##plugins.themes.academic_pro.article.main##

Abstract

The greatest threat to national security is “Terrorism†infiltrating through borders. In critical border areas such as Kashmir and Bangladesh regular forces or even satellites cannot monitor these intruding terrorists as the area monitored is quite large and quite complex. This project provides an innovative and effective solution to this problem.

The project aim is to design a next generation intelligent ultra small dust like wireless sensor motes which has multiple onboard sensors, camera and a processor, which has the ability to detect an enemy intrusion across borders and battlefields. Thousands of these smart dust motes can be deployed within a large area in a few hours by one or two men. The motes can form a network on its own among them, are small in size, rapidly deployable, have wireless connection to outside world. They detect the intrusion and classify it into vehicles or individuals and groups. Onboard hardware include a variety of sensors for vibration/seismic, magnetic, acoustic, thermal signature recognition and camera, a microcontroller for processing these sensor values and a ZigBee  transceiver for communication over a wireless network. The system process the sensor readings, classify the targets and the tracking history can be viewed in the Graphics LCD display attached in the central monitoring unit. The central monitoring node acts as the parent node in a peer to peer wireless network model. The dust motes communicate with central parent node using wireless ZigBee network

Keywords: MEMS accelerometer, Inter Integrated Circuit (I2C), Cortex microcontroller software interface standard (CMSIS), Advanced RISC Machine (ARM), Serial Peripheral Interface (SPI),Smartdust mote.

##plugins.themes.academic_pro.article.details##

Author Biography

Njilo Jemu, Saravana, Bharath University, Chennai

1M. Tech Student, Department of E & TC

2Asistant Professor, Department of E & TC

How to Cite
Saravana, N. J. (2014). A Smart dust network system for monitoring Enemy’s Intrusion using Camera-Acoustic-Magnetic-Thermal- Vibration Signatures. International Journal of Emerging Trends in Science and Technology, 1(09). Retrieved from https://igmpublication.org/ijetst.in/index.php/ijetst/article/view/399

References

1. Jisha R C, Maneesha V. Ramesh, Lekshmi G S, “Intruder Tracking using Wireless Sensor Network,” Computational Intelligence and Computing Research.(ICCIC), 2010 IEEE International Conference on .
2. Akyildiz, I., W. Su, Y. Sankarasubramaniam, and E.Cayirci, “A survey on sensor networks,” IEEE Communications Magazine, 40(8), 102-114, August.
3. Kondaveeti, A., Runger, G., Rowe, J., Huan Liu, “Border Security: Supplementing Human Intelligence in a Sensor Network Using Sequential Pattern Mining,” International Conference on Digital Object Identifier.
4. Emad H. Aboelela, Altaf H Khan, “Wireless Sensors and Neural Networks for Intruders Detection and Classification,” Information Networking, International Conference on Digital Object Identifier.
5. Ashish Mishra, Komal Sudan, Hamdy Soliman. “Detecting Border Intrusion Using Wireless Sensor Network and Artificial Neural Network,” International Conference on Digital Object Identifier.
6. Doug Steel, Smartdust, UH ISRC Technology briefing, March 2005.
7. Pratap.P, Kallberg J.M, Thomas L.A, Challenges of remote border monitoring, 2010 IEEE International Conference on Technologies for Homeland Security (HST)
8. Nohara, T.J;A commercial approach to successful persistent radar surveillance of sea, air and land along the northern Border, 2010 IEEE International Conference on Technologies for Homeland Security (HST)
9. Neumann, C.; Weiss, G.; Wahlen, A.; Brehm, T:Ground Surveillance With Mmw Radar For Border Control And Camp Protection Applications, European Microwave Conference, 2007.
10. Pratap, P.; Kallberg, J.M.; Thomas, L.A ;Challenges Of Remote Border Monitoring, 2010 IEEE International Conference on Technologies for Homeland Security (HST)
11. Girard, A.R.; Howell, A.S.; Hedrick, J.K;Border Patrol And Surveillance Missions Using Multiple Unmanned Air Vehicles, 2004. CDC. 43rd IEEE Conference on Decision and Control
12. Owen, Arch; Duckworth, Gregory; Worsley, Jerry, Optasense: Fibre Optic Distributed Acoustic Sensing For Border Monitoring, 2012 EuropeanIntelligence and Security Informatics Conference (EISIC)
13. Shyam Sadasivan, An introduction to the ARM Cortex-M3 Processor, October 2006, Open journal
14. Cortex-M3 Technical reference manual from ARM, 2010, http://www.arm.com
15. NXP Semiconductors, KMA199E, Programmable sensor, Rev.01-18, October 2007, http://www.nxp.com
16. Knowles Acoustics, SPM0404HESH-PB specification, 2009
17. SB0081, Product manual
18. Phidgets, 1104_0_product_manual_ September 30, 2009
19. IEEE, MRF24J40, http://www.microchip. com
20. PCD85441,ProductSpecification, 1999,http://www.semiconductors.phillips.com