Automatic animal detection and deterrent system
This disclosure provides a method of detecting and deterring a target animal from a target area. A target area is positioned within the field of vision of a video camera connected to a computer processing system. An animal identification computer program using convolution neural networks and deep learning computer programs and camera images rapidly detects a target animal. The animal identification computer program is trained to identify target animals accurately using a learning algorithm and related machine learning technology. The time to deploy a deterrent against a target animal from the instant of detection is 2 seconds or less so that little or no time is available to the target animal to damage the target area.
1. A method of detecting and deterring a target animal from a target area, comprising:
1) placing the target area within the field of vision of a camera, wherein the camera is connected to a computer processing system;
2) running an animal identification computer program with camera images from the camera to detect a target animal;
3) deploying a deterrent to cause the target animal to leave the target area;
4) training the animal identification computer program to identify target animals using a learning algorithm;
5) training the learning algorithm with training data sets;
6) validating the training of the learning algorithm with validation data sets;
7) creating the training data sets and the validation data sets by gathering target animal image data in a target area, building image data sets for target animals and for target areas from the image data, and annotating or labeling images in the data sets so that the data sets may be entered into the learning algorithm;
8) deploying the deterrent against a target animal within 0.25 to 2 seconds from the instant of detection; and
9) repeating step 3 if the target animal has not left the target area after deploying the deterrent.
2. The method of claim 1 , further comprising using convolution neural networks and deep learning computer programs with the camera images to detect the target animal.
3. The method of claim 1 , further comprising verifying if a target animal is in the field of view of the camera.
4. The method of claim 1 , further comprising recording the target animal with the camera if the target animal is in the field of view of the camera.
5. The method of claim 1 , further comprising arming one or more deterrents and setting a target location.
6. The method of claim 1 , wherein the deterrent is a sound device, a light device, a water spray device, compressed air used with projectiles, or combinations thereof.
7. The method of claim 1 , further comprising identifying the species of the target animal.
8. A method of detecting and deterring a target animal from a target area, comprising:
1) placing the target area within the field of vision of a camera, wherein the camera is connected to a computer processing system;
2) running an animal identification computer program with camera images from the camera to detect a target animal;
3) deploying a deterrent to cause the target animal to leave the target area;
4) training the animal identification computer program to identify target animals using a learning algorithm;
5) training the learning algorithm with training data sets;
6) validating the training of the learning algorithm with validation data sets;
7) creating the training data sets and the validation data sets by gathering target animal image data in a target area, building image data sets for target animals and for target areas from the image data, and annotating or labeling images in the data sets so that the data sets may be entered into the learning algorithm;
8) deploying the deterrent against a target animal within 0.25 to 2 seconds from the instant of detection, wherein the deterrent is a sound device, a light device, a water spray device, compressed air used with projectiles, or combinations thereof; and
9) repeating step 3 if the target animal has not left the target area after deploying the deterrent.
9. The method of claim 8 , further comprising using convolution neural networks and deep learning computer programs with the camera images to detect the target animal.
10. The method of claim 8 , further comprising verifying if a target animal is in the field of view of the camera.
11. The method of claim 8 , further comprising recording the target animal with the camera if the target animal is in the field of view of the camera.
12. The method of claim 8 , further comprising arming one or more deterrents and setting a target location.
13. The method of claim 8 , further comprising identifying the species of the target animal.