Design of Windstorm Disaster Early Warning System based on IoT

and Hall Effect Sensor in the Critical Area Location

Herman Yuliandoko

, Vivien Arief Wardhany

, Subono

, Sholeh Hadi Pramono

and Ponco Siwindarto

Informatic Engineering Dept., State Polytechnic of Banyuwangi, Kawang, Banyuwangi, Indonesia

Electrical Engineering Dept., Brawijaya University, Malang, East Java, Indonesia

Keywords

Windstorm, Critical, Warning, IoT, Quickly.

Abstract: One of the biggest natural disasters in Banyuwangi is windstorm and it had brought in loss many property and

life. However, the handling information of windstorm to the people in Banyuwangi still uses conventional

way and it made warning information late in people. So they didn’t have time to prepare and protect their

property or life from windstorm. Therefore it is needed a system that can provide windstorm information

quickly, accurately and widely. In this research, it was designed an early warning system (EWS) of windstorm

by placing sensors in the critical locations. The placing of sensor in the right place made the windstorm

detections more accurate. This research also used IoT technology, web site and android application to inform

the wind speed, direction and warning notification quickly.

1 INTRODUCTION

Indonesia is a tropical country with islands and

waters. Besides that Indonesia also have unique

geographic position between two continents Asian -

Australia and two ocean Indian - Pacific. Thus, the

territory of Indonesia is in a cross position, which

has significance in relation to climate and economy

(Nisa, 2014). That position also influence to the

Indonesian

atmosphere which the changing of

Indonesian atmosphere is caused by ITCZ (Inter

Tropic

Convergence Zone), ENSO (El Nino Sothern

Oscillation) and MJO (Madden Jullian Oscillation.

The changes in the atmosphere will bring climate

change, weather and wind in the territory of

Indonesia

(BNPB, 2017).

The extreme change of climate, weather and wind

will bring disaster and one of the most frequent

disasters in Indonesia is windstorm. The windstorm

disaster brought great destruction and one of the

towns that was often hit by a windstorm disaster was

Banyuwangi. The disaster trend in Banyuwangi also

increase especially windstorm as shown in Figure 1.

The disaster management is very important but so

far in Indonesia majority of disaster management

still use traditional way. It is also in Banyuwangi,

east Java, Indonesia, the disaster management still

focused on the disaster impact (Yuliandoko et al.,

2019).

Figure 1: Disaster Trend in Banyuwangi (Hashiguchi et al.,

2013).

One of important aspect on the disaster

management is mitigation. In the mitigation there is

early warning system as a critical life saving tool for

floods, droughts, windstorm and other hazards. The

effective Early warning system (EWS) contains four

component (1) detection, monitoring and fore-

casting the hazards; (2) analysis of risks involved;

(3) dissemination of timely and authoritative

warnings;

and (4) activation of emergency

preparedness and response plans (World, 2009).

Because It is very useful for human life so it is

needed to make any research and improvement on

EWS. Research on EWS in Indonesia is still rare

Yuliandoko, H., Arief Wardhany, V., Subono, ., Hadi Pramono, S. and Siwindarto, P.

Design of Windstorm Disaster Early Warning System based on IoT and Hall Effect Sensor in the Critical Area Location.

DOI: 10.5220/0010962600003260

In Proceedings of the 4th International Conference on Applied Science and Technology on Engineering Science (iCAST-ES 2021), pages 1217-1224

ISBN: 978-989-758-615-6; ISSN: 2975-8246

 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

1217

especially on the small city, and the purpose of this

research is to develop detection and monitoring

windstorm by using technology IoT

with reposition

windstorm sensor on the critical

location in

Banyuwangi city.

Research on web base information of natural

hazard in Aceh province was done by Nasaruddin,

Khairul Muhadi, M. Dirmansyah and Dedi

Yuliansyah. Their research made a conceptual

design

and the development of prototype for ANHIS

(Aceh Natural Hazards Information System). The

main

purpose of ANHIS was to visualize many

natural

hazards maps and disseminate information of

the

hazardous areas for disaster agencies, researchers

and communities in order to help them act on

warning issue (Munadi et al., 2011). There are many

kind of EWS due to the

purpose of the detection of

hazard, in the

“Development of an operational

coastal flooding early warning system”, researcher

made an early warning system to mitigate the loss of

life and property from coastal flooding. The focus of

this

research to develop a coastal flooding warning

system

by integrating existing sea-state monitoring

technology, numerical ocean forecasting models,

historical database and experiences (Doong et al.,

2012). Many EWS research on flooding detections,

one of that is

“Integration Method of Local-global

SVR and Parallel Time Variant PSO in Water Level

Forecasting for Flood Early Warning System”. The

proposed integration method of Parallel Time

Variant

PSO (PTVPSO) and Local-Glob al Support

Vector Regression (SVR) is used to forecast water

level.

Implementation in this study combine SVR as

regression method for forecast the water level,

Local- Global concept take the role for the

minimization for the computing time, while

PTVPSO used in the SVR to obtain maximum

performance and higher accurate

result by optimize

the parameters of SVR (Soebroto et al., 2018).

Research on flooding detection also can be done

trough monitoring of DAM water level and velocity

of water. By monitoring these parameters can get

information that the flood is happening. The data

from sensor will send to smart phone android by

using microcontroller ESP8266 (Yuliandoko et al.,

2017). So the EWS today also use smart technology

to spread the information to the

people with more

accurate and quickly.

Development of information technology after

computer and internet is Internet of Things (IoT)

(Bing, 2014). Today the application of IoT is very

wide and interesting, because by using IoT can

connect all

goods with internet through information

sensing

device.

This ability will help people to control or monitor

other places via the internet. Therefore the

application of IoT in the disaster management will

be very useful for human being. This research also

use

IoT to send data of hazard especially windstorm

speed, direction and level of danger to the people.

By using this system the people will get a danger

notification to their smart phone so they can prepare

themselves from danger of windstorm disaster. This

system also supported by web and android

application to inform the disaster notification. To

make accurate

the windstorm data, sensors are

placed in critical and potential of windstorm occur in

Banyuwangi area.

2 RESEARCH METHOD

2.1 Research Steps

Research of “Windstorm Disaster Early Warning

System on Critical Area Detection Method by

Using IoT Technology” is done on the several step:

•

Building the windstorm sensor detections

Design of sensor detections has relation with

flow of detection and accuracy of detections.

In this research was made to be able to detect

windstorm

speed, windstorm direction and

rainfall. After

detect speed and direction this

system will make a

classification of hazard level

of windstorm.

•

Web and android based.

This system also use web and android based

inform the measurement of sensor to the

people.

The advantages of this system are easy

to monitor by people by using android

application.

•

Classify of the critical location windstorm

disaster

in Banyuwangi

The critical location is very important to make

an accurate detection with early warning

system.

This critical location based on BNSP

(National

Board for Disaster Management)

Banyuwangi

district data.

•

Experiments result

After all of system connected and running

well, the experiments was done on the State

Polytechnic of Banyuwangi LAB to make

sure

that the system can be implemented in

the real

condition.

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2.2 Accident Area Mapping

Banyuwangi consists of 25 sub-districts with

different characteristic of geographic. Although in

some sub-districts accidents often occur due to strong

wind. The accident was usually in the form of fallen

trees, damaged agricultural land or damaged houses.

Based on BNPB (National Board for Disaster

Management) Banyuwangi district, there were four

sub-districts had high frequency of accident.

Figure 2: Accident Area Mapping in Banyuwangi

(Bencana, 2015).

Refer to Figure 2, Sub-Districts Gambiran,

Rogojampi, Banyuwangi and Glagah had highest

frequency windstorm occur. Therefore these area

become critical area detection of windstorm in

Banyuwangi. This localization of area detection was

very important because these areas had great potential

for windstorm events in the region each year. The

critical location will be the location of windstorm

disaster sensor.

2.3 Disaster Warning System Propose

The most important in the warning system is fast

and accurate information. If the people get an early

accurate information, they can prepare to safe their

live or property. In the BNSP Banyuwangi District

have a mechanism to inform windstorm disaster to the

people as shown in Figure 3, however the mechanism

too complicated and it can cause the delivery of

late

information to the people.

Figure 3: Current BNSP Flow Diagram of Early Warning

System in Banyuwangi (Bencana, 2015).

Therefore it is needed a simple information flow to

the people with a simple way but accurate

information. The simple and fastest sharing

information today is internet, by using internet

network the information can be received by the

people in the fastest way. Beside that an android

application can make the people easy to get detail

information. The application of this method is an

EWS (Early Warning System) application as shown

in Figure 4.

Figure 4: EWS of Windstorm Design System.

3 DEVELOPMENT PROCESS

3.1 Embedded System Preparation

The development of the computer world is

currently so fast and one of them is embedded system.

Embedded system or mini computer is smart

equipment which has microcontroller and the

programming system inside. Embedded system also

has ability to control and monitor the performance of

equipment (Susanti et al., 2018).

Design of Windstorm Disaster Early Warning System based on IoT and Hall Effect Sensor in the Critical Area Location

1219

Figure 5: General Purpose Input Output(GPIO) Raspberry

pi 3 pin schematic diagram (Vatsal and Bhavin, 2017).

In this research use Raspberry pi 3 for embedded

system because Raspberry pi 3 has been equipped

with wireless network. The sensor connections to the

Raspberry pi 3 as shown in Figure 5 and Figure 6

below diagram.

Figure 6: Raspberry pi 3 to sensor diagram.

3.2 Sensors Preparations

There were two main sensors in this system, wind

speed sensor and wind direction sensor.

3.2.1 Wind Speed Sensor and Wind

Directions Sensor

This sensor use bowl propeller to catch wind

movement and convert it to the wind speed

measurement. The bowl propeller was made by using

3D printer with filament material as below Figure

7 design picture.

Figure 7: Wind Speed and Direction Sensor.

In this research use Hall Effect to change the

rotation of bowl propeller become measurement of

wind speed. In the Hall Effect sensor there is a

mechanism to detect the magnetic field come near to

or keep off from the sensor. Then the changing will

be changed to be voltage pulse according to the

frequency of come near to or keep off from the sensor.

Finally the frequency will show a lot of rotation of a

wind speed sensor which will be changed in Km/h.

The block diagram flow of detections is shown in

Figure 8.

Figure 8: General Sensor Block Diagram Based on The

Hall Effect (Krishna and Abraham, 2014).

The Wind Direction sensor used photodiode,

which have a characteristic the resistance will

changethe value if there are light on the photodiode.

The resistance of the photodiode depends on light

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intensity received. Figure 9 explain that the sensor

used to indicate the direction of the wind by LED

as lighting source and photodiode mechanism.

Figure 9: Photodiode, LED and wind direction.

3.3 Web and Application

This research also takes a web and android

application to show the data sensor and give

notification as early warning of windstorm to the

people as shown in Figure 10. In this web there were

location of sensor windstorm, wind speed graph,

highest wind speed, information-tips and data report.

The information of windstorm was not only on web

but in the android application also. The purpose this

application was to give information to the people

about wind speed, direction and windstorm early

warning system by using internet connection.

Figure 10: Web Dashboard of EWS and Splash Screen

Application EWS.

4 EXPERIMENT

There are some levels of wind speed based on

Beaufort standard as mentioned in Tabel 1 below

(Stewart, 2008):

Table 1: Beaufort Wind Scale and State of the Sea.

Beaufort

Numbe

Descriptive

term

m/s Appearance of

the Sea

0 Calm 0 Sea like a mirro

1 Light Air 1.2

Ripples with appearance of

scales; no foam

crests.

2 Light

Breeze

2.8

Small wavelets;

crests of

glassy appearance, not

breaking

3 Gentle

breeze

4.9

Large wavelets;

crests begin

to break; scattered whitecaps.

4 Moderate

breeze

7.7 Small waves, becoming

longer;

numerous whitecaps

Fresh

breeze

10.5

Moderate waves, taking

longer to form; many

whitecaps; some

spray

Strong

breeze

13.1

Large waves forming;

whitecaps everywhere; more

spray

Near gale

15.8

Sea heaps up;

white foam

from

breaking waves begins

to be

blown into streaks.

Gale

1.8

Moderately high waves o

greater length; edges of crests

begin to break into spindrift;

foam is blown in well-

marked streaks.

Strong gale

22.1

High waves; sea

begins to

roll;

dense streaks of foam;

spray may reduce visibility

Storm

25.9

Very high waves with

overhanging crests; sea takes

white appearance

as foam is

blown in very dense

streaks;

rolling is heavy and visibility

reduced

Violent

storm

30.2

Exceptionally high waves; sea

covered with white foam

atches; visibility still more

reduced

Hurricane

35.2

Air is filled with foam; sea

completely white

with driving

spray; visibility greatly

reduced

Windstorm is a strong wind which has a potential

to destroy any kind around it. In BNPB Banyuwangi

district, windstorm has speed 50 Km/h, it’s mean

this categorize in the Beaufort number 7. That why

in this

research danger notification of windstorm

was sent to

the people when wind speed above 50

Km/h.

Design of Windstorm Disaster Early Warning System based on IoT and Hall Effect Sensor in the Critical Area Location

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4.1 Experiment Method

The experiment was done in the Lab Hardware,

State Polytechnic of Banyuwangi. And it was done

with below scenario.

•

The experiment was done to check the

functionality of the EWS on the web based and

android application based.

•

Windstorm detection experiments were done on

there step trial with air compressor blower as

windstorm resource.

•

The windstorm detections based on critical

sensor location and in this trial used one critical

location was Rogojampi area.

•

The there steps of trial based on sensor with

wind compressor spray distance to measure wind

speed. These distances were 300 cm, 200 cm and

70 cm.

5 RESULT AND ANALYSIS

Figure 11: Wind Flow Trial.

In this research functional test by using wind flow

trial as descraibed in Figure 11 with two main

categories, first category was low speed wind (with

distance 200 cm & 300 cm) and second category

was high speed wind (with distance 75 cm). The

wind spray compressor blow the wind directly to the

wind speed sensor surface and found as below result.

Figure 12: Wind Speed Result.

Figure 13: Graphic speed, Critical Location of Windstorm

and Direction.

Refer to Figure 12 and Figure 13, that wind

sensor could

detect wind speed in low speed

category and high speed category. The red line in the

graph on the 50 Km/h was safe wind limit of speed

and trial with distance 75 cm made result until over

safe wind limit

of speed. Its mean this sensor could

detect wind speed until Windstorm category. On the

high speed (windstorm category) was also detect and

give

warning notification as early warning system to

the

people as shown in Figure 14 below:

Figure 14: Web Based, EWS Warning System.

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Figure 15 described that in this research also

made an android application with EWS system to

inform

danger notification to the people.

Figure 15: Real Time Android Based Application, Graphic

and EWS Notification.

By using an android application made the

windstorm information received to the people

quickly

compare to conventional BNSP Banyuwangi

District

Early Warning System flow notification.

5 CONCLUSION

One of an important thing in the disaster

management is early warning system. By using

EWS the information of disaster danger can inform

quickly

and accurately. This research propose a

system EWS for Banyuwangi district based on

android application, web based and IoT technology.

A real time

information become advantages for

people to prepare

and protect their property or life

from windstorm

disaster. Through android

application also made

information could easily

access by people and warning system notification

very useful for people.

These results prove that this

EWS system can detect

windstorm, inform warning

information quickly than conventional way and

easily to use for people. The

main issue show that

the critical location also take an important aspect for

early detection system This

research also gives a

step to make next research with multiple sensors for

deeply information of disaster.

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