Multi-Sensor Embedded System for Security
Volumn 4

Multi-Sensor Embedded System for Security

Prof. R. S. Adnak#1, Prof. A. S. Kulkarni#2

1Department of Electronics and Telecommunication Engineering, MBES COE, Ambajogai, India.

2Department of Electronics and Telecommunication Engineering, MBES TBGP, Ambajogai,India.

1rohini_adnak@rediffmail.com

2ak232009@gmail.com

Abstract—

This paper is based on multi-sensor technology used for monitoring the parameters of fire process like flame, smoke, temperature for early fire detection. Air and Noise pollution is an important issue to deeply think about in current environmental situation which has major impact on human health.

Keywords— Multi-Sensor, Security System, GSM, WSN, zigbee.

I. INTRODUCTION

There is a rapid increase in use of vehicles in metropolitan cities, these days which produce Air pollution and noise pollution which affect the human health. Considering the sensitivity of fire accidents, the Bureau has also collected data on fire accidents according to places of occurrence. A total of 20,500 cases of fire accidents were reported in the country during 2015, which caused 2000 persons injured and 19,800 deaths. The cause-wise analysis of fire accidents revealed that 20% of 20,500 fire accidents were reported in residential/dwelling buildings. The aim of this paper is to protect people and property by generating an alarm earlier by sensing the environmental conditions.  By using a multi-sensor to monitor the parameters of the fire process, such

as Flame, smoke, temperature, the range of fire monitoring in time is expanded compared with a single-sensor system [1].

A. Effect of Air pollution on human health

Due to expansion of industrial area and increase in use of vehicles, air pollution continuously grows affecting human health. Heavy pollution due to above reasons causes many diseases like hyperventilation, vision damage, lung congestion, central nervous system injury, abrupt muscle contractions, elevated blood pressure, and shortness of breath. Exposure can also cause dizziness, headache, sweating, fatigue, numbness and tingling of extremities, memory loss, nausea, vomiting, depression, confusion, skin and eye burns, and ringing in the ears [3,4]. 

B. Effect of Noise Pollution on Human Health

The level of noise increases due to departure of aircrafts, use of heavy machines at construction sites, industries. Different vehicles like trucks, road rollers, railways also produce loud noise can put people at risk for noise-induced hearing loss. Sounds that are louder than 85 dB can cause permanent hearing loss. The hearing system can be injured not only by a loud blast or explosion but also by prolonged exposure to high noise levels. When a sudden, extremely loud sound, such as an explosion, a gunshot, or a firecracker close to the ear, damages any of the structures in the ear and produces an immediate, permanent hearing loss. This type of injury often requires immediate medical attention.

 Loud noise can also cause other physical problems, such as:

  • High blood pressure
  • Increased or abnormal heart rate
  • Upset stomach
  • Insomnia or difficulty sleeping (even after the noise stops)
  • Hardware Design

II. HARDWARE DESIGN

The main aim of this paper is to protect people and property by generating an alarm earlier by sensing the environmental conditions. In this paper, we have presented one master node which consists of arm7 microcontroller, GSM module and Zigbee module. The slave node is designed using ARM microcontroller, Zigbee module with different sensors. Slave node collects the information about different environmental parameters such as air pollution, Noise pollution and parameters of fire process.

Fig. 1  Master Node
Fig. 1  slave  Node

Master node consist of ARM7 micro-controller, GSM module, Zigbee module, Buzzer and serial port to USB converter. Master node monitor and collect the information from slave nodes. Zigbee module is used for short distance communication between master and slave nodes and GSM is used for long distance communication to transmit the alert message on owner’s mobile phone.

Slave node consists of ARM microcontroller, multi-sensors such as smoke detector, flame detector and temperature detector for detection of fire parameters. Noise detector and Air pollution detector are used to sense loud noise level and air pollution. When Air pollution detector exceeds threshold value DC motor will be turn ON to open the windows and air purifier will be turn ON. When environmental noise exceeds its threshold value it is detected by noise detector ARM transmit signal to master node. When master node receive signal, it send ‘High Noise’ alert message on mobile phone via GSM. Also master node is connected to PC where we can monitor the level of the Noise and Air pollution continuously and stored database on PC. When multi-sensor detectors used for monitoring the parameters of fire process like flame, smoke, temperature exceeds threshold value ARM transmit signal to master node. When master node receive signal, it send ‘Fire Detected’ alert message on mobile phone via GSM and an alarm is generated by master node.

III. METHODOLOGY

A. Air pollution detector

Fig. 3 Air pollution detector MQ 135

The MQ-135 gas sensor senses the gases like ammonia nitrogen, oxygen, alcohols, aromatic compounds, sulphide and smoke. The boost converter of the chip MQ-3 gas sensor is PT1301. The operating voltage of this gas sensor is from 2.5V to 5.0V. The MQ-3 gas sensor has a lower conductivity to clean the air as a gas sensing material. In the atmosphere we can find polluting gases, but the conductivity of gas sensor increases as the concentration of polluting gas increases. MQ-135 gas sensor can be implementation to detect the smoke, benzene, steam and other harmful gases. It has potential to detect different harmful gases.

B. Noise detector

Fig. 4 Noise detector

This is an updated version of the Analog Noise Sensor. Analog Noise Sensor is typically used in detecting the loudness in ambient, the Arduino can collect its output signal and actuate accordingly. This sensor works best with our Noise analyser module. 

C. Flame  detector

2262-large_default
Fig. 5 Flame detector

A flame wavelength between 760 nm to 1100 nm infrared is most sensitive. Module has two outputs:1, AO, analog output, real-time output voltage signal on the thermal resistance2, DO, when the temperature reaches a certain threshold, the output high and low signal threshold adjustable via potentiometer Power supply: DC 3-5.5VAnalog output.

D. Smoke  detector

Image result for mq7 sensor
Fig. 6 Smoke detector

The MQ-2 smoke sensor is sensitive to smoke.  Sensitive material of MQ-2 gas sensor is SnO2, which with lower conductivity in clean air. When the target combustible gas exist, the sensor’s conductivity is higher along with the gas concentration rising.

E. Temperature  detector

 The LM35 is one kind of commonly used temperature sensor that can be used to measure temperature with an electrical o/p comparative to the temperature (in °C). It can measure temperature more correctly compare with a thermistor. This sensor generates a high output voltage than thermocouples and may not need that the output voltage is amplified. The LM35 has an output voltage that is proportional to the Celsius temperature. The scale factor is .01V/°C [2].

LM35 Temperature Sensor
Fig. 7 Temperature detector

The LM35 does not need any exterior calibration and maintains an exactness of +/-0.4°C at room temperature and +/-0.8°C over a range of 0°C to +100°C.One more significant characteristic of this sensor is that it draws just 60 micro amps from its supply and acquires a low self-heating capacity. The LM35 temperature sensor available in many different packages like T0-46 metal can transistor-like package, TO-92 plastic transistor-like package, 8-lead surface mount SO-8 small outline package [.

IV RESULTS

The mobile number of the user should be included in the software programming in order to receive the message of exceeded values of different parameters from the GSM modem. The snapshot indicates the message alerts of Fire detection, High noise detection.

Fig. 8 Snapshot of Fire, detection message

We can store database of Noise and Air pollution on PC. So we can analyse toxic gas concentration in air and loudness level of noise for each and every second. Below graph show the result of Air pollution and loudness level of noise variation in one day.

Fig. 9 Graph of one day variation of  Air and Noise Pollution.

V. CONCLUSION

This paper suggests designing of embedded controlled sensor networks used for controlling the home devices as well as monitoring the environmental parameters. The features of GSM and Zigbee are used to design the system for long distance as well as short distance communication

Embedded controlled sensor networks have proven themselves to be a reliable solution in providing remote control and sensing for indoor environmental monitoring systems. Different detectors had been integrated with the system to monitor and compute the level of existence of toxic gases, Noise and Air pollution in atmosphere using information and communication technologies. Flame, Smoke and Temperature detector avoid false alarm and indicate early existence of fire.

REFERENCES

  1. S. Zeng, Y.; Sreenan, C.J.; Sitanayah, L.; Xiong, N.; Park, J.H.; Zheng,   G. An emergency-adaptive routing scheme for wireless sensor networks for  building fire hazard monitoring. Sensors 2011.
  2. “Environment Monitoring and device control using arm based  Embedded  Controlled Sensor network” by Rakesh sherla and S.Kalyan.                                                                                                                                                                                                     
  3. Bus Management System Using RFID in WSN” by Ben Ammar Hatem and Hamam Habib (2009)
  4. “Intelligent Traffic Management System Base on WSN and RFID” by Lejiang Guo, Wei Fang, Guoshi Wang and Longsheng Zheng (2010).
  5. “Environment Monitoring and Device Control using ARM based Embedded Controlled Sensor Network” by Suneha D. Pawar1, Prof. U.A. Rane2.
  6. “ZigBee Based Environment monitoring and Controlling the Gas Plant using ARM “ by Mrs. Aparna V. Pethkar1 Prof. Savita A. Pawar2 .
  7. “Design Of Arm Based Embedded Controlled Sensor Network For Automatic Environment Monitoring And Device Control” by Ojja Mallikarjun1, G.Sai Kumar2.
  8. “Design And Implementation Of Arm Intelligent Monitoring System Using Zigbee” by P.Naresh Kumar, Dr. N.S Murthy Sharma, Mr. M.S.Madhan Mohan , Mr. Dhana Raj.
  9. “Implementation of Environment Monitoring and Device Control using ARM Based Embedded Control Sensor Network” by Mohd Imran1, Hilal Ahmad Malik2. [10] “Device Control Approach For Environment Monitoring Using Wireless Sensor Network “ by Pravin Dattatray Auti, ME, Prof.R.B.Sonawane, ME,
  10. “Device Control Approach For Environment Monitoring Using Wireless Sensor Network “ by Pravin Dattatray Auti, ME, Prof.R.B.Sonawane, ME,

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