An earthquake early warning system is proposed that uses wireless sensor networks and the Internet of Things. Sensors placed on the ground surface can detect P and S seismic waves from an earthquake. The faster moving P waves trigger alerts that are transmitted via Zigbee transmitters to a gateway and then through the Internet of Things to smartphones, providing early warning before the slower but stronger S waves arrive. This could help save many human lives. The system design includes sensors, Arduino/NodeMCU microcontrollers, software components like Embedded C, and outputs alerts through phones and emails. Evaluation of the system shows it can successfully detect seismic waves and transmit warnings.

1. EARTHQUAKE EARLY
WARNING SYSTEM
USING
WIRELESS SENSOR
NETWORKS
BY
L N S Sravani

2. INTRODUCTION
▪ Earthquake is commonly said to be a natural disaster which is also known as tremor .
▪ The sudden shake in the surface of the earth, which shutters down the buildings and
kills thousands of human lives.
▪ Thereby by predicting the surfaces shake earlier by means of sensors that may warn
public earlier.
▪ By the theory that the S waves are the first attack wave from the surface and then the
P waves attack the surface latter that brings the strongest shake then the S wave.
▪ Hence the public is warned earlier in few minutes or seconds before.
▪ The IOT is the network it connects the internet connected objects to form a network
and hence the alert message is send to the public is more accurate way by IOT.

3. ABSTRACT
▪ The Wireless sensor network (WSN) is spatially distributed sensors in an
autonomous manner to monitor physical environmental conditions. The Internet of
things (IOT) is the network of computed physical objects which enables these things
to connect, collect and exchange data. In this paper, we propose an earthquake early
warning system by means of an IOT in WSN. The sensors are placed in the surface
of the earth. When an earthquake occurs, both compression P wave and transverse S
wave radiates outward the epicenter of the earth. The P wave, which travels fastest,
trips the sensors, placed in the landscape. It causes early alert signals to be transfer
ahead, giving humans and automated electronic system a warning to take
precautionary actions. So that before the damage begins with the arrival of the slower
but stronger S waves, the public are warned earlier. The signal from each sensor
which senses the P wave and which has Zigbee transmitter transfers the alert signal
to the gateway. The gateway which has the Zigbee receiver and acts as an IOT
transfers the warning to smart phones. Thus early alert message is received by the
people in terms of location, time and other parameters. Eventually, many of the
human lives can be saved. The software used here is LABVIEW where the three
angle axis of the sensor can be sensed and detected when the sensors are interfaced
with this software.

4. BLOCK DIAGRAM

5. EXISTING SYSTEM
Earthquake early warning (EEW) systems use earthquake science and
the technology of monitoring systems to alert devices and people when
shaking waves generated by an earthquake are expected to arrive at
their location. The seconds to minutes of advance warning can allow
people and systems to take actions to protect life and property from
destructive shaking.

6. PROPOSED SYSTEM
In the proposed system we have the modules of Zigbee for remote
correspondence and three sensors for information retrieval. The
sensors utilized are Force Sensor, Vibration Sensor and Flex Sensor.
There will be warning system at the remote place which will be
activated when the sensor values cross threshold value

7. HARDWARE COMPONENTS
▪ Ardunio
▪ Node MCU
▪ Flex sensor
▪ Vibration sensor
▪ Force Sensor
▪ Xbee

8. SOFTWARE COMPONENTS
▪ Embadded C
▪ Ardunio IDE
▪ HTML
▪ XCTU

9. ARDUINO UNO
▪ MICRO CONTROLLER with 14 digital pins.
▪ Micro controller-Atmega328
▪ Digital i/o pins 14.
▪ Analog input pins 6.
▪ 16mgh ceramic resonator.
▪ USB connection,powerjack,ICSP header and a reset
button.

10. FLUX SENSOR
Flux sensor which is 2.2 inches in length. This sensor works by
bending the sensor itself.
As the sensor is being flexed or bent, the resistance across the sensor
increases. The greater the angle of bending, the greater the resistance.
This can be tested with multimeter. The resistance of the flex sensor
changes when the metal pads are on the outside of the bend.

11. FORCE SENSOR
▪ This is a force sensitive resistor with a square, 1.75x1.5", sensing area.
▪ This FSR will vary its resistance depending on how much pressure is
being applied to the sensing area. The harder the force, the lower the
resistance.
▪ When no pressure is being applied to the FSR its resistance will be
larger than 1MΩ.
▪ This FSR can sense applied force anywhere in the range of 100g-10kg.

12. VIBRATION SENSOR
▪ This basic Vibration sensor can be used in anti-theft devices, electronic
locks, mechanical equipment vibration detection, sound gesture
application and counts vibration sensor occasions.
▪ These vibration levels could be given to any controller/processor and
necessary decisions could be taken through it.
▪ Module triple output mode, digital output simple, analog output more
accurate, serial output with exact readings.
▪ Resistance Decreases when Vibration Increases near the Sensor places

13. XBEE
▪ XBees are hugely popular wireless transceivers for a number of
reasons.
▪ They’re flexible they send and receive data over a serial port, which
means they’re compatible with both computers and microcontrollers
(like Arduino).
▪ They are highly configurable you can have meshed networks with
dozens of XBees, or just a pair swapping data.
▪ You can use them to remotely control your robot, or arrange them all
over your house to monitor temperatures or lighting conditions in
every room.

14. NODE MCU
▪ NodeMCU is a Micro controller and an open source IoT platform. It
includes firmware which runs on the ESP8266 WiFi SoC from
Espressif, and hardware which is based on the ESP-12 module.
▪ The ESP8266 module is a IoT device consisting of a 32-bit ARM
microprocessor with support of WIFI network and built-in flash
memory.
▪ This architecture allows it to be programmed independently, without
the need of other microcontrollers like the Arduino.

15. BREAD BOARD
▪ 63 vertical columns on top and 63 columns below.
▪ Each column has 5 connected holes.
▪ There are also 4 rails for power and ground running horizontally.

16. DESIGN
1. CLASS DIAGRAM
2. USECASE DIAGRAM
3. SEQUENCE DIAGRAM
4. STATE CHART

17. CLASS DIAGRAM

18. USECASE DIAGRAM

19. SEQUENCE DIAGRAM

20. STATECHART DIAGRAM

21. IMPLEMENTATION
}
void loop() {
Flux = analogRead(A0);
Vibration = analogRead(A3);
Force = analogRead(A2);
delay(1000);
String payloadStr = buildJSON();
publishZWaveTx(payloadStr);
Serial.println(payloadStr);
}
}String buildJSON() {
String payloadStr;
payloadStr = "{";
payloadStr += ""Flux":"" +String
(Flux,DEC)+ "",";
payloadStr += ""Vibration":""
+String (Vibration,DEC)+ "",";
payloadStr += ""Force":"" +String
(Force,DEC)+ """; payloadStr += "}";
return (payloadStr);
}

22. OUTPUTS
,

23. NODE MCU CODE
}We now create a URI for the request
String url = "/update";
url += "?api_key=";
url += privateKey;
url += "&field1=";
url += Flux;
url += "&field2=";
url += Vibration;
url += "&field3=";
url += Force;
Serial.print("Requesting URL: ");
Serial.println(url);
client.print(String("GET ") + url + "
HTTP/1.1rn" +
"Host: " + host + "rn" +
"Connection: closernrn");
delay(10);
while(client.available()){
String line = client.readStringUntil('r');
Serial.print(line);
}

24. OUTPUT

25. GRAPHS

26. Alert Message Through Phone

27. Alert Message Through Email

28. CONCLUSION
By use of Wireless Sensor Network any mechanical or geo-physical sensor
can be interfaced easily for protection of our on livelihood as well as nation’s
wealth. This paper discussed a proto-model of NODE design for ‘Earthquake
Early Warning’ which of great importance especially in heavy rainfall and
hilly areas. The WSN deployment leads to access many of the sensor
information and by using Ethernet, Wi-Fi, Satellite or any other wireless
protocol the danger intimation can be passed to the nearby villages and to the
government officials.

29. FUTURE SCOPE
▪ Ongoing improvements to the sensor networks and data processing centers
allowed the ShakeAlert system to advance from a “demonstration” to a
“production prototype” phase in February 2016, allowing selected users to
develop pilot implementations that take protective actions.
▪ USGS has published an implementation plan spelling out the steps needed to
complete the system and begin issuing public alerts (Given and others, 2014).
Public alerts and large-scale automatic implementation require additional
development and further testing to make ShakeAlert sufficiently reliable (see
sidebar “How Warning Can Increase Safety and Prevent Damage”), as well
as end-user education on how to understand and use alerts.
▪ The successful completion of the system will require the coordinated

30. REFERENCES
▪ Allen, R., 2013, Seismic hazards; seconds count: Nature, v. 502, no. 7469,
accessed 2014 at http://www.nature.com/news/seismic-hazards-seconds-
count-1.13838.
▪ Federal Emergency Management Agency, 2008, FEMA 366; HAZUS-MH
estimated annualized earthquake losses for the United States: Federal
Emergency Management Agency, accessed 2014 at
https://www.fema.gov/media-library/assets/documents/13293?id=3265.
▪ Fujinawa, Y., and Noda, Y., 2013, Japan’s earthquake early warning system
on 11 March 2011—Performance, shortcomings, and changes: Earthquake
Spectra, v. 29, no. S1, p. S341–S368, http://dx.doi.org/10.1193/1.4000127.

31. THANK YOU