http://www.iaeme.com/IJCIET/index.asp 1773 editor@iaeme.com International Journal of Civil Engineering and Technology (IJCIET) Volume 10, Issue 03, March 2019, pp. 1773-1781, Article ID: IJCIET_10_03_174 Available online at http://www.iaeme.com/ijciet/issues.asp?JType=IJCIET&VType=10&IType=03 ISSN Print: 0976-6308 and ISSN Online: 0976-6316 © IAEME Publication Scopus Indexed BIOMETRIC BASED ATTENDANCE MONITORING SYSTEM USING QUEUING PETRI NETS Dr. V.B. Kirubanand Associate Professor, Department of Computer Science CHRIST (Deemed to be University) Bengaluru-560029. ABSTRACT In each college it is required to screen participation. Educators anticipate that understudies should be available in the majority of their classes. In each college participation is taken for consistently. By along these lines all in all one hour is squandered multi day. To discover an answer for this disadvantage biometric based participation observing framework is planned. This arrangements with face recognition to maintain every one of the insights about the participation of the understudies are as of now put away in the class database. Camera catches the substance of the understudy and contrasts it and the database. On the off chance that it matches than the participation is checked present, if not, the participation is stamped missing. Also, in the event that the understudies confront isn't in the database, it says the individual isn't approved. Queuing Petri nets usage produces different customer demands handling with more effectiveness and without hold up time. By along these lines participation is denoted each hour. Keywords: Camera, Raspberry pi, Biometric device, Queuing Petri nets. Cite this Article: Dr. V.B. Kirubanand, Biometric Based Attendance Monitoring System Using Queuing Petri Nets. International Journal of Civil Engineering and Technology, 10(3), 2019, pp. 1773-1781 http://www.iaeme.com/IJCIET/issues.asp?JType=IJCIET&VType=10&IType=03 1. INTRODUCTION Face Recognition System Face Recognition Using Principal Component Analysis Additionally, face detection and recognition scheme must be capable of tolerating variations in the faces themselves.[2] The human face is not a unique rigid object. There are billions of different faces and each of them can assume a variety of deformations. Interpersonal variations can be due to race, identity,