IRJET- Customized Campus Surveillance System

International Research Journal of Engineering and Technology (IRJET)

e-ISSN: 2395-0056

Volume: 07 Issue: 01 | Jan 2020

p-ISSN: 2395-0072

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Customized campus surveillance system Sarikonda Poojitha1, Dr. Sunil Bhutada2 1M.Tech

Student, Information Technology Department, Srinidhi college of science and technology, Hyderabad, Telangana, India 2Professor, Information Technology Department, Srinidhi college of science and technology, Hyderabad, Telangana, India ---------------------------------------------------------------------***--------------------------------------------------------------------Abstract - Colleges these days are trying to augment the quality of being in the campus by integrating the finest practices of safety along with security with the help of technology. A significant element of a comprehensive security system is the deployment of a surveillance camera scheme.

This surveillance in the college is intended to identify the authorization of the people who try to enter into the college and aid in protecting the property of the College in conjunction with student`s safety. These guidelines concentrate on the College’s safety and security needs while respecting individual privacy of those attending, working or visiting the College. This ensures monitoring the presence of the student in the campus by the parents and the college.

Key Words: surveillance camera scheme, authorization, monitoring, privacy.

1. INTRODUCTION Surveillance system is generally significant in the field of security. Preset days, video surveillance framework is a significant security resource for business, law implementation and military applications. Straightforward frameworks recognize movement in a camera's field of view. Surveillance cameras are camcorders utilized to watch a region. They are regularly associated with a chronicle gadget or IP organize, and might be viewed by a security gatekeeper or law authorization official. Cameras and recording gear used to be moderately costly and required human faculty to screen camera film.

Identification and authorization has become an important subject. This framework provides the identifying and authorizing a person from his entry into the campus. The visual Surveillance captures the images of the persons and identifies them to the already existing database. This includes installation of a cctv camera to capture the images of the persons. The fundamental issues when structuring an insightful CCTV framework are identified with the choice of the correct focal points and sensors for camcorders utilized, as these cameras ought to have the option to give 100% inclusion to the zone being under observation. It plans to consequently distinguish, perceive and track individuals and items from picture arrangements so as to comprehend and portray elements and cooperation among them.

Entryway security or passage entryway security is important to anticipate the authorization in the controlled region. A customary checking gadget makes utilization of Š 2020, IRJET

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costly hardware, includes high power utilization and requires consistent plate get to which clearly requires colossal space. The installed arrangements beat these deficiencies and give live encourages from webcam working on cloud without the requirement of the PC. Calculations are added to the inserted frameworks to increase their effectiveness, by making utilization of the open source libraries, the development location calculations permit Aurdino Uno to distinguish development, the protest discovery calculations identify true elements like face of a person.

The new TensorCam is the security camera with built-in Artificial Intelligence that has been specifically designed for capturing images of living and non living things.

Here the AI is built on Google’s TensorFlow, Keras, and Caffe2, and one can setup their own recognition tasks using the Deep Cognition Deep Learning Studio. We can use the deep learning capabilities to setup specific tasks, like detecting certain objects, specific faces, or even particular kinds of actions. The camera itself has full HD 1080p resolution and night vision, and will live stream the feed so one can check it whenever required.

Facial acknowledgment CCTV innovation yields phenomenal execution in spite of halfway impediments of the face, the utilization of glasses, scarves or tops, changes of outward appearance, and moderate pivots of the face. Also, it doesn't enable clients to be imitated utilizing photos. Tensor biometric innovation is the ideal answer for control the entrance of staff to confined security zones.

2. LITERATURE SURVEY: Ching-Kai Huang and Tsuhan Chen [1] proposed a technique by recording just video that has significant data, i.e., video that has movement in the scene. This can be accomplished with a computerized camcorder furthermore, a DSP calculation that identifies movement.

Wijnhoven et al [2] considered model-based element location for traffic reconnaissance, going for object arrangement. Inside distinguished locales of-intrigue (ROIs) of moving articles in the scene, the direction of the item is detected utilizing an angle bearing histogram. For the purposeful direction, a 3D wire-outline model is applied onto the picture information and the best coordinating pixelposition is determined inside the item's districts of-intrigue.

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International Research Journal of Engineering and Technology (IRJET)

e-ISSN: 2395-0056

Volume: 07 Issue: 01 | Jan 2020

p-ISSN: 2395-0072

www.irjet.net

Stauffer, C et al [3] examined about demonstrating each pixel as a gathering of Gaussians and utilizations an online estimate to restore the model. The Gaussian appropriations of the versatile blend model are evaluated to figure out which are probably to result from a foundation process. Every pixel is sorted dependent on the Gaussian dispersion which speaks to it most productively is viewed as a component of the foundation model..

Rama et al [4] tended to the issue of how to pick the most good number of sensors and how to choose their area in a given observed region for MSS. Pradeep et al [5] suggested a novel strategy which energetically processes the certainty level of new streams in view of the reality whether it gives proof which agrees or repudiates with the effectively confided in streams Atrey et al [6] displayed a top-down occasion discovery approach for sound based occasion recognition for reconnaissance. The proposed approach at first sorts a given sound edge into non-vocal and vocal occasions, and next convey outs advance grouping into energized and typical occasions.

An ensuing system,W4S [7], incorporated ongoing sound system to survive the complexities that W4 met with unexpected brightening changes, shadow and impediment which make following a lot harder in force pictures.

location of the respective person. Upon entering the campus, each time the person has to be identified by the Cam i.e., whether he is already registered or not. If the person`s data is already available at the database, he is allowed to enter. If the person`s data is not available in the database the computer that is connected to the cam asks for the registration or creation of the new table. The person who is identified is highlighted in the green color and the person who is unidentified is highlighted in red color. Upon the indication of the person`s face in red highlighted box, they are entitled to register. It is easy to monitor who is entering into the campus. Basically there are two main categories in the database with the person`s details. They are PRIVATE (Pr) and PUBLIC (Pu). Private consists of students, employees (working and non- working staff).Public is for the people who are visitors of the college. Each data sheet of the student contains the name, roll no, admission no, class, department, entry and exit data. Each data sheet of the employee contains the name, employee id, designation and the department entry and exit. Visitor`s data sheet contains the details as name, person to be visited, mobile number, entry and exit details. A log entry is enlarged upon requirement. This also includes the facility of logging into the website for monitoring the presence of the students by their parents.

Wren et al. [8] built up The Pfinder framework which is utilized to recover a 3-dimensional portrayal of an individual in a tremendous zone.

Axel Baumann et al [9] gave a precise survey of quantifies and assesses their adequacy for explicit highlights like division, occasion recognition and following.

Ismail Haritaoglu et al [10] proposed a minimal effort PC based constant visual observation framework, called W4, for following individuals and their pieces of the body, and administering their exercises in surround sound and monochromatic symbolism. It works on grayscale just as infrared video symbolism 3. PROPOSED SYSTEM: The system`s architecture propounds the installation of TensorCam at each entry level. The objective of this system is the availability of the TensorCam is to capturing and the comparing for the identification of the authorized and the unauthorized persons upon the entry into the campus. A database is connected to the TensorCam in which the details of the persons (studying, working ,visiting the campus ) along with the photographs are stored. Tensorcam captures each person`s face upon the entry and compares it with the data present in the database. The architecture includes the installation of end-end surveillance i.e., upon entering and leaving the college. And also intermediate cameras are installed at different levels to check the presence and Š 2020, IRJET

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Figure: Architecture of the proposed system.

RESULTS: Using the proposed system a database has been created with the enrolled students. Appropriate images of the students have been taken. The camera has to be setup in such a way that faces can be captured via camera .

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International Research Journal of Engineering and Technology (IRJET)

e-ISSN: 2395-0056

Volume: 07 Issue: 01 | Jan 2020

p-ISSN: 2395-0072

www.irjet.net

[3] Stauffer. C, Grimson W.E.L, “Adaptive background mixture models for real-time tracking”, IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Volume 2., Ft. 1999, pp. 252–258.

[4] Rama, K.G.S., Atrey, P.K., Singh, V.K., Ramakrishnan, K., Kankanhalli, M.S., “A Design Methodology For Selection and Placement of Sensors in Multimedia Surveillance Systems”, The 4th ACM International Workshop on Video Surveillance and Sensor Networks, Santa Barbara, CA, USA 2006.

[5] P. K. Atrey, Mohan S. Kankanhalli, Abdulmotaleb El Saddik, “Confidence Building Among Correlated Streams in Multimedia Surveillance Systems”, MMM 2007, LNCS 4352, Part II, 2007, pp. 155–164.

Figure: Camera identifying the students while entry into the college.

[6] Atrey, P.K., Maddage, N.C., Kankanhalli, M.S., “Audio based event detection for multimedia surveillance”, IEEE International Conference on Acoustics, Speech and Signal Processing, 2006, pp 813–816.

[7] Ismail Haritaoglu, David Harwood, Larry S. Davis, “W4S: A Real-Time System for Detecting and Tracking People in 2 ½ D”.

[8] Wren, C. R., Azarbayejani, A., Darrell, T., Pentland, A. P.: Pfinder:real-time tracking of the human body. IEEE Transactions Pattern Analysis Machine Intelligence, Vol. 19, No.7,780–785.(1997)

Figure: Camera identifing students in side the campus.

CONCLUSION & FUTURE WORK: In current generation security has been a major concern in most of the sectors especially in Educational institutions where it constitutes large number of people. So the proposed setup enables the Institution management as well as parents to have surveillance without interrupting one’s privacy. By utilizing this setup, it emphasizes the identification of persons very efficiently. The capability of enhancing situational awareness across multiple scales of time and space is the significant feature of this system. Addition of an alarm to the system adds an advanced security when prohibited persons try to enter the campus. A video tracking be added to monitor any suspicious activities.

[9] Axel Baumann, Marco Boltz, Julia Ebling, Matthias Koenig, Hartmut S. Loos, Marcel Merkel, Wolfgang Niem, Jan KarlWarzelhan, Jie Yu “A Review and Comparison of Measures for Automatic Video Surveillance Systems”, Hindawi Publishing Corporation EURASIP Journal on Image and Video Processing Volume 2008, Article ID 824726, 30 pages doi:10.1155/2008/824726.

[10] Ismail Haritaoglu, Harwood, D., Davis, L, “W4: real-time surveillance of people and their activities”, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 22, 2000, pp. 809–830.

REFERENCES [1] Ching-Kai Huang and Tsuhan Chen, “Motion Activated Video Surveillance Using TI DSP”, DSPS FEST '99, Houston, Texas, August 4-6, 1999.

[2] Wijnhoven, R., de With, P, “3D wire-frame objectmodeling experiments for video surveillance”, Proc. of 27th Symposium on Information Theory in the Benelux, 2006, pp.

101–108.

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