Development of Contactless Employee Management System with Mask Detection and Body Temperature Measurement using TensorFlow

Development of Contactless Employee Management System with Mask Detection and Body Temperature Measurement using TensorFlow

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Product Code: Embedded - Raspberry pi
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Product Description

Objective

             Aim of the project is to build a smart employee management system which should be contactless, able to perform mask detection, body temperature detection and contain sanitizer dispensing unit.

Abstract

        CoVID-19 pandemic signified the importance of social distancing and non-contact routines. Even after the pandemic, everyone should abide by the same protocols for a hygienic life. Institutions must put in place pre-emptive measures before people return. These include marking the presence of employees and monitoring their health status. This paper focuses on developing a contactless employee management system with sensor fusion and deep learning technology. It can perform the attendance routine without compromising the safety measures. Employees can be identified using random QR code recognition which can avoid the mask removal to perform employee recognition. While recognizing the QR, system will double verify the employee by detecting the MAC address of is mobile Bluetooth at backend. It can eliminate fake attendance system. After employee identification system will perform mask detection process. To detect the mask, system uses the pre-trained deep learning model. That deep learning model is generated by CNN algorithm which can classify “Face with mask” and “Face with No mask”.  After successful completion of mask detection, system checks the employee body temperature by IR temperature sensor followed by sanitizer dispensing action. Response for the whole process will be updated to employee’s mobile application as well as Employee Management Authority (EMA).

 

Proposed System

             Proposed system uses two factor employee authentication processes to ensure the security and to eliminate the fake attendance system. That is Random QR code recognition followed by employee’s mobile Bluetooth MAC id verification. MAC id verification is done at back end without knowledge of employee. For Temperature measurement system uses the IR thermal sensor. Employee can get the process result in android application. If the safety (Mask and temperature detection) or security (Employee verification) measures are not matched system will intimate to Employee Management Authority through mail.

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Package Includes

Software Projects Includes

  1. Demo  Video
  2. Abstract
  3. Base paper
  4. Full Project PPT
  5. UML Diagrams
  6. SRS
  7. Source Code
  8. Screen Shots
  9. Software Links
  10. Reference Papers
  11. Full Project Documentation
  12. Online support


The Delivery time for software projects is 2 -3 working days. Some of the software projects will require Hardware interface. Please go through the hardware Requirements in the abstract carefully. The Hardware will take 7-8 Working Days

 

Hardware Projects Includes

  1. Demo  Video
  2. Abstract
  3. Base paper
  4. Full Project PPT
  5. Datasheets
  6. Circuit Diagrams
  7. Source Code
  8. Screen Shots & Photos
  9. Software Links
  10. Reference Papers
  11. Lit survey
  12. Full Project Documentation
  13. Online support


The Delivery time for Hardware projects is 7-8 working days.

   

Mini Projects: Software Includes

  1. Demo  Video
  2. Abstract
  3. Base paper
  4. Full Project PPT
  5. UML Diagrams
  6. SRS
  7. Source Code
  8. Screen Shots
  9. Software Links
  10. Reference Papers
  11. Full Project Documentation
  12. Online support

 

The Delivery time for software Miniprojects is 2 -3 working days.

 

Mini Projects - Hardware includes

  1. Demo  Video
  2. Abstract
  3. PPT
  4. Datasheets
  5. Circuit Diagrams
  6. Source Code
  7. Screen Shots & Photos
  8. Software Links
  9. Reference Papers
  10. Full Project Documentation
  11. Online support

The Delivery time for Hardware Mini projects is 7-8 working days.