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Article

Biosensors: A Modern Day Achievement

1Department of Biotechnology, Sapthagiri College of Engineering, Bangalore, Karnataka, India


Journal of Instrumentation Technology. 2014, 2(1), 26-39
DOI: 10.12691/jit-2-1-5
Copyright © 2014 Science and Education Publishing

Cite this paper:
Shruthi GS, Amitha CV, Blessy Baby Mathew. Biosensors: A Modern Day Achievement. Journal of Instrumentation Technology. 2014; 2(1):26-39. doi: 10.12691/jit-2-1-5.

Correspondence to: Blessy  Baby Mathew, Department of Biotechnology, Sapthagiri College of Engineering, Bangalore, Karnataka, India. Email: blessym21@gmail.com

Abstract

The term biosensor is often used to cover sensor devices used in order to determine the concentration of substances and other parameters of biological interest even where they do not utilize a biological system directly. This review discusses recent advances in biosensor technology which draw on the disciplines of physics, chemistry, biochemistry and electronics. This article states that a biosensor consists of three components, a biological detection system, a transducer and an output system. Biological receptors are briefly reviewed, followed by a detailed discussion of immobilization procedures for the efficacious attachment of receptor molecules to a transducer surface. Widely used in the fields of research and development in this field is wide and multidisciplinary, spanning biochemistry, bioreactor science, physical chemistry, electrochemistry, electronics and software engineering.

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References

[[[[[[[[[[[[[[[[[[[[[[[[[[[
[[1]  Khandpur, R. S. Handbook of biomedical instrumentation. Tata McGraw-Hill Education, 1992, 15-75.
 
[[2]  Buerk, D. G. Biosensors: Theory and applications. Crc Press, 1995.
 
[[3]  Newman, J. D., & Setford, S. J. (2006). Enzymatic biosensors. Molecular biotechnology, 32 (3), 249-268.
 
[[4]  Koyun, A., Ahlatcıoğlu, E., & İpek, Y. K. Biosensors and Their Principles and Kahraman C. (2008). Fuzzy multi-criteria decision making: theory and applications with recent developments (Vol. 16) Springer.
 
[[5]  Eggins, B. R. (2008). Chemical sensors and biosensors (Vol. 28). John Wiley & Sons.
 
Show More References
[6]  Grieshaber, D., Mac Kenzie, R., Voeroes, J., & Reimhult, E. (2008). Electrochemical biosensors-Sensor principles and architectures. Sensors, 8 (3), 1400-1458.
 
[7]  Kumar, A. (2000). Biosensors based on piezoelectric crystal detectors: theory and application. JOM-e, 52 (10).
 
[8]  Martins, T. D., Ribeiro, A. C. C., de Camargo, H. S., da Costa Filho, P. A., Cavalcante, H. P. M., & Dias, D. L. (2013). New insights on optical biosensors: techniques, construction and application.
 
[9]  Strehlitz, B., Nikolaus, N., & Stoltenburg, R. (2008). Protein detection with aptamer biosensors. Sensors, 8 (7), 4296-4307.
 
[10]  Pohanka, M., & Skládal, P. (2008). Electrochemical biosensors–principles and applications. J Appl Biomed, 6 (2), 57-64.
 
[11]  da Costa Silva, L. M., Melo, A. F., & Salgado, A. M. Biosensors for Environmental Applications.
 
[12]  Allain, L. R., Stratis-Cullum, D. N., & Vo-Dinh, T. (2004). Investigation of microfabrication of biological sample arrays using piezoelectric and bubble-jet printing technologies. Analytica chimica acta, 518 (1), 77-85.
 
[13]  Newman, J. D., & Setford, S. J. (2006). Enzymatic biosensors. Molecular biotechnology, 32 (3), 249-268.
 
[14]  Blum, L. J., & Coulet, P. R. Biosensor principles and applications, 1991.
 
[15]  Yoo, Eun-Hyung, and Soo-Youn Lee. "Glucose biosensors: an overview of use in clinical practice." Sensors 10.5 (2010): 4558-4576.
 
[16]  Croce RA, Jr, Vaddiraju S, Papadimitrakopoulos F, Jain FC. Theoretical Analysis of the Performance of Glucose Sensors with Layer-by-Layer Assembled Outer Membranes. Sensors. 2012; 12 (10): 13402-13416.
 
[17]  Parth Malik, Varun Katyal, Vibhuti Malik, Archana Asatkar, Gajendra Inwati, and Tapan K. Mukherjee, “Nanobiosensors: Concepts and Variations,” ISRN Nanomaterials, vol. 2013, Article ID 327435, 9 pages, 2013.
 
[18]  Rai, Mahendra, Gade, Aniket, Gaikwad, Swapnil, Marcato, Priscyla D., & Durán, Nelson. (2012). Biomedical applications of nanobiosensors: the state-of-the-art. Journal of the Brazilian Chemical Society, 23 (1), 14-24.
 
[19]  http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-50532012000100004&lng=en&tlng=en.10.1590/S0103-50532012000100004 (Retrieved on December 03, 2014).
 
[20]  Yoo, E. H., & Lee, S. Y. (2010). Glucose biosensors: an overview of use in clinical practice. Sensors, 10 (5), 4558-4576.
 
[21]  Shtenberga, G., & Segalb, E. (2014). Porous Silicon Optical Biosensors.
 
[22]  Chambers, J. P., Arulanandam, B. P., Matta, L. L., Weis, A., & Valdes, J. J. (2008). Biosensor recognition elements. TEXAS UNIV AT SAN ANTONIO DEPT OF BIOLOGY.
 
[23]  Kawai, T., & Akira, S. (2010). The role of pattern-recognition receptors in innate immunity: update on Toll-like receptors. Nature immunology, 11 (5), 373-384.
 
[24]  Zhang, X., Ju, H., & Wang, J. (Eds.). (2011). Electrochemical sensors, biosensors and their biomedical applications. Academic Press.
 
[25]  Valgimigli, F., Mastrantonio, F., & Lucarelli, F. (2014). Blood Glucose Monitoring Systems. In Security and Privacy for Implantable Medical Devices (pp. 15-82). Springer New York.
 
[26]  Heise, H. M., Marbach, R., Koschinsky, T., & Gries, F. A. (1994). Multicomponent assay for blood substrates in human plasma by mid-infrared spectroscopy and its evaluation for clinical analysis. Applied Spectroscopy, 48 (1), 85-95.
 
[27]  Park, S., Boo, H., & Chung, T. D. (2006). Electrochemical non-enzymatic glucose sensors. Analytica Chimica Acta, 556 (1), 46-57.
 
[28]  Vasylieva, N. (2013). Implantable microelectrode biosensors for neurochemical monitoring of brain functioning (Doctoral dissertation, ETH Zurich).
 
[29]  Henry, C. (1998). Getting under the skin: implantable glucose sensors. Analytical chemistry, 70 (17), 594A-598A.
 
[30]  Abad, J. M., Vélez, M., Santamaría, C., Guisán, J. M., Matheus, P. R., Vázquez, L., Fernández, V. M. (2002). Immobilization of peroxidase glycoprotein on gold electrodes modified with mixed epoxy-boronic acid monolayers. Journal of the American Chemical Society, 124 (43), 12845-12853.
 
[31]  Huang, S. (2011). Glucose Biosensor Using Electrospun Mn2O3-Ag Nanofibers.
 
[32]  Toghill, K. E., Compton, R. G. (2010). Electrochemical non-enzymatic glucose sensors: a perspective and an evaluation. Int. J. Electrochem. Sci, 5 (9), 1246-1301.
 
Show Less References

Article

High-speed OH-PLIF Measurements for the Fundamental Study of Premixed Combustion and Flame

1School of Mechanical and Power Engineering, Henan Polytechnic University, Jiaozuo, China


Journal of Instrumentation Technology. 2014, 2(1), 17-25
DOI: 10.12691/jit-2-1-4
Copyright © 2014 Science and Education Publishing

Cite this paper:
Junjie Chen, Xuhui Gao. High-speed OH-PLIF Measurements for the Fundamental Study of Premixed Combustion and Flame. Journal of Instrumentation Technology. 2014; 2(1):17-25. doi: 10.12691/jit-2-1-4.

Correspondence to: Junjie  Chen, School of Mechanical and Power Engineering, Henan Polytechnic University, Jiaozuo, China. Email: comcjj@163.com

Abstract

OH-PLIF measurements were conducted for investigating the fundamental study of premixed combustion and flame characteristics. High-speed OH-PLIF measurements in premixed combustion and flame fields to image flow and composition fields in flames are quickly evolving and measurements of velocity and reactive species were recently reported in various flow configurations. The purpose of this paper is to discuss the most recent and significant advancement of technology in high-speed OH-PLIF measurements for the fundamental study of premixed combustion and flame. The highlight of this review will be focusing on explaining the concept of OH-PLIF process, its current related research, influences of process parameters, advantages and challenges pertaining to the fundamental study of combustion and flame. The results show that gas-phase combustion is significantly suppressed due to the depletion of the reactants rather than the radical adsorption. The vorticity is generated particularly close to the reaction zone where axial strain and dilatation exhibit local minima. The recommendations on future scientific studies are proposed for this novel process to move forward and to complement existing study of combustion and flame with a more sustainable approach.

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References

[[[[[[[[[[[[[[[[[[[[[[[
[[1]  J. Fu, C.L. Tang, W. Jin, Z.H. Huang, Effect of preferential diffusion and flame stretch on flame structure and laminar burning velocity of syngas Bunsen flame using OH-PLIF, Int. J. Hydrogen Energy, 39 (2014), pp. 12187-12193.
 
[[2]  J. Sjöholm, J. Rosell, B. Li, M. Richter, Z. Li, X.S. Bai, M. Aldén, Simultaneous visualization of OH, CH, CH2O and toluene PLIF in a methane jet flame with varying degrees of turbulence, Proc. Combust. Inst., 34 (2013), pp. 1475-1482.
 
[[3]  J. Fu, C. Tang, W. Jin, L.D. Thi, Z. Huang, Y. Zhang, Study on laminar flame speed and flame structure of syngas with varied compositions using OH-PLIF and spectrograph, Int. J. Hydrogen Energy, 38 (2013), pp. 1636-1643.
 
[[4]  A.N. Karpetis, R.S. Barlow, Measurements of flame orientation and scalar dissipation in turbulent partially premixed methane flames, Proc. Combust. Inst., 30 (2005), pp. 665-672.
 
[[5]  S.A. Kaiser, J.H. Frank, Spatial scales of extinction and dissipation in the near field of non-premixed turbulent jet flames, Proc. Combust. Inst., 32 (2009), pp. 1639-1646.
 
Show More References
[6]  H. Yang, Y. Feng, X. Wang, L. Jiang, D. Zhao, N. Hayashi, H. Yamashita, OH-PLIF investigation of wall effects on the flame quenching in a slit burner, Proc. Combust. Inst., 34 (2013), pp. 3379-3386.
 
[7]  Z.M. Nikolaou, N. Swaminathan, J.Y. Chen, Evaluation of a reduced mechanism for turbulent premixed combustion, Combust. Flame, 162 (2014), pp. 3085-3099.
 
[8]  M. Boileau, G. Staffelbach, B. Cuenot, T. Poinsot, C. Berat, LES of an ignition sequence in a gas turbine engine, Combust. Flame, 154 (2008), pp. 2-22.
 
[9]  A.M. Steinberg, J.F. Driscoll, Stretch-rate relationships for turbulent premixed combustion LES subgrid models measured using temporally resolved diagnostics, Combust. Flame, 157 (2010), pp. 1422-1435.
 
[10]  I. Boxx, C. Heeger, R. Gordon, B. Bohm, M. Aigner, A. Dreizler, W. Meier, Simultaneous three-component PIV/OH-PLIF measurements of a turbulent lifted, C3H8-Argon jet diffusion flame at 1.5 kHz repetition rate, Proc. Combust. Inst., 32 (2009), pp. 905-912.
 
[11]  J. Hult, U. Meier, W. Meier, A. Harvey, C.F. Kaminski, Experimental analysis of local flame extinction in a turbulent jet diffusion flame by high repetition 2-D laser techniques and multi-scalar measurements, Proc. Combust. Inst., 30 (2005), pp. 701-709.
 
[12]  C. Kittler, A. Dreizler, Cinematographic imaging of hydroxyl radicals in turbulent flames by planar laser-induced fluorescence up to 5 kHz repetition rate, Appl. Phys. B, 89 (2007), pp. 163-166.
 
[13]  B. Bohm, C. Heeger, I. Boxx, W. Meier, A. Dreizler, Time-resolved conditional flow field statistics in extinguishing turbulent opposed jet flames using simultaneous highspeed PIV/OH-PLIF, Proc. Combust. Inst., 32 (2009), pp. 1647-1654.
 
[14]  F. Alberini, M.J.H. Simmons, A. Ingram, E.H. Stitt, Assessment of different methods of analysis to characterise the mixing of shear-thinning fluids in a Kenics KM static mixer using PLIF, Chem. Eng. Sci., 112 (2014), pp. 152-169.
 
[15]  E. Mastorakos, Ignition of turbulent non-premixed flames, Prog. Energy Combust. Sci., 35 (2009), pp. 57-97.
 
[16]  H. Hesse, N. Chakraborty, E. Mastorakos, The effects of the Lewis number of the fuel on the displacement speed of edge flames in igniting turbulent mixing layers, Proc. Combust. Inst., 32 (2009), pp. 1399-1407.
 
[17]  Y. Saiki, Y. Suzuki, Effect of wall surface reaction on a methane-air premixed flame in narrow channels with different wall materials, Proc. Combust. Inst., 34 (2013), pp. 3395-3402.
 
[18]  P.J. Trunk, I. Boxx, C. Heeger, W. Meier, B. Böhm, A. Dreizler, Premixed flame propagation in turbulent flow by means of stereoscopic PIV and dual-plane OH-PLIF at sustained kHz repetition rates, Proc. Combust. Inst., 34 (2) (2013), pp. 3565-3572.
 
[19]  M. Tanahashi, S. Murakami, G.M. Choi, Y. Fukuchi, T. Miyauchi, Simultaneous CH-OH PLIF and stereoscopic PIV measurements of turbulent premixed flames, Proc. Combust. Inst., 30 (2005), pp. 1665-1672.
 
[20]  B. Böhm, D. Geyer, A. Dreizler, K.K. Venkatesan, N.M. Laurendeau, M.W. Renfro, Simultaneous PIV/PTV/OH PLIF imaging: Conditional flow field statistics in partially premixed turbulent opposed jet flames, Proc. Combust. Inst., 31 (2007), pp. 709-717.
 
[21]  M. Juddoo, A.R. Masri, High-speed OH-PLIF imaging of extinction and re-ignition in non-premixed flames with various levels of oxygenation, Combust. Flame, 158 (2011), pp. 902-914.
 
[22]  I. Boxx, C. Heeger, R. Gordon, B. Böhm, M. Aigner, A. Dreizler, W. Meier, Simultaneous three-component PIV/OH-PLIF measurements of a turbulent lifted, C3H8-Argon jet diffusion flame at 1.5 kHz repetition rate, Proc. Combust. Inst., 32 (2009), pp. 905-912.
 
[23]  C. Kittler, A. Dreizler, Cinematographic imaging of hydroxyl radicals in turbulent flames by planar laser-induced fluorescence up to 5 kHz repetition rate, Appl. Phys. B, 89 (2-3) (2007), pp. 163-166.
 
[24]  A. Upatnieks, J.F. Driscoll, C.C. Rasmussen, S.L. Ceccio, Liftoff of turbulent jet flames-assessment of edge flame and other concepts using cinema-PIV, Combust. Flame, 138 (2004), pp. 259-272.
 
[25]  C. Yu, J. Wang, Z. Wang, S. Shuai, Comparative study on gasoline homogeneous charge induced ignition (HCII) by diesel and gasoline/diesel blend fuels (GDBF) combustion, Fuel, 106 (2013), pp. 447-470.
 
[26]  G. Kalghatgi, R. Kumara Gurubaran, A. Davenport, A.J. Harrison, Y. Hardalupas, A.M.K.P. Taylor, Some advantages and challenges of running a Euro IV, V6 diesel engine on a gasoline fuel, Fuel, 108 (2013), pp. 197-207.
 
[27]  E. Knudsen, Shashank, H. Pitsch, Modeling partially premixed combustion behavior in multiphase LES, Combust. Flame, 162 (2014), pp. 159-180.
 
[28]  S. Kim, Y. Yan, J.M. Nouri, C. Arcoumanis, Effects of intake flow and coolant temperature on the spatial fuel distribution in a direct-injection gasoline engine by PLIF technique, Fuel, 106 (2013), pp. 737-748.
 
Show Less References

Article

The Design of Robust Soft Sensor Using ANFIS Network

1Department of Instrumentation and Automation engineering, Petroleum University of Technology, Ahvaz, Iran

2Department of Basic Sciences, Petroleum University of Technology, Ahvaz, Iran


Journal of Instrumentation Technology. 2014, 2(1), 9-16
DOI: 10.12691/jit-2-1-3
Copyright © 2014 Science and Education Publishing

Cite this paper:
Hamed Hosseini, Mehdi Shahbazian, Mohammad Ali Takassi. The Design of Robust Soft Sensor Using ANFIS Network. Journal of Instrumentation Technology. 2014; 2(1):9-16. doi: 10.12691/jit-2-1-3.

Correspondence to: Hamed  Hosseini, Department of Instrumentation and Automation engineering, Petroleum University of Technology, Ahvaz, Iran. Email: hamedehosseini@gmail.com

Abstract

A soft Sensor is a model which is used to estimate the unmeasurable output of an industrial process. Designing a soft sensor is usually difficult because its modeling is often based on case data. These data commonly contain the outliers and noise as soft sensor design is been problem. In order to solve the problem and successfully design a soft sensor, this paper introduces a new approach for designing a robust soft sensor which is not affected by outliers especially batch outlier and long tail noise. To response this goal, a robust soft sensor based on Adaptive Neuro-Fuzzy Inference System (ANFIS) which is based on robust cost function such as the summation of the absolute cost function. To minimize the cost function the particle swarm optimization (PSO) algorithm was used. The subtractive clustering technique was used to determine the ANFIS structure. The proposed method for designing a soft sensor is implemented on a chemical plant and compared with soft sensor based on ANFIS which is based on quadratic cost function. The simulation result shows higher accuracy in prediction of output variable in new robust soft sensor.

Keywords

References

[[[[[[[[
[[1]  R. Neelakantan. and J. Guiver., “Applying Neural Networks,” Hydrocarbon Processing, vol. 9, pp. 114-119, 1998.
 
[[2]  P. Kadlec., B. Gabrys., and S. Strandt., “Data-driven Soft Sensors in the process industry,” Computers and Chemical Engineering, vol. 33, pp. 795-814, 2009.
 
[[3]  G. D. Gonzalez., “Soft sensors for processing plants,” in Proceedings of the second international conference on intelligent processing and manufacturing of materials, IPMM99, 1999.
 
[[4]  L. Fortuna., S. Graziani., A. Rizzo., and M. G. Xibilia, “Soft Sensors for Monitoring and Control of Industrial Processes,” London: Springer-Verlag, 2007.
 
[[5]  A. Adamski. and S. Habdank-Wojewodzki., “Traffic congestion and incident detector realized by fuzzy discrete dynamic system,” Archives of Transport, vol. 17, pp. 5-13, 2004.
 
Show More References
[6]  W. B. Zhu., D. S. Li., and Y. Lu., “Real time speed measure while automobile braking on soft sensing technique,” Journal of Physics: Conference Series, vol. 48, pp. 730-733, 2006.
 
[7]  J. S. R. Jang., “ANFIS: Adaptive-network-based fuzzy inference systems,” IEEE Trans, Syst, Man Cybern, vol. 23, pp. 665-685, 1993.
 
[8]  S. Chiu., “Fuzzy Model Identification Based on Cluster Estimation,” Intelligent & Fuzzy Systems, vol. 2, 1994.
 
[9]  R. Kothandaraman. and L. Ponnusamy., “PSO tuned Adaptive Neuro-fuzzy Controller for Vehicle Suspension Systems,” Journal of Advances in Information Technology, vol. 3, pp. 57-63, Feb 2012.
 
[10]  K. Singh. and S. Upadhyaya., “Outlier Detection: Applications And Techniques” International Journal of Computer Science Issues, vol. 9, pp. 307-323, January 2012.
 
[11]  J. Kennedy. and R. Eberhart., “Particle Swarm Optimization,” Proceedings of IEEE International Conference on Neural Networks IV., pp. 1942-1948, 1995.
 
[12]  Y. Shi and R. Ebcrhart, “Paramctcr Sclcction in Panicle Swarm Optimization,” Proe. Scvcnth Annual Conf. on Evolutionary Programming, pp. 591-601, March 1998.
 
[13]  S. Kamelian., “Adaptive distributed control of industrial plants using stability-based nonlinear technique,” Ahwaz, 2012.
 
Show Less References

Article

The Modified Resonant Method for Measuring the Velocity Factor of the Electromagnetic Wave in the Microstrip Transmission Line

1Radio Engineering Department of the Engineering Physics and Radio Electronics Institute of the Siberian Federal University, Krasnoyarsk, Russia


Journal of Instrumentation Technology. 2014, 2(1), 5-8
DOI: 10.12691/jit-2-1-2
Copyright © 2014 Science and Education Publishing

Cite this paper:
Alexey Kopylov, Yuri Salomatov, Alexander Senchenko. The Modified Resonant Method for Measuring the Velocity Factor of the Electromagnetic Wave in the Microstrip Transmission Line. Journal of Instrumentation Technology. 2014; 2(1):5-8. doi: 10.12691/jit-2-1-2.

Correspondence to: Alexey  Kopylov, Radio Engineering Department of the Engineering Physics and Radio Electronics Institute of the Siberian Federal University, Krasnoyarsk, Russia. Email: kopaph@yandex.ru

Abstract

To measure the real value of velocity factor of the electromagnetic waves in the microwave microstrip transmission line was developed a modified resonant method and implements its measuring system. This system is using measuring the resonant frequency of a closed on the end one wave microstrip resonator. The method is designed to determine the velocity factor of the electromagnetic wave in the microstrip transmission line on substrates “policor” (95% Al2O3) for a small batch of microwave hybrid integrated circuits.

Keywords

References

[
[[1]  Jin, C., Chen, Z. “Compact Triple-Mode Filter Based on Quarter-Mode Substrate Integrated Waveguide”, IEEE Transactions on Microwave Theory and Techniques, 62 (1). 37-45. Jun. 2014.
 
[[2]  Chretiennot, T., Dubuc, D., Grenier, K. “A Microwave and Microfluidic Planar Resonator for Efficient and Accurate Complex Permittivity Characterization of Aqueous Solutions”, IEEE Transactions on Microwave Theory and Techniques, 61 (2). 972-978. Feb. 2013.
 
[[3]  Farzami, F., Norooziarab, M. “Experimental Realization of Tunable Transmission Lines Based on Single-Layer SIWs Loaded by Embedded SRRs”, IEEE Transactions on Microwave Theory and Techniques, 61 (8). 2848-2857. Aug. 2013.
 
[[4]  Kirshin, E., Oreshkin, B., Zhu, G.K., Popovic, M., Coates, M. “Microwave Radar and Microwave-Induced Thermoacoustics: Dual-Modality Approach for Breast Cancer Detection”, IEEE Transactions on Biomedical Ingineering, 61 (2). 354-360. Feb. 2013.
 
[[5]  Agilent. Solutions for Measuring Permittivity and Permeability with LCR Meters and Impedance Analyzers. Application Note 1369-1.
 
Show More References
[6]  Bernard, P. A., Gautray, J. M. “Measurement of Dielectric Constant Using a Microstrip Ring Resonator”, IEEE Transactions on Microwave Theory and Techniques, 32 (3). 974. March 1991.
 
Show Less References

Article

Study on a Hazardous Environment Monitoring and Control using Virtual Instrumentation

1Rerearch and Development Centre, Bharathiar University, Coimbatore, INDIA

2Department of Electronics and Instrumentation, Bharathiar University, Coimbatore, INDIA


Journal of Instrumentation Technology. 2014, 2(1), 1-4
DOI: 10.12691/jit-2-1-1
Copyright © 2014 Science and Education Publishing

Cite this paper:
Sureshkumar A, S. Muruganand. Study on a Hazardous Environment Monitoring and Control using Virtual Instrumentation. Journal of Instrumentation Technology. 2014; 2(1):1-4. doi: 10.12691/jit-2-1-1.

Correspondence to: Sureshkumar  A, Rerearch and Development Centre, Bharathiar University, Coimbatore, INDIA. Email: sureshkumarelex@gmail.com

Abstract

This paper proposes a hazardous environment monitoring and control for monitoring information concerning safety and security, utilizing Wireless Sensor Network (WSN) technology. The proposed hazardous environment monitoring and control collects industrial environmental safety and security information from both inside and outside industry environment through WSN-based sensors, collects image information through vision system, and collects location information through wireless radio modules. This collected information is converted into a database through the Virtual Environment Monitoring Server consisting of a sensor manager, image information manager and wireless radio manager. The sensor manager manages information collected from the WSN sensors, the image information manager manages image information collected from vision system and the wireless radio manager processes the location information of the hazardous environment. In addition, a power supply based on solar cell and battery back-up is implemented with the central control unit so that it could also be used in environments with insufficient power infrastructure. Immediately after the occurrence of accident, the Accident Data Recorder (ADR) automatically logs the wireless sensors and vision system data for the legal verification and judicial purpose. This data can be used as a First Information Report (FIR) for accident damage investigation and estimation. And it could be expected that the usage of such a system could contribute to increasing safety and security.

Keywords

References

[[[[[
[[1]  Gregory STAMATESCU1, Valentin SGÂRCIU2 Integration of wireless sensor networks with Virtual instrumentation in a residential Environment, U.P.B. Sci. Bull., Series C, Vol. 75, Iss. 2, 2013.
 
[[2]  Chandani Anand Wireless multi-sensor embedded system for Agro-industrial monitoring and control , , International Journal on Advances in Networks and Services, vol 3 no 1 & 2, Year 2010.
 
[[3]  Dr. Aditya Goel Remote Data Acquisition Using Wireless-SCADA System, International Journal of Engineering (IJE), Volume (3): Issue (1).
 
[[4]  Constantin Volosencu Monitoring of Distributed Parameter Systems Based on Virtual Instrumentation and Sensor Networks, Proceedings of the 2nd International Conference on Manufacturing Engineering, Quality and Production Systems.
 
[[5]  Clifford K. Ho Overview of Sensors and Needs for Environmental Monitoring, Sensors 2005, 5, 4-37.
 
Show More References
[6]  A. Balaji Ganesh Remote Monitoring of Multi Parameters Using an Embedded Digital Controller, Proceedings of the Mobile and Pervasive Computing (CoMPC-2008).
 
[7]  Jocob Fraden Handbook of Modern Sensors 3rd Edition Publication by Springer.
 
[8]  J. Wilson Sensor Technology Handbook Printed by Elsevier First Edition.
 
[9]  Amiya Nayak and Ivan Stojmenovic Wireless Sensor and Actuator Networks Edited, John Wiley & Sons, INC, Publication.
 
[10]  Arun Ganesh, M. AnandForest Fire Detection Using Optimized Solar Powered Zigbee Wireless Sensor Networks IJSER © 2013.
 
Show Less References
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