2.1 Software and MDA300 testing to create basic battery profile. Thus, the sensor nodes being implemented on the probe sensor to get the measure parameters. Figure 6. Research Methodology
- 4. B. Setup The Programming Using MoteView 2.1 (a) (b) Figure 7. MoteView 2.1 Programming for XMeshBase and XMDA300 C. Setup The Experiment Author develops C language source code to support the microcontroller as desired. The compiled source code was simulated with the MoteConfig 2.0 software. Figure 8. Program Flow Chart V. RESULTS AND DISCUSSION Figure 9. Result for Chlorine Water (PH 7) Figure 10. Result for UTP Lake Water (PH6.5 to PH7).
- 5. Figure 11. Result for Graph of Alkaline Water ( >PH 7) The graph proved that from all the parameter setup and all data reading were correct according to the Water Quality Index (WQI) where three different samples of water taken from different PH value. Figure 12. Levels of Parameters Temperature, Humidity and PH value in water samples from the UTP Lake Water Hours WQI* Water Quality 0900 3.19 Excellent 1000 2.84 Excellent 1100 2.74 Good 1200 2.77 Good 1300 1.42 Good 1400 1.38 Poor 1500 1.37 Poor 1600 2.02 Poor 1700 2.00 Good 1800 2.04 Good 1900 2.10 Good 2000 2.10 Good Average 2.15 Good Table 3. WQI values per 12hours at UTP Lake Water from 0900 Hour to 2000 Hour The calculated WQI determined excellent water quality for the morning, good quality for afternoon and night and poor for evening. The results show that the water of this ecosystem can be used without any problem for ecological purposes as well as for artificial aquatic ecosystem. It is highly recommend to continue monitoring water and to employ other methodologies like the WQI using additional variables. VI. CONCLUSION This paper discuss on the Water Quality Index determined to measure the quality water using Mote-IRIS 2.4GHz and to design and built a prototype of design a wet- proof case for the WSN for it able to work closely to water. The prototype is still under progress and the test for the all the parameter with MoteView 2.1 will be done as author resolve the hardware and source code issues on the prototype. Combination of many parameters will be done to get more data collection. ACKNOWLEDGMENT First and foremost I would like to express my humble gratitude to Allah S.W.T, because of His blessings and guidance to me throughout completing my final year project. I would also like to sincerely acknowledge for those who had assist me on this achievement of my project. My appreciation and gratitude goes to my supervisor, Dr. Azrina Abdul Aziz, for her sincere guidance and teaching me throughout this whole project. Not forgetting Dr Azlan Awang and Mr Abu Bakar Sayuti on assisting me to understand and completing my tasks throughout the whole year. Special thanks to my colleagues, Muhammad Asyraf, Shafiq Imtiaz and Nurul Ashikin for their cooperation to help me during my difficulties on accomplishing this project. I would like to express my gratitude to my university, Universiti Teknologi PETRONAS especially the Electrical and (a) (b) (c)
- 6. Electronic Engineering Department for equipping me with essential theories and skills for self-learning. Its well-rounded graduate philosophy has proven to be useful in the industry. REFERENCES [1] Rubio-Arias, H., JM, O. R., RM, Q., Saucedo-Teran, R., & NI, R. B. (2013). Development of a Water Quality Index (WQI) of an Artificial Aquatic Ecosystem in Mexico. Journal of Environmental Protection, 2013. [2] Hong-Bo, X., Peng, J., & Kai-Hua, W. (2009, December). Design of water environment data monitoring node based on ZigBee technology. In Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on (pp. 1-4). IEEE. [3] Akyildiz,I.F., ET AL., Wireless sensor networks;a survey.Computer Networks, 2002.38(4): p.393-422 [4] Alippi, C., et al., A robust, adaptive, solar-powered WSN framework for aquatic environmental monitoring. Sensor Journal, IEEE, 2011. 11(1): P.45-55 [5] MEMSIC Inc. MDA300 User Manual. Retrieved May 20, 2014, from http://www.memsic.com/wireless-sensor- networks/MDA300.html [6] MEMSIC Inc. MoteView User Manual. Retrieved June 14, 2014, from http://archive.cone.informatik.uni- freiburg.de/teaching/praktikum/Adhocnetworks- w07/wsn/mica2- cd/Manuals%20and%20Docs/MoteView_Users_Manual_ 7430-0008-04_C.pdf [7] MEMSIC Inc. MIB520 User Manual. Retrieved July 10, 2014, from http://www.memsic.com/wireless-sensor- networks/MIB520.html