IoT Based Classroom Environment Monitoring System
D.Surendran1, M.K.Bhuvana2, Monica Murugesan3, Saleekha4
1D.Surendran, Professor, Department of Computer Science and Engineering, Sri Krishna College of Engineering and Technology, Coimbatore, India.
2M.K.Bhuvana, PG Scholar, Department of Computer Science and Engineering, Sri Krishna College of Engineering and Technology, Coimbatore, India.
3Monica Murugesan, PG Scholar, Department of Computer Science and Engineering, Sri Krishna College of Engineering and Technology, Coimbatore, India.
4Saleekha, PG Scholar, Department of Computer Science and Engineering, Sri Krishna College of Engineering and Technology, Coimbatore, India.
Manuscript received on 08 April 2019 | Revised Manuscript received on 15 April 2019 | Manuscript Published on 26 April 2019 | PP: 636-640 | Volume-8 Issue-6S April 2019 | Retrieval Number: F61430486S19/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Field communication systems and sensors are playing an important and fundamental role in the Internet of things. RFID is one of the Near field communication technology, and widely used in different sector, such as in transportation, store sales, education, animal husbandry and so on. Because of information can be shared wirelessly via Bluetooth, Wi-Fi, Radio Frequency and Zigbee. Facial recognition is one of the simple and effective bio-metric authentication systems. LBP is a cost effective and simply efficient algorithm for face recognition using two dimensional surface texture operators. This paper is providing a way of accessing and controlling classroom with RFID and Facial recognition techniques. The overall performance of the system is completely monitored via web based framework. The students attendance monitoring and energy preserving activities are controlled by sensors, actuators, RFID tags, RFID reader, camera and raspberry pi kit.
Keywords: RFID Tags, Facial Recognition, Cloud Database, PIR Sensor, IoT, Web Framework.
Scope of the Article: Communication