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FERNANDO, MICHAEL

AIP Conference Proceedings 2043, 020020 (2018); https://doi.org/10.1063/1.5080039 2043, 020020
© 2018 Author(s).
Designing flood early warning system using
internet of things
Cite as: AIP Conference Proceedings 2043, 020020 (2018); https://doi.org/10.1063/1.5080039
Published Online: 20 November 2018
Michael Fernando, and Ford Lumban Gaol
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Designing Flood Early Warning System Using Internet of 
Things 
Michael Fernando1 and Ford Lumban Gaol2 
1 Master of Information Technology 
   Bina Nusantara University, Indonesia 
    
2 Doctor of Computer Science 
  Bina Nusantara University, Indonesia  
E-mail: 1 michael.fer.tan@gmail.com  
        2 fgaol@binus.edu 
Abstract. Internet of things technology has grown rapidly in recent years. Internet of things can be used for 
environmental monitoring to make an early warning system for disaster. This technology is much needed to warn people 
about flood that usually happen in Jakarta. In this prototype water level sensor are used to measure whether the water 
level has reached a dangerous state and flow rate sensor is used to measure flow rate. In this paper the number of 
notification sent and the time it needed since water level has reached a dangerous state until a notification alert is 
received is measure to see if the notification can be receive before flood happens. The result shows that most of the 
notification received before flood happens. The states of the sensor and internet speed affect the process to send the 
notification. 
INTRODUCTION 
The rapid development of technology nowadays has caused the technology to be integrated in many aspect of 
human’s life. One of the rapidly developing technologies is internet of things. Internet of things can be described as 
a technology that connect physical things with computing capabilities across a wide range of services and 
technologies [1]. 
Internet of things can be used to monitor the environment such as water level, flow rate, rainfall and many other 
things. Because of this, there are many early warning systems for disaster is integrated with internet of things. 
Early warning system for disaster especially flood is needed in Jakarta. From 2011 to 2016, 1210 flood occurred 
in Indonesia and 48 of them occurred in Jakarta [2]. Because of this, the demand of technology to alert citizen is 
high and it has to be fast, accurate, and dependable. 
From this problem, the writer proposed a method to give alert notification about alert status via e-mail or SMS. 
The writer creates a prototype of flood early warning system with 2 sensor, the first one is to measure the water level 
and the second one is to measure the flow rate. 
FLOOD EARLY WARNING SYSTEM 
Flood early warning system is a device that will measure the water level which will enable to know the amount of 
water in a river, it will also know if the water have reached the condition where it’s necessary to alert people about 
the water that has potential to overflow and cause floods [3]. In flood early warning system, cloud computing acts as 
a receiver of data from the sensor, as a computer to analyze, interpret, and providing user with easy to understand 
web based visualization of the data [4]. In this paper to create the prototype, the writer used 2 sensors, which is a 
The 6th International Conference on Science & Engineering in Mathematics, Chemistry and Physics
AIP Conf. Proc. 2043, 020020-1–020020-8; https://doi.org/10.1063/1.5080039
Published by AIP Publishing. 978-0-7354-1769-4/$30.00
020020-1
water level sensor and flow rate sensor, a LinkIt One PCB board, and ubidots as a server to collect data, analyze, and 
sending alert. 
 
Water Level Sensor 
Water level sensor is used for water detection, which can be used in sensing the rainfall, liquid leakage, or in this 
paper it’s used to detect water level.  
TABLE 1. Water level sensor specification 
Specification Minimum Maximum 
Sensor Type Analog 
Operating Voltage 3V 5V 
Working Current 1mA 20mA 
Dimensions 65mm x 20 mm x 8mm 
Detection Area 40 mm x 16 mm 
 
The specifications listed on table 1 above is the specification of water level sensor used in this paper are listed on 
table below and taken from www.fecegypt.com. The detection area of this sensor is 40 mm x 16 mm. This sensor 
works by having a series of exposed traces connected to ground and when water made contact with the exposed 
traces the sensor will detect it and send the data to PCB as a number. The number depends on how big is the surface 
that made contact with water [5]. It can’t detect anything that haven’t made contact with the sensor. 
Flow Rate Sensor 
Flow rate sensor is used to detect the size of the flow of water.  
TABLE 2. Flow rate sensor specification 
Specification Minimum Maximum 
Sensor Type Digital 
Operating Voltage 3V 18V 
Working Current 1mA 15mA 
Water Pressure - 1.75MPa 
Flow Rate 1 L 30 L 
 
The specifications listed on table 2 above is the specification of flow rate sensor used in this paper are listed on table 
below and taken from www.microelectronics.com. The flow rate that can be detected with this sensor is between 1 
litre to 30 litres and this sensor works by having the water flows through rotor components, magnetic rotor rotating, 
and speed along with the flow of a linear change then hall element output corresponding pulse signal feedback to the 
controller [6]. 
 
LinkIt One 
According to wiki.seeed.cc [7] LinkIt One is a PCB board made by collaboration of Seeed Studio and MediaTek to 
made a prototype of devices embedded with internet of things.  
TABLE 3. LinkIt One PCB Board specification 
Specification Value 
Dimensions 3.3 x 2.1 inches 
RAM 4 MB 
Digital Output 3.3v 
Analog Input 5v 
DC Current per I/O pin 1mA 
020020-2
The specifications of LinkIt One PCB board are listed on table below and taken from official LinkIt One website.
This PCB will be used as main processor of the prototype created in this experiment. 
Ubidots 
According to www.ubidots.com [8] Ubidots is an engineering services firm, specializing in hardware and software 
development for internet of things projects. In ubidots, the data from sensor will be analyzed and presented as a line 
diagram. Ubidots also provide the feature to send SMS and e-mail. 
 
 
METHODOLOGY 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
CHART 1. Methodology used in this experiment 
 
Using the technology listed on the previous parts, a method can be devised. There are 5 steps for the method   
Step 1: Measuring flow rate and water level 
Flow rate will be measured every second with flow rate sensor to get an actual data. 
Step 2: Sending data from LinkIt One PCB 
After sensor receive the data. The data will be sent to LinkIt One PCB to be processed. 
Step 3: Sending data to ubidots 
The data processed by LinkIt One will be received by ubidots. After ubidots received the data, a list will be made in 
ubidots sorted by the time of the data received and a graph is made based on the data. 
Step 4: Considering sending alert 
Need to 
send alert 
Measuring flow rate and water level 
Sending data from LinkIt One PCB 
Sending data to ubidots 
Considering sending alert 
Sending Alert 
Don’t need to 
send alert 
020020-3
At this step ubidots will identify the data and compare it with a predetermined threshold. If the data exceed the 
predetermined threshold, alert will be sent. 
Step 5: Sending Alert 
If the data exceed the predetermined threshold alert will be sent via ubidots to e-mail and phone number listed in 
ubidots. If not the step will repeat the first step. 
Data Resources 
In this paper the authors conduct an experiment using flood early warning system prototype made by the author. The 
data obtained from the prototype are flow rate and data from water level sensor. The experiments have 3 sessions 
and every session indicate different condition. The conditions indicate by this experiment is: 
1. When the flow rate every minute is below the limit of the container. 
2. When the flow rate every minute equals the limit of the container. 
3. When the flow rate every minute is more than the limit of the container. 
 The container used in this experiment has height and diameter respectively 24 cm and 22 cm and has a tube shape 
which means limit of the container in this experiment is 9.118 litres while the water level sensor is placed at 
respectively 5 cm, 10 cm, 15 cm, and 20 cm from the bottom of the container. The position of the water level sensor 
is based on Seal (2012) works [9].This indicate the Alert level in Indonesia which is Alert 1, Alert 2, Alert 3, and 
Alert 4. 
EVALUATION 
To evaluate the result, the author use the Accuracy formula [10] listed below: 
ܣܿܿݑݎܽܿݕ ൌ ܾܽ כ ͳͲͲΨ 
The function of this formula is to prove whether the prototype can work properly by calculating the 
x b is number of alert received 
x a is amount of alert that should be sent 
 
For example if the prototype supposed to receive 10 alert but only 7 alert sent therefore the calculation will be 
ܣܿܿݑݎܽܿݕ ൌ  ͹ͳͲ כ ͳͲͲΨ 
That means the accuracy is 70%. 
RESULT 
In this experiment the container used has a 22 cm diameter, 24 cm height, and 9.118 litres volume. The result of the 
experiment can be seen below. 
 
 
 
 
 
 
 
 
 
 
 
 
 
020020-4
TABLE 4. flow rate 1 litre – 7 litre 
No. Flow rate 
average 
(Litre /minute) 
Water level 
sensor height 
(centimeter) 
Alert status 
(sent or not 
sent) 
Time needed to 
received alert 
notification 
Status 
Alert 
Time needed 
to fill 
container 
1 ±1 L/min 5 cm - - Alert IV 540 sec 
2 ±2 L/min 5 cm - - Alert IV 270 sec 
3 ±3L/min 5 cm - - Alert IV 180 sec 
4 ±4 L/min 5 cm - - Alert IV 135 sec 
5 ±5 L/min 5 cm - - Alert IV 108 sec 
6 6.812 L/min 5 cm 3 15 sec Alert IV 90 sec 
6.737 L/min 10 cm - - Alert III 
7 7.477 L/min 5 cm 3 17 sec Alert IV 78 sec 
7.241 L/min 10 cm 3 30 sec Alert III 
7.886 L/min 15 cm - - Alert II 
3: Alert sent 
 
From the table above, can be seen that the prototype get the correct result of 3 times out of all 3 experiments. The 
flow rate average of 1 to 5 litres and the second 6 litres experiment and the third 7 litres experiment stop midway 
because there’s no way the water to reach the height required since the water flow out before it can fill the container. 
 
In the second experiment the author get result listed in the table below: 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
020020-5
 TABLE 5. flow rate 8 litre – 9 litre 
No. Flow rate 
average 
(Litre /minute) 
Water level 
sensor height 
(centimeter) 
Alert status 
(sent or not 
sent) 
Time needed to 
received alert 
notification 
Status 
Alert 
Time needed 
to fill 
container 
1 8.683 L/min 5 cm 3 14 sec Alert IV 68 sec 
8.132 L/min 10 cm 3 28 sec Alert III 
8.498 L/min 15 cm 3 40 sec Alert II 
8.812 L/min 20 cm 3 52 sec Alert I 
2 
 
 
 
9.315 L/min 5 cm 3 12 sec Alert IV 60 sec 
9.791 L/min 10 cm 3 22 sec Alert III 
9.872 L/min 15 cm 3 35 sec Alert II 
9.805 L/min 20 cm 3 45 sec Alert I 
3: Alert sent 
 
Based on table 5 above can be seen that in all experiments alert notification was sent correctly and can be seen that 
everytime the notification sent, the time needed always under the time needed to fill the container. 
 
The result of the third experiment can be seen below: 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
020020-6
TABLE 6 .flow rate more than 9 litre 
No. Flow rate 
average 
(Litre /minute) 
Water level 
sensor height 
(centimeter) 
Alert status 
(sent or not 
sent) 
Time needed to 
received alert 
notification 
Status 
Alert 
Time needed 
to fill 
container 
1 10.524L/min 5 cm 3 11 sec Alert IV 54 sec 
10.174L/min 10 cm 3 20 sec Alert III 
10.846L/min 15 cm 3 32 sec Alert II 
10.538L/min 20 cm 3 45 sec Alert I 
2 
 
 
 
15.542L/min 5 cm 3 7 sec Alert IV 37 sec 
15.204L/min 10 cm 3 14 sec Alert III 
15.696L/min 15 cm - - Alert II 
15.173L/min 20 cm 3 30sec Alert I 
3 20.498L/min 5 cm 3 5 sec Alert IV 27 sec 
20.662L/min 10 cm 3 11 sec Alert III 
20.319L/min 15 cm 3 17 sec Alert II 
20.121L/min 20 cm 3 22 sec Alert I 
3: Alert sent 
 
From the table above can be seen that in every experiment except the third 15 litres the notification was sent and 
receive before it reached the time needed to fill the container. On the third 15 litres notification was not sent, this 
probably happens because of the internet connection was down at the time the experiment is done. 
After all the experiment is done the accuracy is calculated with the formula discussed in the previous 
chapter, this prototype have 95.6% accuracy. 
RESULT 
Based on the result of experiments done, the flood early warning system work properly this can be seen by the 
accuracy achieved. 
 
 
 
020020-7
 REFERENCES 
 
 
[1]  D. Miorandi, S. Sicari, F. De Pellegrini and I. Chlamtac, "Internet of things: Vision, applications and 
research challenges," Science Direct , 2012.  
[2]  "Geospasial Badan Penanggulangan Bencana," 2011. [Online].  
[3]  M. A. Wister, P. Pancardo, A. J. Jara, F. D. Acosta and J. A. Hernandez-Nolasco, "Water Level 
Meter for Alerting Population about Floods," IEEE, 2016.  
[4]  M. A. Wister, P. Pancardo, A. J. Jara, F. D. Acosta and J. A. Hernandez-Nolasco, "Emergency 
population warning about Floods by Social Media," IEEE, 2016.  
[5]  "Emartee," [Online]. Available: www.emartee.com. 
[6]  "Microelectronics," [Online]. Available: 
http://www.microelectronicos.com/datasheets/UCTS0058.pdf. 
[7]  S. Development, "seeed wiki," [Online]. Available: http://wiki.seeed.cc/LinkIt_ONE/. 
[8]  "Ubidots," [Online]. Available: www.ubidotscom. 
[9]  V. Seal, A. Raha, S. Maity, S. K. Mitra, A. Mukherjee and M. K. Naskar, "ASIMPLE FLOOD 
FORECASTING SCHEME USING WIRELESS SENSOR NETWORKS," IJASUC, 2012.  
[10] P. Anne Marie Helmenstine, "ThoughtCo," [Online]. Available: https://www.thoughtco.com/how-to-
calculate-percent-error-609584. 
[11] N. Bari, G. Mani and S. Berkovich, "Internet of Things as a Methodological Concept," IEEE, 2013.  
[12] S. A. Sayed Hussin, M. Ismail and H. Sofian, "INTELLIGENT FLOOD INFORMATION SYSTEM 
VIA SMS (IFIS)," Research Gate, 2012.  
[13] A. Alkandari, M. Alnasheet, Y. Alabduljader and S. M. Moein, "Water Monitoring System using 
Wireless Sensor Network (WSN): Case Study of Kuwait Beaches," IEEE, 2012.  
 
 
020020-8


English

Designing Flood Early Warning System Using

Internet of Things

Sanny, Lim

Form Reviewer "Business Strategy Selection Using SWOT Analysis with ANP and Fuzzy TOPSIS for Improving Competitive Advantage"

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Check Potential Impact of Social Media to Support
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CHOWANDA, ANDRY

 
LEMBAR  
HASIL PENILAIAN SEJAWAT SEBIDANG ATAU PEER REVIEW 
KARYA ILMIAH : PROSIDING* 
 
Judul Makalah : Teaching Social Critique to Adults with A Desktop Horror Myth Game 
Penulis Makalah : Andry Chowanda, S.Kom., M.M., Ph.D., MBCS., CCP 
Jumlah Penulis : 5 orang 
Identitas Pengusul : Penulis pertama/penulis ke-5/penulis korespondensi ** 
Identitas Prosiding :  a. Judul Prosiding : 3rd International Conference on Computer Science and 
Computational Intelligence, ICCSCI 2018 
  b. ISBN/ISSN : 1877-0509 
  c. Tahun Terbit, Tempat Pelaksanaan : 7-8 September 2018, Tangerang, Indonesia 
 d. Penerbit/organize : Elsevier B.V.  
 e. Alamat repository PT/web prosiding  :  
 https://www.sciencedirect.com/science/article/pii/S1877050918315175/pdf?md5=d
2ffcdaab8c0bd0c4377cb85466245ed&pid=1-s2.0-S1877050918315175-main.pdf 
  f. Terindeks di (jika ada)   : Scopus 
 
Kategori Publikasi Makalah 
(beri √ pada kategori yang tepat) 
 Prosiding Forum Ilmiah Internasional Terindeks 
Prosiding Forum Ilmiah Internasional 
Prosiding Forum Nasional 
 
Hasil Penilaian Peer Review : 
  
 
Komponen Yang Dinilai 
Nilai Maksimal Prosiding  
Nilai Akhir 
Yang 
Diperoleh 
Internasional 
Terindeks 
Internasional Nasional 
a. Kelengkapan unsur isi paper (10%) 0.3   0.255 
b. Ruang lingkup dan kedalaman   
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0.9   0.765 
c. Kecukupan dan kemutakhiran   
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0.9   0.765 
d. Kelengkapan unsur dan kualitas terbitan/  
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0.9   0.765 
Total = (100%) 3   2.55 
Nilai Pengusul =  
 
Jakarta, 04-11-2020 
 
 
 
 
 
Dr. Derwin Suhartono, S.Kom., M.T.I. 
Unit kerja: Universitas Bina Nusantara 
 
*Dinilai oleh dua Reviewer secara terpisah 
**Coret yang tidak perlu 
 
 
 
 
 
 
 
 
  
 
√ 
 
 
√ 
 
 
 
LEMBAR  
HASIL PENILAIAN SEJAWAT SEBIDANG ATAU PEER REVIEW 
KARYA ILMIAH : PROSIDING* 
 
Judul Makalah : Teaching Social Critique to Adults with A Desktop Horror Myth Game 
Penulis Makalah : Andry Chowanda, S.Kom., M.M., Ph.D., MBCS., CCP 
Jumlah Penulis : 5 orang 
Identitas Pengusul : Penulis pertama/penulis ke-5/penulis korespondensi ** 
Identitas Prosiding :  a. Judul Prosiding : 3rd International Conference on Computer Science and 
Computational Intelligence, ICCSCI 2018 
  b. ISBN/ISSN : 1877-0509 
  c. Tahun Terbit, Tempat Pelaksanaan : 7-8 September 2018, Tangerang, Indonesia 
 d. Penerbit/organize : Elsevier B.V.  
 e. Alamat repository PT/web prosiding  :  
 https://www.sciencedirect.com/science/article/pii/S1877050918315175/pdf?md5=d
2ffcdaab8c0bd0c4377cb85466245ed&pid=1-s2.0-S1877050918315175-main.pdf 
  f. Terindeks di (jika ada)   : Scopus 
 
Kategori Publikasi Makalah 
(beri √ pada kategori yang tepat) 
 Prosiding Forum Ilmiah Internasional Terindeks 
Prosiding Forum Ilmiah Internasional 
Prosiding Forum Nasional 
 
Hasil Penilaian Peer Review : 
  
 
Komponen Yang Dinilai 
Nilai Maksimal Prosiding  
Nilai Akhir 
Yang 
Diperoleh 
Internasional 
Terindeks 
Internasional Nasional 
a. Kelengkapan unsur isi paper (10%) 0.3   0.24 
b. Ruang lingkup dan kedalaman   
    pembahasan (30%) 
0.9   0.72 
c. Kecukupan dan kemutakhiran   
    data/informasi dan metodologi (30%) 
0.9   0.72 
d. Kelengkapan unsur dan kualitas terbitan/  
    prosiding (30%) 
0.9   0.72 
Total = (100%) 3   2.4 
Nilai Pengusul =  
 
Jakarta, 04-11-2020 
 
 
 
 
 
Dr. Fredy Purnomo, S.Kom., M.Kom. 
Unit kerja: Universitas Bina Nusantara 
 
*Dinilai oleh dua Reviewer secara terpisah 
**Coret yang tidak perlu 
 
 
 
 
 
 
 
 
  
 
√ 
 
 
√ 
 
 


Form Reviewer "Teaching Social Critique to Adults with A Desktop Horror Myth Game "

 
LEMBAR  
HASIL PENILAIAN SEJAWAT SEBIDANG ATAU PEER REVIEW 
KARYA ILMIAH : PROSIDING* 
 
Judul Makalah : Facial Expression Recognition as Dynamic Game Balancing System 
Penulis Makalah : Andry Chowanda, S.Kom., M.M., Ph.D., MBCS., CCP 
Jumlah Penulis : 5 orang 
Identitas Pengusul : Penulis pertama/penulis ke-2/penulis korespondensi ** 
Identitas Prosiding :  a. Judul Prosiding : 3rd International Conference on Computer Science and 
Computational Intelligence, ICCSCI 2018 
  b. ISBN/ISSN : 1877-0509 
  c. Tahun Terbit, Tempat Pelaksanaan : 7-8 September 2018, Tangerang, Indonesia 
 d. Penerbit/organize : Elsevier B.V.  
 e. Alamat repository PT/web prosiding  :  
 https://www.sciencedirect.com/science/article/pii/S1877050918314741/pdf?md5=3
d929846388e6f797f81a54240cd951c&pid=1-s2.0-S1877050918314741-main.pdf 
  f. Terindeks di (jika ada)   : Scopus 
 
Kategori Publikasi Makalah 
(beri √ pada kategori yang tepat) 
 Prosiding Forum Ilmiah Internasional Terindeks 
Prosiding Forum Ilmiah Internasional 
Prosiding Forum Nasional 
 
Hasil Penilaian Peer Review : 
  
 
Komponen Yang Dinilai 
Nilai Maksimal Prosiding  
Nilai Akhir 
Yang 
Diperoleh 
Internasional 
Terindeks 
Internasional Nasional 
a. Kelengkapan unsur isi paper (10%) 0.3   0.255 
b. Ruang lingkup dan kedalaman   
    pembahasan (30%) 
0.9   0.765 
c. Kecukupan dan kemutakhiran   
    data/informasi dan metodologi (30%) 
0.9   0.765 
d. Kelengkapan unsur dan kualitas terbitan/  
    prosiding (30%) 
0.9   0.765 
Total = (100%) 3   2.55 
Nilai Pengusul =  
 
Jakarta, 04-11-2020 
 
 
 
 
 
Dr. Derwin Suhartono, S.Kom., M.T.I. 
Unit kerja: Universitas Bina Nusantara 
 
*Dinilai oleh dua Reviewer secara terpisah 
**Coret yang tidak perlu 
 
 
 
 
 
 
 
 
  
 
√ 
 
 
√ 
 
 
 
LEMBAR  
HASIL PENILAIAN SEJAWAT SEBIDANG ATAU PEER REVIEW 
KARYA ILMIAH : PROSIDING* 
 
Judul Makalah : Facial Expression Recognition as Dynamic Game Balancing System 
Penulis Makalah : Andry Chowanda, S.Kom., M.M., Ph.D., MBCS., CCP 
Jumlah Penulis : 5 orang 
Identitas Pengusul : Penulis pertama/penulis ke-2/penulis korespondensi ** 
Identitas Prosiding :  a. Judul Prosiding : 3rd International Conference on Computer Science and 
Computational Intelligence, ICCSCI 2018 
  b. ISBN/ISSN : 1877-0509 
  c. Tahun Terbit, Tempat Pelaksanaan : 7-8 September 2018, Tangerang, Indonesia 
 d. Penerbit/organize : Elsevier B.V.  
 e. Alamat repository PT/web prosiding  :  
 https://www.sciencedirect.com/science/article/pii/S1877050918314741/pdf?md5=3
d929846388e6f797f81a54240cd951c&pid=1-s2.0-S1877050918314741-main.pdf 
  f. Terindeks di (jika ada)   : Scopus 
 
Kategori Publikasi Makalah 
(beri √ pada kategori yang tepat) 
 Prosiding Forum Ilmiah Internasional Terindeks 
Prosiding Forum Ilmiah Internasional 
Prosiding Forum Nasional 
 
Hasil Penilaian Peer Review : 
  
 
Komponen Yang Dinilai 
Nilai Maksimal Prosiding  
Nilai Akhir 
Yang 
Diperoleh 
Internasional 
Terindeks 
Internasional Nasional 
a. Kelengkapan unsur isi paper (10%) 0.3   0.24 
b. Ruang lingkup dan kedalaman   
    pembahasan (30%) 
0.9   0.72 
c. Kecukupan dan kemutakhiran   
    data/informasi dan metodologi (30%) 
0.9   0.72 
d. Kelengkapan unsur dan kualitas terbitan/  
    prosiding (30%) 
0.9   0.72 
Total = (100%) 3   2.4 
Nilai Pengusul =  
 
Jakarta, 04-11-2020 
 
 
 
 
 
Dr. Fredy Purnomo, S.Kom., M.Kom. 
Unit kerja: Universitas Bina Nusantara 
 
*Dinilai oleh dua Reviewer secara terpisah 
**Coret yang tidak perlu 
 
 
 
 
 
 
 √ 
 
 
 
  
 
√ 
 
 


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