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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)

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Impact Factor : 8.14

Issue per Year : 12

Volume Published : 7

Issue Published : 74

Article Submitted : 3608

Article Published : 2079

Total Authors : 5515

Total Reviewer : 528

Total Countries : 39

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Published Paper Details
Paper Title: IOT ENABLED SMART DOORS THROUGH FACE MASK DETECTION
Authors Name: Anshuja Anand Meshram , Kunal Bhojraj kohale , Ankita Tote , Aniket Dnyandeo Agham , Prof. Sudesh A. Bachwani
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IJRTI_182325
Published Paper Id: IJRTI2206133
Published In: Volume 7 Issue 6, June-2022
DOI: http://doi.one/10.1729/Journal.30728
Abstract: COVID 19 pandemic is causing a global health epidemic. The most powerful safety tool is wearing a face mask in public places and everywhere else. The COVID 19 outbreak forced governments around the world to implement lockdowns to deter virus transmission. In this paper, an IoT-enabled smart door that uses a machine learning model for face mask detection. Evaluation of the proposed framework is done by the Face Mask Detection algorithm using the TensorFlow software library.[1] The proposed framework capitalizes on the MobileNetV2 face detection model to identify the faces and their corresponding facial landmarks present in the video frame. The proposed methodology demonstrated its effectiveness in detecting facial masks by achieving high precision, recall, and accuracy.[2] In the field of computer vision, this is a common research direction by extracting features directly from the detection region and then using machine detection learning algorithms to identify and recognize[3]. This proposed system can detect the users from COVID 19 by enabling the Internet of Things (IoT) technology.[1]
Keywords: Face mask detection, Deep learning , Internet of things ,Arduino ,MobileNetv2, Tensorflow , Keras ,OpenCV , Pyfirmata .
Cite Article: "IOT ENABLED SMART DOORS THROUGH FACE MASK DETECTION ", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.7, Issue 6, page no.796 - 802, June-2022, Available :http://www.ijrti.org/papers/IJRTI2206133.pdf
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ISSN: 2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publication Details: Published Paper ID: IJRTI2206133
Registration ID:182325
Published In: Volume 7 Issue 6, June-2022
DOI (Digital Object Identifier): http://doi.one/10.1729/Journal.30728
Page No: 796 - 802
Country: Yavatmal, Maharashtra, India
Research Area: Computer Engineering 
Publisher : IJ Publication
Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2206133
Published Paper PDF: https://www.ijrti.org/papers/IJRTI2206133
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED
Journal Starting Year (ESTD) : 2016

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