Master copy implementation

TABLE OF CONTENTS

• Get Master DB
• Server Shell
• Facial recognition
  • Physical camera
  • Add the Camera to the HMI

• Get Master DB

  1.  AutoMill_Master\DB\MC Template\Automill.bacpac
     
  2. Restore Master DB onto Server
     1. Import Data-tier Application
     2. Import from local disk
     3. Please give it a proper name related to site
     4. Confirm DB Logins
     5. (Drop and create Station_Config)

• Server Shell

  1. D/AutoMill_Master/Automill Server
     1. Run the Server Shell
     2. Activate the UM Module and add the correct IPs
     3. 
     4. Restart The Shell
  2. AutoMill HMI
     1. Open HMI
     2. Mouse click twice next to the Login button(Header) and Press CTR + F12
     3. Add the UM module and Path to the server(Server IP) and confirm KVIM IP.  You can activate the 'Use Updater', but it must also be activated on the shell
        1. 

     4. iv. Reboot HMI Shell

     5. Log in with Kairos User and confirm docking

  3. Facial recognition

     1. Physical camera

        1. Power on

        2. Add Kairos as user

        3. Add Password not containing any special characters(!@#$%) password eg. Automill2023

        4. Add Static IP

     2. Add the Camera to the HMI

        1. On the HMI, go to the Body`s Config(In the big blue block, press CTR + F12)

        2. Facial Camera Configuration

        3. 

        4. Add Name, IP(Same as on the device), Username('admin'), Password(Same as device).  Press the 'ADD' button

        5. You can confirm in the Server Shell:

        6. 

        7. On the HMI, go to the Body`s Config(In the big blue block, press CTR + F12)

        8. Configuration:

        9. 

        10. Add the Name the Camera name to the: 'FR Camera Name'.  Remember no extra spcaes or new lines.

     3. Shut down the HMI

     4. Install the 32-bit VLC version(d:\Software\Facial recognition).  After installation, make sure VideoLAN is in the C:\Program Files (x86)\VideoLAN

     5. Open HMI, add a face to a test/your user

     6. Logout

     7. Test Facial recognition with the camera