(45-3) 08 * << * >> * Russian * English * Content * All Issues

Application of a wireless sensor system for object protection using infrared sensors
V.I. Parfenov 1,2, V.D. Le 1

Voronezh State University,
394006, Russia, Voronezh, Universitetskaya pl. 1,
Voronezh Institute of the Ministry of Home Affairs of Russia,
394065, Russia, Voronezh, prospect Patriotov, 53

 PDF, 1028 kB

DOI: 10.18287/2412-6179-CO-788

Pages: 364-371.

Full text of article: Russian language.

Abstract:
In this work, an algorithm that makes decisions on whether or not an object under protection has been penetrated based on data from infrared (IR) sensors included in a wireless sensor system is considered. Based on theoretical considerations, methods for calculating the attenuation of infrared radiation by the medium, including attenuation due to molecular gases and aerosol attenuation, are presented. Peculiarities of the external environment impact on the functioning of local heat sensors are shown. Also, peculiarities of the noise immunity characteristics of a radio communication channel are considered with due regard for signal fading. With the purpose of analyzing the environment impact on the efficiency of the entire system, we present dependencies of the total error probability on the energy parameter, taking into account the attenuation of infrared radiation in both the environment at the level of local sensors and the radio communication channel. In addition, a dependence of the total error probability on the communication distance under the influence of fading is presented. The results arrived at are analyzed and the degree of influence of the environment on the quality of functioning of the wireless sensor system of thermal type is evaluated. It is shown that adverse weather conditions can have a significant impact on the efficiency of local sensors, and, hence the entire system. However, despite the possible significant deterioration in efficiency due to the IR signal attenuation in the medium and in the radio channel, the efficiency can be increased by increasing the number of sensors used.

Keywords:
wireless sensor networks (WSN), sensor, error probability, absorption, signal fading, infrared radiation, aerosols, atmospheric transmittance.

Citation:
Parfenov VI, Le VD. Application of a wireless sensor system for object protection using infrared sensors. Computer Optics 2021; 45(3): 364-371. DOI: 10.18287/2412-6179-CO-788.

References:

  1. Urmanov DM, Boldova OI. Wireless sensor systems for security of moving and stationary objects [In Russian]. Electronics: Science, Technology, Business 2013; 3(125): 128-134.
  2. Sohraby K, Minoli D, Znati T. Wireless sensor networks: technology, protocols, and application. Hoboken, New Jersey: John Wiley & Sons Inc; 2007. ISBN: 978-0-471-74300-2.
  3. Belousov YI, Postnikov ES. Infrared Photonics. Part I. Features of formation and propagation of infrared radiation [In Russian]. Saint-Petersburg: ‎ITMO University Publisher; 2019.
  4. Smirnov BM. Infrared radiation in the energy of the atmosphere. High temperature 2019; 57(4): 573-595. DOI: 10.1134/S0018151X19040199.
  5. Kriksunov LZ, ed. Reference book to the basics of infrared technology [In Russian]. Moscow: “Soviet Radio” Publisher; 1978.
  6. Alekhin, SG, Gotyur IA, Semenov VV. Method of the calculating atmospheric transparency coefficient for thermal imaging systems in the spectral range 8-12 μm [In Russian]. Proceedings of the Military Space Academy Named after AF Mozhaisky 2019; 668: 117-128.
  7. Timofeev YM, Vasiliev AV. Theoretical fundamentals of atmospheric optics [In Russian]. Saint-Petersburg: “Nauka” Publisher; 2003.
  8. Dikrin DE. Networks and telecommunications systems: a course of lectures [In Russian]. Kazan: Kazan University Publisher; 2013.
  9. Sidelnikov GM, Makarov АА. Statistical theory of radio engineering systems [In Russian]. Novosibirsk: Siberian State University of Telecommunications and Informatics Publisher; 2015.
  10. Parfenov VI, Le VD. Algorithms of information aggregation in wireless sensor networks taking into account probability of sensors failure [In Russian]. Radioengineering 2019; 12(19): 53-59. DOI: 10.18127/j00338486-201912(19)-06.
  11. Parfenov VI, Le VD. The optimal algorithm of aggregation of information in wireless sensor networks taking into account the influence of interference in the radio channel [In Russian]. Telecommunications 2020; 2: 12-17.
  12. Sriranga N, Nagananda G, Blum RS, Saucan A, Varshney PK. Energy-efficient decision fusion for distributed detection in wireless sensor networks. Proceeding IEEE International Conference on Information Fusion (FUSION) 2018: 1541-1547. DOI: 10.23919/ICIF.2018.8454976.
  13. Spectroscopy of atmospheric gases [In Russian]. Source: <http://spectra.iao.ru/home.overview>.
  14. Mikhailenko SN, Babikov YuL, Golovko VF. Information-calculating system Spectroscopy of Atmospheric Gases. The structure and main functions. Atmos Oceanic Opt 2005; 18(09): 685-695.
  15. Clough SA, Shephard MW, Mlawer EJ, Delamere JS, Iacono MJ, Cady-Pereira K, Boukabara S, Brown PD. Atmospheric radiative transfer modeling: a summary of the AER codes. J Quant Spectrosc Radiat Transf 2005; 91(2): 233-244. DOI: 10.1016/j.jqsrt.2004.05.058.
  16. Mlawer EJ, Payne VH, Moncet J-L, Delamere JS, Alvarado MJ, Tobin DD. Development and recent evaluation of the MT_CKD model of continuum absorption. Philos Trans A Math Phys Eng Sci 2012: 370(1968): 2520-2556. DOI: 10.1098/rsta.2011.0295.
  17. Vladimirov VM, Yukseev VA, Lapukhin EG. An optical system for remote sensing in the UV, visible, and NIR spectral ranges. Computer Optics 2020; 44(2): 195-202. DOI: 10.18287/2412-6179-CO-611.

© 2009, IPSI RAS
151, Molodogvardeiskaya str., Samara, 443001, Russia; E-mail: ko@smr.ru ; Tel: +7 (846) 242-41-24 (Executive secretary), +7 (846) 332-56-22 (Issuing editor), Fax: +7 (846) 332-56-20