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International Journal of Electrical and Computer Engineering (IJECE)
Vol. 10, No. 2, April 2020, pp. 1278~1287
ISSN: 2088-8708, DOI: 10.11591/ijece.v10i2.pp1278-1287  1278
Journal homepage: http://ijece.iaescore.com/index.php/IJECE
A long range, energy efficient Internet of Things based drought
monitoring system
Van-Phuc Hoang1
, Minh-Hong Nguyen2
, Thanh Quan Do3
, Dinh-Nhan Le4
, Du Duong Bui5
1,2,3,4
Le Quy Don Technical University, 236 Hoang Quoc Viet Str., Hanoi, Vietnam
5
National Center for Water Resources Planning and Investigation (NAWAPI), Hanoi, Vietnam
Article Info ABSTRACT
Article history:
Received May 30, 2019
Revised Oct 1, 2019
Accepted Oct 11, 2019
The climate change and global warning have been appeared as an emerging
issue in recent decades. In which, the drought problem has been influenced
on economics and life condition in Vietnam. In order to solve this problem,
in this paper, we have designed and deployed a long range and energy
efficient drought monitoring based on IoT (Internet of Things) for real time
applications. After being tested in the real condition, the proposed system has
proved its high dependability and effectiveness. The system is promising to
become a potential candidate to solve the drought problem in Vietnam.
Keywords:
Environment Monitoring
Internet of Things
LORA
Smart Water
Copyright © 2020 Institute of Advanced Engineering and Science.
All rights reserved.
Corresponding Author:
Van-Phuc Hoang,
Department of Microprocessor Engineering,
Le Quy Don Technical University,
236 Hoang Quoc Viet Str., Hanoi, Vietnam
Email: phuchv@lqdtu.edu.vn
1. INTRODUCTION
In recent years, Internet of Things (IoT) is the key word that there are a large number of people
looking for and it is a part of the fourth industrial revolution. Many researchs [1-5] related to this subject
have been performed with many different areas, such as healthcare, transportation, smart infrastructure, smart
city, etc. Howerver, most of these applications have different requirements, operate in different
environments, so all equipment of each application have to be designed the most optimal to achieve
the highest effectiveness. Especially, one of these applications is smart environment monitoring system based
on IoT that can provide real time data. In the past few decades, there have been a large number of researchers
focus on applications related to Wireless Sensor Networks (WSNs), Wireless Body Area Networks
(WBANs), IoT with a variety of different platforms [6-33]. In these designs, microcontrollers (MCU) which
are often ultra-low power chips were chosen to reduce the systempower consumption and MSP430 family
from Texas Instrument (TI) is a good choice [8-10, 13]. Moreover, some transceivers were used in these
works, including Wi-Fi module, bluetooth module, Radio Frequency (RF) module with many different
protocols. Especially, authors in [10] presented the comparison of different wireless transmission modules to
give the best choice for a detailed application. In addition, in recent years, smart cities have concerning in
many countries, so Wi-Fi will cover most of place in the future. Therefore, using Wi-Fi modules as
transceiver should be used in applications related to WSN, WBAN, IoT. With each application which has
different functions, sensors will be chosen to ensure the lowest power consumption and the highest accuracy.
However, to provide long range communications, energy efficient and real time monitoring, in this paper,
LORA technology is used.
Int J Elec & Comp Eng ISSN: 2088-8708 
A long range, energy efficient Internet of Things based drought monitoring system (Van-Phuc Hoang)
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In Vietnam, the drought has appeared as a burning issue and seriously influenced on economics,
society and the daily life for recent years. In addition, the drought increases significantly the level and widens
the affected area, leading to critical consequence if it is not controlled effectively as reported in [34].
As a result, the early drought warning and monitoring is an essential solution to address this matter.
In this work, we have researched, designed and implemented a really full worked-out system based on LORA
technology drought for monitoring, consisting of both hardware and monitoring software. After a number of
experiments, the system has demonstrated the effectiveness and stable working. The rest of this paper is
organized as follows. Section 2 describes the system architecture. Section 3 shows data analysis and
processing method. Section 4 presents the implementation results and finally, Section 5 concludes of
the paper.
2. SYSTEM DESIGN
The proposed IoT based drought monitoring system has three main sectors including slave node,
master node and monitor software as shown in Figure 1. These sectors are connected throught an IoT
platform with LORA, Wi-Fi and Internet systems. The slave nodes will collect temperature and precipitation
information and then transmit this information to master node as shown in Figure 2. Since there have many
slave nodes, each node will be assigned a code. When the slave node receives an instruction from the master
node, it will transmit data. Consequently, data management of the slave node is more efficient and the slave
node power consumption is reduced. On the other hand, the master node roles are to monitor and control
the slave nodes, to collect data and then to calculate the drought parameters and transmit this information to
website. The website will show the recent temperature and precipitation data of all slave nodes, daily and
monthly average temperature and precipitation, and the SPI, PE and J index. All these parameters will be
analyzed in order to state the drought level of each area and predict the drought trend in the future.
Figure 1. System block diagram of proposed IoT based drought monitoring system
Figure 2. The master (right side) and slave (left side) nodes hardware
 ISSN: 2088-8708
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1280
In order to implement the proposed system, the AcSIP LoRa WAN EVK+Antenna KIT S76SXB of
the ACSIP Technology Corp was used. This development kit can be considered as a really effective platform
for the popose of technical developing and testing of the AcSIP S76S SIP LoRa module employing
LoRaWAN protocol as shown in Table 1 [33]. Because USB-to-UART chip is included in the developer
board, testing and programming of the MCU becomes more easily. Moreover, since a Micro-USB connector
is used in the interface, it can power the modules. In addition, the sensors used in the slave nodes play an
important role in the proposed system because they affect directly to accuracy and dependability of
the system. In the proposed system, the DS18B20 sensor was used to measure the temperature due to its high
accuracy and low power consumption. In order to measure the precipitation, the system employs a box to
contain water. This box contains the sensor to measure the water level and has a normal closed valse.
The valse will be opened daily to evaluate the daily precipitation.
Table 1. LoraWAN parameters
LoraWAN parameters Value
Frequency 433 MHz
Bandwidth 125 KHz
Spreading Factor 10
Coding Rate 4/5
Tx Power 7 dBm
Sensitivity -137 dBm
Payload length 64 bytes
CRC on payload Enable
Distance 16 km
3. IMPLEMENTATION RESULTS AND ANALYSIS
3.1. Evaluating precipitation
In the proposed system, three main precipitation indexes were analyzed, the Standardized
Precipitation Index (SPI) [34], the Precipitaion Effectiveness Index (P-E index) [35] and the De Martonne
aridity index (Iar-DM) [36]. These indexes will be clarified briefly as follows. The first index, SPI, can be
defined as following equation:
SPI =
P - P
s
(1)
where P and P are the precipitation and the average precipitation (in mm) in defined time period,
respectively. The σ parameter is the standard deviation of the precipitation. In fact, the SPI can determine
the wetness value in different time periods as 1, 3, 6 months; 1, 2 years, and so on based on the application of
user, ranging from -2.0 to +2.0 as shown in Table 2. In the proposed system, the time period was chosen as
one month.
Table 2. The range of the SPI value
SPI value Climate condition
≥2 Extremely wet
1.50 ÷ 1.99 Very wet
1.00 ÷ 1.49 Moderately wet
-0.99 ÷ 0.99 Near normal
-1.49 ÷ -1.00 Moderately dry
-1.99 ÷ -1.50 Severely dry
≤-2 Extremely dry
The second index, (P-E index), was introduced by Thornthwaite and used to analyze the climate. The index is
defined by the following equation:
P-E = 115(
P
T -10
)10/9
i=1
12
å (2)
Where P and T are the mean monthly precipitation in inches and temperature in F as shown in Table 3.
Int J Elec & Comp Eng ISSN: 2088-8708 
A long range, energy efficient Internet of Things based drought monitoring system (Van-Phuc Hoang)
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Table 3. The range of the P-E index value
P-E value Climate condition
≥ 128 Wet
64 ÷ 127 Humid
31 ÷ 64 Sub-hummid
16 ÷ 31 Semi-arid
≤ 15 Arid
The third index, Iar-DM, is the suggestive indicator for the characterization of the aridity index which is
introduced by De Martonne, being clarified by the following equation:
12
Iar
10m
P
DM
T
- =

(3)
Here, P and are the total monthly precipitation and the mean monthly temperature, respectively.
In the equation (3), the additional value of 10°C is added to the mean monthly temperature in order to make
positive results in some regions having the negative average annual temperatures such as mountainous and
desert areas. The Iar-DM index is basically used to evaluate the climate and subsequently used in
the clarification of soil hydrologic regime as shown in Table 4.
3.2. The proposed method of precipitation evaluation
In our experimental system, there are one master node and three slave nodes in which each slave
node is assigned by one code. In this paper, the working process of the proposed system will be illustrated
clearly. First of all, the master node frequently sends the slave node code in the circle in which each node
code will be sent in given number of minutes as shown in Figure 3a. Second, when the slave node receives its
node code, it will measure the temperature and precipitation, transmitting these information to the master
node as shown in Figure 3b. The master node controls all the slave nodes and every day the master node send
a reset instruction to all the slave nodes in order to collect data for new day. Finally, when the master node
receives data from the slave node, it will transmit this data to sever computer as shown in Figure 3a. The
sever computer will analyze and calculate the defined indexes and informs the climate condition. All this
information will be shown on the website.
Table 4. The range of the Iar-DM index value
Iar-DM value Climate condition
≥ 60 Very wet
30 ÷ 60 Wet
20 ÷ 30 Mildly wet
15 ÷ 20 Semi-dry
5 ÷ 15 Dry
0 ÷ 5 Very dry
3.3. Power consumption of the system
For many smart electronic systems, the power consumption is the key factor which determines
the dependability and the effectiveness. In the proposed system, the power consumption of the slave node is
the most important because they are set far from the control center. On the other hand, the power
consumption of the master node and the sever computer is not necessary because they are set in the control
center. As a result, in this paper the energy consumption of the slave node will be calculated mathematically
and tested in the real system.
In our system, the period of each slave node is 5 minutes (300 seconds) insitting of 290 seconds in
waiting mode and 10 seconds in reading and sending mode. Depending on the datasheet of devices, the total
current is about 9 mA in the waiting mode and is 61.4 mA in the reading and sending mode in which
the current of the LoRa s76s kit, DS18b20 sensor and the precipitation sensor are 49 mA, 1mA and 14.1 mA,
respectively. Consequently, the total average current can be calculated approximately as:
0
9*290 64.1*10
10.8( )
300
I mA

= = (4)
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Int J Elec & Comp Eng, Vol. 10, No. 2, April 2020 : 1278 - 1287
1282
In the experimental system, we used two Ultrafire 18600 batteries combined parallel in which each
battery capacity is 4800mAh. As a result, the average life time of the slave node will be:
4800*2
888.9( ) 37( )
10.8
LifeT hours days= = = (5)
In fact, the real average life time of the slave node is about 35 days. This life time is reasonable, however,
it does not meet requirement of the modem smart and automatic systems. To overcome this problem,
we proposed two types of energy for the slave node that are solar energy and solar energy combined with
standby battery, depending on the sunlight condition. After one-year testing, the solar energy has illustrated
its high dependability and efficiency.
3.4. Demonstration system
In this work, we have designed a complete system consiting of both hardware and software for
drought monitoring. After testing in the real condition in three areas in Hanoi, the proposed system has
proved its high effectiveness and dependability. In order to produce convenience to user, the Google map is
also intergated into our website, consiquently, the user can easily find out information about temperature,
precipitation, drought index and drought degree by one click to the slave node area as shown in Figure 4.
After testing the proposed system in three areas in Hanoi (Cau Giay, Phuong Canh and Academy of Finance),
the system has produced the dependable information about the temperature and precipitation all the year as in
Figures 5-7 and the drought index and the drought degree as in Figures 8-10. By analyzing this information,
climate experts can support the government and authority to make and adjust plan to overcome drought
problem. The proposed system can be considered as a potential candidate to solve partly the climate change
and global warning in order to bring better life for people.
Start
Setting parameter
Node=1
Have data
Send Node
Receive
Send to Raspberry
Node=Node+1
Node>3
False
TrueFalse
Time = 24h
Send Reset
True
True
False
(a)
Start
Setting parameter
Receive data
Data=My code
Read Temperature
Send data
True
False
Data=Reset
Open valve
Close valveRead Rainfall
Close valve
True
False
(b)
Figure 3. The working algorithms of the master (a) and slave (b) nodes
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A long range, energy efficient Internet of Things based drought monitoring system (Van-Phuc Hoang)
1283
Figure 4. The map of the slave node distribution
Figure 5. Temperature and precipitaion in Cau Giay district
Figure 6. Temperature and precipitaion in Phuong Canh
 ISSN: 2088-8708
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Figure 7. Temperature and precipitaion in Academy of Finance
Figure 8. P-E index
Figure 9. SPI index
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A long range, energy efficient Internet of Things based drought monitoring system (Van-Phuc Hoang)
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Figure 10. Iar-DM index
4. CONCLUSION
In this paper, a complete system based on IoT has been designed and tested for drought monitoring.
The proposed system has shown its high dependability and effectiveness. We believe that the proposed
system can be a potential solution to support our government to solve the climate change issuses that has
been affecting significantly and suffering to economics, society and the life condition in Vietnam.
For the future work, the proposed system needs to be tested for more time and area to prove its benefits.
We also need to improve protocol to control the slave node more effeciently when the number of the slave
node increases to cover a wider area.
ACKNOWLEDGMENT
This research is funded by Vingroup Innovation Foundation (VINIF) under the grant number
VINIF.2019.17.
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BIBLIOGRAPHY OF AUTHORS
Van-Phuc Hoang was born in Hung Yen Province, Vietnam. He received PhD degree in
Electronic Engineering from the University of Electro-Communications, Tokyo, Japan in 2012.
He has worked as Postdoc researcher, visiting scholar at the University of Electro-
Communications, Tokyo, Japan and Universiy of Strathclyde, Glasgow, UK during the period of
2012-2014. He is working as an Associate Professor, Deputy Head of The Department of
Microprocessor Engineering, Le Quy Don Technical University, Hanoi, Vietnam. His research
interests include embedded systems for Internet of Things, VLSI architecture for digital signal
processing, digital circuits and systems, low power IC design and hardware security.
Minh-Hong Nguyen was born in 1960. He received PhD degree in Automation Engineering from
Le Quy Don Technical University, Hanoi, Vietnam. He is working as the Deputy Director of
Center for Automation Engineering, Le Quy Don Technical University. His research interests
include automation engineering, embedded systems for Internet of Things, VLSI architecture for
digital signal processing, digital circuits and systems.
Thanh Quan Do was born in Hung Yen Province, Vietnam. He received PhD degree in Electronic
Engineering Yokohama National University, Japan in 2017. His research interests include wireless
communications, Internet of Things, digital circuits and systems, advanced digital signal
processing algorithms.
Dinh-Nhan Le is a Bachelor student of Le Quy Don Technical University, Hanoi, Vietnam.
He was the leader of a student scientific research team receiving the Certificate of Merit from
the university president for the excellent research achievement. His research interests include
embedded systems for Internet of Things, automation engineering and advanced digital signal
processing algorithms.
Du Duong Bui received PhD degree at Tokyo Metropolitan University, Japan in 2011. He has 14-
year experience in teaching, research and management in the areas of Water resources & Climate
change: Impacts and Adaptation; Disaster management including drought management, mitigating
water-related risks; Water management policy and water governance. He is founder of the Vietnam
Water Cooperation Initiative - a global platform hosted by Vietnam to promote water
collaborations with worldwide partners. He has visit more than 20 countries around the world and
published extensively, including peer-reviewed articles and book chapters.

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A long range, energy efficient Internet of Things based drought monitoring system

  • 1. International Journal of Electrical and Computer Engineering (IJECE) Vol. 10, No. 2, April 2020, pp. 1278~1287 ISSN: 2088-8708, DOI: 10.11591/ijece.v10i2.pp1278-1287  1278 Journal homepage: http://ijece.iaescore.com/index.php/IJECE A long range, energy efficient Internet of Things based drought monitoring system Van-Phuc Hoang1 , Minh-Hong Nguyen2 , Thanh Quan Do3 , Dinh-Nhan Le4 , Du Duong Bui5 1,2,3,4 Le Quy Don Technical University, 236 Hoang Quoc Viet Str., Hanoi, Vietnam 5 National Center for Water Resources Planning and Investigation (NAWAPI), Hanoi, Vietnam Article Info ABSTRACT Article history: Received May 30, 2019 Revised Oct 1, 2019 Accepted Oct 11, 2019 The climate change and global warning have been appeared as an emerging issue in recent decades. In which, the drought problem has been influenced on economics and life condition in Vietnam. In order to solve this problem, in this paper, we have designed and deployed a long range and energy efficient drought monitoring based on IoT (Internet of Things) for real time applications. After being tested in the real condition, the proposed system has proved its high dependability and effectiveness. The system is promising to become a potential candidate to solve the drought problem in Vietnam. Keywords: Environment Monitoring Internet of Things LORA Smart Water Copyright © 2020 Institute of Advanced Engineering and Science. All rights reserved. Corresponding Author: Van-Phuc Hoang, Department of Microprocessor Engineering, Le Quy Don Technical University, 236 Hoang Quoc Viet Str., Hanoi, Vietnam Email: phuchv@lqdtu.edu.vn 1. INTRODUCTION In recent years, Internet of Things (IoT) is the key word that there are a large number of people looking for and it is a part of the fourth industrial revolution. Many researchs [1-5] related to this subject have been performed with many different areas, such as healthcare, transportation, smart infrastructure, smart city, etc. Howerver, most of these applications have different requirements, operate in different environments, so all equipment of each application have to be designed the most optimal to achieve the highest effectiveness. Especially, one of these applications is smart environment monitoring system based on IoT that can provide real time data. In the past few decades, there have been a large number of researchers focus on applications related to Wireless Sensor Networks (WSNs), Wireless Body Area Networks (WBANs), IoT with a variety of different platforms [6-33]. In these designs, microcontrollers (MCU) which are often ultra-low power chips were chosen to reduce the systempower consumption and MSP430 family from Texas Instrument (TI) is a good choice [8-10, 13]. Moreover, some transceivers were used in these works, including Wi-Fi module, bluetooth module, Radio Frequency (RF) module with many different protocols. Especially, authors in [10] presented the comparison of different wireless transmission modules to give the best choice for a detailed application. In addition, in recent years, smart cities have concerning in many countries, so Wi-Fi will cover most of place in the future. Therefore, using Wi-Fi modules as transceiver should be used in applications related to WSN, WBAN, IoT. With each application which has different functions, sensors will be chosen to ensure the lowest power consumption and the highest accuracy. However, to provide long range communications, energy efficient and real time monitoring, in this paper, LORA technology is used.
  • 2. Int J Elec & Comp Eng ISSN: 2088-8708  A long range, energy efficient Internet of Things based drought monitoring system (Van-Phuc Hoang) 1279 In Vietnam, the drought has appeared as a burning issue and seriously influenced on economics, society and the daily life for recent years. In addition, the drought increases significantly the level and widens the affected area, leading to critical consequence if it is not controlled effectively as reported in [34]. As a result, the early drought warning and monitoring is an essential solution to address this matter. In this work, we have researched, designed and implemented a really full worked-out system based on LORA technology drought for monitoring, consisting of both hardware and monitoring software. After a number of experiments, the system has demonstrated the effectiveness and stable working. The rest of this paper is organized as follows. Section 2 describes the system architecture. Section 3 shows data analysis and processing method. Section 4 presents the implementation results and finally, Section 5 concludes of the paper. 2. SYSTEM DESIGN The proposed IoT based drought monitoring system has three main sectors including slave node, master node and monitor software as shown in Figure 1. These sectors are connected throught an IoT platform with LORA, Wi-Fi and Internet systems. The slave nodes will collect temperature and precipitation information and then transmit this information to master node as shown in Figure 2. Since there have many slave nodes, each node will be assigned a code. When the slave node receives an instruction from the master node, it will transmit data. Consequently, data management of the slave node is more efficient and the slave node power consumption is reduced. On the other hand, the master node roles are to monitor and control the slave nodes, to collect data and then to calculate the drought parameters and transmit this information to website. The website will show the recent temperature and precipitation data of all slave nodes, daily and monthly average temperature and precipitation, and the SPI, PE and J index. All these parameters will be analyzed in order to state the drought level of each area and predict the drought trend in the future. Figure 1. System block diagram of proposed IoT based drought monitoring system Figure 2. The master (right side) and slave (left side) nodes hardware
  • 3.  ISSN: 2088-8708 Int J Elec & Comp Eng, Vol. 10, No. 2, April 2020 : 1278 - 1287 1280 In order to implement the proposed system, the AcSIP LoRa WAN EVK+Antenna KIT S76SXB of the ACSIP Technology Corp was used. This development kit can be considered as a really effective platform for the popose of technical developing and testing of the AcSIP S76S SIP LoRa module employing LoRaWAN protocol as shown in Table 1 [33]. Because USB-to-UART chip is included in the developer board, testing and programming of the MCU becomes more easily. Moreover, since a Micro-USB connector is used in the interface, it can power the modules. In addition, the sensors used in the slave nodes play an important role in the proposed system because they affect directly to accuracy and dependability of the system. In the proposed system, the DS18B20 sensor was used to measure the temperature due to its high accuracy and low power consumption. In order to measure the precipitation, the system employs a box to contain water. This box contains the sensor to measure the water level and has a normal closed valse. The valse will be opened daily to evaluate the daily precipitation. Table 1. LoraWAN parameters LoraWAN parameters Value Frequency 433 MHz Bandwidth 125 KHz Spreading Factor 10 Coding Rate 4/5 Tx Power 7 dBm Sensitivity -137 dBm Payload length 64 bytes CRC on payload Enable Distance 16 km 3. IMPLEMENTATION RESULTS AND ANALYSIS 3.1. Evaluating precipitation In the proposed system, three main precipitation indexes were analyzed, the Standardized Precipitation Index (SPI) [34], the Precipitaion Effectiveness Index (P-E index) [35] and the De Martonne aridity index (Iar-DM) [36]. These indexes will be clarified briefly as follows. The first index, SPI, can be defined as following equation: SPI = P - P s (1) where P and P are the precipitation and the average precipitation (in mm) in defined time period, respectively. The σ parameter is the standard deviation of the precipitation. In fact, the SPI can determine the wetness value in different time periods as 1, 3, 6 months; 1, 2 years, and so on based on the application of user, ranging from -2.0 to +2.0 as shown in Table 2. In the proposed system, the time period was chosen as one month. Table 2. The range of the SPI value SPI value Climate condition ≥2 Extremely wet 1.50 ÷ 1.99 Very wet 1.00 ÷ 1.49 Moderately wet -0.99 ÷ 0.99 Near normal -1.49 ÷ -1.00 Moderately dry -1.99 ÷ -1.50 Severely dry ≤-2 Extremely dry The second index, (P-E index), was introduced by Thornthwaite and used to analyze the climate. The index is defined by the following equation: P-E = 115( P T -10 )10/9 i=1 12 å (2) Where P and T are the mean monthly precipitation in inches and temperature in F as shown in Table 3.
  • 4. Int J Elec & Comp Eng ISSN: 2088-8708  A long range, energy efficient Internet of Things based drought monitoring system (Van-Phuc Hoang) 1281 Table 3. The range of the P-E index value P-E value Climate condition ≥ 128 Wet 64 ÷ 127 Humid 31 ÷ 64 Sub-hummid 16 ÷ 31 Semi-arid ≤ 15 Arid The third index, Iar-DM, is the suggestive indicator for the characterization of the aridity index which is introduced by De Martonne, being clarified by the following equation: 12 Iar 10m P DM T - =  (3) Here, P and are the total monthly precipitation and the mean monthly temperature, respectively. In the equation (3), the additional value of 10°C is added to the mean monthly temperature in order to make positive results in some regions having the negative average annual temperatures such as mountainous and desert areas. The Iar-DM index is basically used to evaluate the climate and subsequently used in the clarification of soil hydrologic regime as shown in Table 4. 3.2. The proposed method of precipitation evaluation In our experimental system, there are one master node and three slave nodes in which each slave node is assigned by one code. In this paper, the working process of the proposed system will be illustrated clearly. First of all, the master node frequently sends the slave node code in the circle in which each node code will be sent in given number of minutes as shown in Figure 3a. Second, when the slave node receives its node code, it will measure the temperature and precipitation, transmitting these information to the master node as shown in Figure 3b. The master node controls all the slave nodes and every day the master node send a reset instruction to all the slave nodes in order to collect data for new day. Finally, when the master node receives data from the slave node, it will transmit this data to sever computer as shown in Figure 3a. The sever computer will analyze and calculate the defined indexes and informs the climate condition. All this information will be shown on the website. Table 4. The range of the Iar-DM index value Iar-DM value Climate condition ≥ 60 Very wet 30 ÷ 60 Wet 20 ÷ 30 Mildly wet 15 ÷ 20 Semi-dry 5 ÷ 15 Dry 0 ÷ 5 Very dry 3.3. Power consumption of the system For many smart electronic systems, the power consumption is the key factor which determines the dependability and the effectiveness. In the proposed system, the power consumption of the slave node is the most important because they are set far from the control center. On the other hand, the power consumption of the master node and the sever computer is not necessary because they are set in the control center. As a result, in this paper the energy consumption of the slave node will be calculated mathematically and tested in the real system. In our system, the period of each slave node is 5 minutes (300 seconds) insitting of 290 seconds in waiting mode and 10 seconds in reading and sending mode. Depending on the datasheet of devices, the total current is about 9 mA in the waiting mode and is 61.4 mA in the reading and sending mode in which the current of the LoRa s76s kit, DS18b20 sensor and the precipitation sensor are 49 mA, 1mA and 14.1 mA, respectively. Consequently, the total average current can be calculated approximately as: 0 9*290 64.1*10 10.8( ) 300 I mA  = = (4)
  • 5.  ISSN: 2088-8708 Int J Elec & Comp Eng, Vol. 10, No. 2, April 2020 : 1278 - 1287 1282 In the experimental system, we used two Ultrafire 18600 batteries combined parallel in which each battery capacity is 4800mAh. As a result, the average life time of the slave node will be: 4800*2 888.9( ) 37( ) 10.8 LifeT hours days= = = (5) In fact, the real average life time of the slave node is about 35 days. This life time is reasonable, however, it does not meet requirement of the modem smart and automatic systems. To overcome this problem, we proposed two types of energy for the slave node that are solar energy and solar energy combined with standby battery, depending on the sunlight condition. After one-year testing, the solar energy has illustrated its high dependability and efficiency. 3.4. Demonstration system In this work, we have designed a complete system consiting of both hardware and software for drought monitoring. After testing in the real condition in three areas in Hanoi, the proposed system has proved its high effectiveness and dependability. In order to produce convenience to user, the Google map is also intergated into our website, consiquently, the user can easily find out information about temperature, precipitation, drought index and drought degree by one click to the slave node area as shown in Figure 4. After testing the proposed system in three areas in Hanoi (Cau Giay, Phuong Canh and Academy of Finance), the system has produced the dependable information about the temperature and precipitation all the year as in Figures 5-7 and the drought index and the drought degree as in Figures 8-10. By analyzing this information, climate experts can support the government and authority to make and adjust plan to overcome drought problem. The proposed system can be considered as a potential candidate to solve partly the climate change and global warning in order to bring better life for people. Start Setting parameter Node=1 Have data Send Node Receive Send to Raspberry Node=Node+1 Node>3 False TrueFalse Time = 24h Send Reset True True False (a) Start Setting parameter Receive data Data=My code Read Temperature Send data True False Data=Reset Open valve Close valveRead Rainfall Close valve True False (b) Figure 3. The working algorithms of the master (a) and slave (b) nodes
  • 6. Int J Elec & Comp Eng ISSN: 2088-8708  A long range, energy efficient Internet of Things based drought monitoring system (Van-Phuc Hoang) 1283 Figure 4. The map of the slave node distribution Figure 5. Temperature and precipitaion in Cau Giay district Figure 6. Temperature and precipitaion in Phuong Canh
  • 7.  ISSN: 2088-8708 Int J Elec & Comp Eng, Vol. 10, No. 2, April 2020 : 1278 - 1287 1284 Figure 7. Temperature and precipitaion in Academy of Finance Figure 8. P-E index Figure 9. SPI index
  • 8. Int J Elec & Comp Eng ISSN: 2088-8708  A long range, energy efficient Internet of Things based drought monitoring system (Van-Phuc Hoang) 1285 Figure 10. Iar-DM index 4. CONCLUSION In this paper, a complete system based on IoT has been designed and tested for drought monitoring. The proposed system has shown its high dependability and effectiveness. We believe that the proposed system can be a potential solution to support our government to solve the climate change issuses that has been affecting significantly and suffering to economics, society and the life condition in Vietnam. For the future work, the proposed system needs to be tested for more time and area to prove its benefits. We also need to improve protocol to control the slave node more effeciently when the number of the slave node increases to cover a wider area. ACKNOWLEDGMENT This research is funded by Vingroup Innovation Foundation (VINIF) under the grant number VINIF.2019.17. REFERENCES [1] L. Boves and E. den Os, "Speaker recognition in telecom applications," Proceedings. 1998 IEEE 4th Workshop, Interactive Voice Technology for Telecommunications Applications, 1998. IVTTA '98. Torino, pp. 203-208, 1998. [2] I. V. McLoughlin and Hamid Reza Sharifzadeh, "Speech recognition engine adaptions for smart home dialogues," 2007 6th International Conference on Information, Communications & Signal Processing, Singapore, pp. 1-5, 2007. [3] E. Marchetto, F. Avanzini and F. Flego, "An automatic speaker recognition system for intelligence applications," 2009 17th European Signal Processing Conference, Glasgow, pp. 1612-1616, 2009. [4] K. Selvan, A. Joseph and K. K. Anish Babu, "Speaker recognition system for security applications," 2013 IEEE Recent Advances in Intelligent Computational Systems (RAICS), Trivandrum, pp. 26-30, 2013. [5] R. Ajgou, S. Sbaa, S. Ghendir, A. Chamsa and A. Taleb-Ahmed, "Robust remote speaker recognition system based on AR-MFCC features and efficient speech activity detection algorithm," 2014 11th International Symposium on Wireless Communications Systems (ISWCS), Barcelona, pp. 722-727, 2014. [6] O. Hahm, E. Baccelli, H. Petersen and N. Tsiftes, “Operating Systems for Low-End Devices in the Internet of Things: A Survey,” in IEEE Internet of Things Journal, vol. 3, no. 5, pp. 720-734, Oct. 2016. [7] S. M. R. Islam, D. Kwak, M. H. Kabir, M. Hossain and K. S. Kwak, “The Internet of Things for Health Care: A Comprehensive Survey,” in IEEE Access, vol. 3, no. , pp. 678-708, 2015. [8] A. Kamilaris and A. Pitsillides, “Mobile Phone Computing and the Internet of Things: A Survey,” in IEEE Internet of Things Journal, vol. 3, no. 6, pp. 885-898, Dec. 2016. [9] C. Perera, C. H. Liu, S. Jayawardena and M. Chen, “A Survey on Internet of Things from Industrial Market Perspective,” in IEEE Access, vol. 2, pp. 1660-1679, 2014.
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Zou, “The design of oil drilling wireless data acquisition system,” 2011 International Conference on Electrical and Control Engineering, Yichang, 2011, pp. 1810-1813. [15] Y. Wang, C. Hu, Z. Feng and Y. Ren, “Wireless transmission module comparison,” 2014 IEEE International Conference on Information and Automation (ICIA), Hailar, 2014, pp. 902-907. [16] H. Kim, J. Shin, H. Shin and B. Song, “Design and Implementation of Gateways and Sensor nodes for Monitoring Gas Facilities,” 2015 Fourth International Conference on Information Science and Industrial Applications (ISI), Busan, 2015, pp. 3-5. [17] D. Spirjakin, A. M. Baranov and V. Sleptsov, “Design of smart dust sensor node for combustible gas leakage monitoring,” 2015 Federated Conference on Computer Science and Information Systems (FedCSIS), Lodz, 2015, pp. 1279-1283. [18] D. Oletic and V. Bilas, “Design of sensor node for air quality crowdsensing,” 2015 IEEE Sensors Applications Symposium (SAS), Zadar, 2015, pp. 1-5. [19] P. Dhar and P. Gupta, “Intelligent parking Cloud services based on IoT using MQTT protocol,” 2016 International Conference on Automatic Control and Dynamic Optimization Techniques (ICACDOT), pp. 30-34, Pune, 2016. [20] R. Y. Rodriquez, M. R. Julcapoma and R. A. Jacinto, “Network monitoring environmental quality in agriculture and pisciculture with low power sensor nodes based on Zigbee and GPRS technology,” 2016 IEEE XXIII International Congress on Electronics, Electrical Engineering and Computing (INTERCON) , pp. 1-6, Piura, 2016. [21] X. Zhang; J. Du; C. Fan; D. Liu; J. Fang; L. Wang, “A wireless sensor monitoring node based on automatic tracking solar-powered panel for paddy field environment,” IEEE Internet of Things Journal , vol.PP, no.99, pp.1- 1, 2017. [22] D. H. Kang et al., “Room Temperature Control and Fire Alarm/Suppression IoT Service Using MQTT on AWS,” 2017 International Conference on Platform Technology and Service (PlatCon), pp. 1-5, Busan, 2017. [23] A. Gomez; M. Magno; M. F. Lagadec; L. Benini, “Precise, Energy-Efficient Data Acquisition Architecture for Monitoring Radioactivity using Self-Sustainable Wireless Sensor Nodes,” in IEEE Sensors Journal, vol.PP, no. 99, pp.1-1, 2017. [24] J. E. Luzuriaga, J. C. Cano, C. Calafate, P. Manzoni, M. Perez and P. Boronat, “Handling mobility in IoT applications using the MQTT protocol,” 2015 Internet Technologies and Applications (ITA), Wrexham, pp. 245-250, 2015. [25] K. Grgic, I. Speh and I. Hedi, “A web-based IoT solution for monitoring data using MQTT protocol,” 2016 International Conference on Smart Systems and Technologies (SST), Osijek, 2016, pp. 249-253. [26] S. Ahmed, A. Topalov and N. Shakev, “A robotized wireless sensor network based on MQTT cloud computing,” 2017 IEEE International Workshop of Electronics, Control, Measurement, Signals and their Application to Mechatronics (ECMSM), pp. 1-6, Donostia-San Sebastian, 2017. [27] S. M. Kim, H. S. Choi and W. S. Rhee, “IoT home gateway for auto-configuration and management of MQTT devices,” 2015 IEEE Conference on Wireless Sensors (ICWiSe), pp. 12-17, Melaka, 2015. [28] A. Antonic, M. Marjanovic, P. Skoeir and I. P. Zarko, “Comparison of the CUPUS middleware and MQTT protocol for smart city services,” 2015 13th International Conference on Telecommunications (ConTEL), pp. 1-8, Graz, 2015. [29] T. Yokotani and Y. Sasaki, “Comparison with HTTP and MQTT on required network resources for IoT,” 2016 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC), pp. 1-6, Bandung, 2016. [30] K. Rajaram and G. Susanth, “Emulation of IoT gateway for connecting sensor nodes in heterogenous networks,” 2017 International Conference on Computer, Communication and Signal Processing (ICCCSP), pp.1-5, 2017. [31] https://www.cloudmqtt.com. [32] https://reliefweb.int/disaster/dr-2015-000180-vnm. [33] Datasheet “Product specification”, Product name S76S, Version F, Doc No 901-10201, AcSiP Technology Corp., Oct. 2016. [34] Hang Vu-Thanh, Thanh Ngo-Duc, Tan Phan-Vam, “Evolution of meteorological drought characteristics in Vietnam during the 1961–2007 period”, Theoretical and Applied Climatological, Volume 118, Issue 3, p-p 368-370, November 2014. [35] SK Acharya, G C Mishra, Karma P Kaleon, Lalu Das, “People's Perception on Climate Change and a Typical Hill Ecosystem of India”, Krishi Sanskriti Publications, p-p 10-11, New Delhi, 2015. [36] Marius Lungu, Liliana Panaitescu and Simona Niţă, “Aridity, Climatic Risk Phenomenon in Dobrudja”, Present environment and sustainable development, Vol. 5, no. 1, p-p 181-182, 2011.
  • 10. Int J Elec & Comp Eng ISSN: 2088-8708  A long range, energy efficient Internet of Things based drought monitoring system (Van-Phuc Hoang) 1287 BIBLIOGRAPHY OF AUTHORS Van-Phuc Hoang was born in Hung Yen Province, Vietnam. He received PhD degree in Electronic Engineering from the University of Electro-Communications, Tokyo, Japan in 2012. He has worked as Postdoc researcher, visiting scholar at the University of Electro- Communications, Tokyo, Japan and Universiy of Strathclyde, Glasgow, UK during the period of 2012-2014. He is working as an Associate Professor, Deputy Head of The Department of Microprocessor Engineering, Le Quy Don Technical University, Hanoi, Vietnam. His research interests include embedded systems for Internet of Things, VLSI architecture for digital signal processing, digital circuits and systems, low power IC design and hardware security. Minh-Hong Nguyen was born in 1960. He received PhD degree in Automation Engineering from Le Quy Don Technical University, Hanoi, Vietnam. He is working as the Deputy Director of Center for Automation Engineering, Le Quy Don Technical University. His research interests include automation engineering, embedded systems for Internet of Things, VLSI architecture for digital signal processing, digital circuits and systems. Thanh Quan Do was born in Hung Yen Province, Vietnam. He received PhD degree in Electronic Engineering Yokohama National University, Japan in 2017. His research interests include wireless communications, Internet of Things, digital circuits and systems, advanced digital signal processing algorithms. Dinh-Nhan Le is a Bachelor student of Le Quy Don Technical University, Hanoi, Vietnam. He was the leader of a student scientific research team receiving the Certificate of Merit from the university president for the excellent research achievement. His research interests include embedded systems for Internet of Things, automation engineering and advanced digital signal processing algorithms. Du Duong Bui received PhD degree at Tokyo Metropolitan University, Japan in 2011. He has 14- year experience in teaching, research and management in the areas of Water resources & Climate change: Impacts and Adaptation; Disaster management including drought management, mitigating water-related risks; Water management policy and water governance. He is founder of the Vietnam Water Cooperation Initiative - a global platform hosted by Vietnam to promote water collaborations with worldwide partners. He has visit more than 20 countries around the world and published extensively, including peer-reviewed articles and book chapters.