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• You can configure the Fire detection module on the settings panel of
the 
• the Fire detection object created on the basis of the Camera object on the Hardware tab of the System settings window.
• You can configure the Smoke detection module on the settings panel of the Smoke detection object created on the basis of the Camera object on the Hardware tab of the System settings window.
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The To configure the Fire detection and Smoke detection modules are configured similarly and as follows modules, do the following:

1. Go to the settings panel of the
appropriate
2. corresponding module.
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3. To receive events about the end of fire/smoke only after the time period
specified in
4. from the Alarm duration, sec
parameter
5. setting, set the Track alarm end checkbox. By default, the checkbox is
clear
6. cleared, which means that events about the end of fire/smoke are received immediately.
7. In the Alarm duration, sec field, enter the time period in seconds during which the repeated fire/smoke alarm events are ignored. By default, the setting isn't available for editing. To enable it, you must set the Track alarm end checkbox (see the previous step).

   Info
   title Note

The

8. If you set the Track alarm end checkbox, the events about the end of fire/smoke are received after the time specified in

the

9. the Alarm duration, sec

parameter has expired. During this time, all repeated fire/smoke alarm events are ignored. A

10. setting. If, until the end of this period, the current fire/smoke is completed and the new one is detected, the detector doesn't generate events about completing the current and starting the new alarm. The new fire/smoke event is received after the current alarm

has

11. is completed.

12. Set the Generate alarm on camera checkbox if
it is necessary
13. you want to initiate an alarm on the camera when the detector
is triggered
14. generates an event.
15. By default, the standard (default) neural network is initialized according to the device selected in
the Device drop-down list. The
16. step 10. You must not select the standard neural networks for the different
types of processors are selected
17. processor types manually, since it is performed automatically. If there is a
custom
18. unique neural network
is prepared
19. for use,
in the
20. click the Image Added button to the right of the Tracking model field,
click the Image Removed button,
21. and 
select the
22. specify its file in the standard Windows Explorer window that opens.

23. In the Detection sensitivity [0, 100] field, enter the detector sensitivity

of the detector

24. —an integer value in the range from 0 to 100. This parameter determines at what certainty of fire/smoke detection the detector

will generate

25. generates an alarm: the higher the sensitivity, the higher the recognition threshold. For example, at sensitivity 100, the detector neural network must get 100% certainty for some period of time

when

26. during the frame processing

the frames

27. . The value of the Detection sensitivity field is determined experimentally.

28. In the Frames processed per second [0.016, 100] field, set the number of frames per second that
will be processed by
29. the neural network processes. This value affects the processor load: the higher the value, the greater the load. It also affects the operation speed of the algorithm: the higher the frame rate, the faster the required number of frames are collected for making a decision and generating an alarm, if required.

30. In the Number of frames for analysis and output [5, 20] field, enter the minimum number of frames in the range from 5 to 20 for the detector to analyze before generating an alarm. The higher the value, the more reliable the result of the detector operation. At the same time, if the value is too high, the short-time fire/smoke can be missed. If you enter a value less than the minimum, the value is set to 5.

31. Set the Scanning mode checkbox to track small objects. If you enable this mode, the load on the system increases.

So

32. That is why we recommend

specifying a

33. setting the small number of frames processed per second in

the Frames processed per second [0.016, 100] field.

34. step 7. By default, the checkbox is

clear

35. cleared. For more information on the scanning mode, see Configuring the Scanning mode.
    

    Info
    title Note
    You cannot configure the scanning windows for the Fire detection and Smoke detection modules. The default parameters are used. When you use the scanning mode, we recommend using a full frame without specifying the area of interest in step 11.

36. From the Device drop-down list, select the device on which the neural network will operate: the CPU, one of the NVIDIA GPUs, or one of the Intel GPUs. Auto (default value)—the device is selected automatically:
 
37. The NVIDIA GPU gets the highest priority, followed by the Intel GPU, then the CPU.
    

    Note
    title Attention!
    We recommend using the GPU. It can take several minutes to launch the algorithm on the NVIDIA GPU after you apply the settings. You can use caching to speed up future launches (see Optimizing the operation of neural analytics on GPU).

38. Specify the area of interest on the video image:
    1. Click the Stop video button to capture the frame of the video image.
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    2. Click the Area of interest button.

    3. On the captured video

image

39. 1. frame, sequentially set the anchor points of the area using the left mouse button, the situation

in

40. 1. of which you want to analyze

, by sequentially clicking the left mouse button

41. 1. . After you add

an

42. 1. the area, the

rest

43. 1. remaining part of the video image is darkened. If you don't specify the area of interest, the entire frame is analyzed.
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    2. Click the OK button.

       Info
       title Note
       To remove the area, click the Image Modified button next to the Area of interest button. You can add only one area. If you try to add

a

44. 1. the second area, the first area

will be

45. 1. is deleted.

46. Click the Apply button.

Configuring the Fire detection and Smoke detection modules is complete. 

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