Smart Security and Surveillance System in Laboratories Using Machine Learning

Autor: Krupali Shetty, V. Anni Shinay, Suneeta V. Budihal, G. Tejaswini, Shweta Hinge, Ashwini Patil, C. Sujata, Nalini C. Iyer
Rok vydání: 2021
Předmět:
Zdroj: Communications in Computer and Information Science ISBN: 9789811604188
DOI: 10.1007/978-981-16-0419-5_2
Popis: The paper proposes to design and develop a smart authentication system in laboratory as a part of security and surveillance. To address the unauthorized entry in the laboratory, a smart alert system is designed and developed. The authentic entry to any laboratory will reduce the student response to hazards and accidents, risks to acceptable levels. The proposed methodology uses face detection and recognition techniques for the student authentication. Based on the results, the attendance is updated in the attendance data base if the authorized users enter the laboratory else the details will be sent to the course instructors through the registered mails. The authentic student is also verified for wearing the personal protective equipment during the entry to the laboratory. By this, we can reduce the vandalism occurring in laboratories and maintain the integrity.
Databáze: OpenAIRE