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Mohana H.S

Work place: Dept. of IT & EC Malnad College of Engineering, Hassan - 573201, India

E-mail: hsm@mcehassan.ac.in

Website:

Research Interests: Computational Engineering, Engineering

Biography

Professor Dr. H.S.Mohana is born in the year 1965. Obtained B.E Degree in Electical and Electronics Engineering from University of Mysore during 1986. Since then serving technical education field in various capacities. Obtained M.E from University of Roorkee presently IIT ROORKEE with the specialization in Measurement and Instrumentation. Obtained Ph.D. form VTU during 2010 in Computer & Information Science.   Worked as chairmen and Member of Board of Examiner and Board of studies with several universities which includes, University of Mysore, Kuvempu University  and VTU. Presented research findings in 12 National Conferences and in 4 International conferences held across the world. Recognized as AICTE expert committee member in the inspection and reporting continuation of affiliation and Increase in intake of the Engineering Colleges. Completed, one AICTE/MHRD-TAPTECH project, and one AICTE/MHRD- Research project successfully. Coordinated TWO ISTE Sponsored STTP for the technical college teachers. Presently working as Dean Academics in MCE Hassan, Karnataka, India.

Author Articles
Implementation of Computer Vision Based Industrial Fire Safety Automation by Using Neuro-Fuzzy Algorithms

By Manjunatha K.C. Mohana H.S P.A Vijaya

DOI: https://doi.org/10.5815/ijitcs.2015.04.02, Pub. Date: 8 Mar. 2015

A computer vision-based automated fire detection and suppression system for manufacturing industries is presented in this paper. Automated fire suppression system plays a very significant role in Onsite Emergency System (OES) as it can prevent accidents and losses to the industry. A rule based generic collective model for fire pixel classification is proposed for a single camera with multiple fire suppression chemical control valves. Neuro-Fuzzy algorithm is used to identify the exact location of fire pixels in the image frame. Again the fuzzy logic is proposed to identify the valve to be controlled based on the area of the fire and intensity values of the fire pixels. The fuzzy output is given to supervisory control and data acquisition (SCADA) system to generate suitable analog values for the control valve operation based on fire characteristics. Results with both fire identification and suppression systems have been presented. The proposed method achieves up to 99% of accuracy in fire detection and automated suppression.

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