One of the new and upcoming parts of the Oracle cloud is the Oracle AI Cloud platform. In effect this is a bundle of pre-installed frameworks and libraries who are tuned to run on the Oracle cloud infrastructure. One of the deployments in the Oracle AI Cloud Platform is OpenCV. When you are working with incoming visual data this might be of much interest to you.
OpenCV (Open Source Computer Vision) is a library of programming functions mainly aimed at real-time computer vision. Officially launched in 1999, the OpenCV project was initially an Intel Research initiative to advance CPU-intensive applications, part of a series of projects including real-time ray tracing and 3D display walls.
The below image showcases the full Oracle AI Cloud platform:
Example usecase
as an example usecase for using OpenCV from the Oracle AI Cloud Platform we like to outline a theoretical case where on a regular base pictures of a "old fashion" parking space at an airport are being uploaded to OpenCV. based upon the images that are being send to OpenCV on the Oracle AI Cloud Platform the system can detect on which part of the parking area most open spots are and direct visitors to this area.
Even though most parking spaces have a counter of how many cars are currently on the parking lot, when this is done for a large space it can still be hard to find the area where there are free spots. As you already would need some level of camera security for this area the costs for adding this feature are much lower compared to installing sensors in the ground who could detect where a car is parked or not.
Even though it might sound complex, detecting free parking space is a relative easy task to conduct with OpenCV and a large number of examples and algorithms are available. With relative ease you would be able to create a solution like this on the Oracle Cloud and by doing so improve the satisfaction of customers without the need to add sensors in every possible parking location.
OpenCV (Open Source Computer Vision) is a library of programming functions mainly aimed at real-time computer vision. Officially launched in 1999, the OpenCV project was initially an Intel Research initiative to advance CPU-intensive applications, part of a series of projects including real-time ray tracing and 3D display walls.
The below image showcases the full Oracle AI Cloud platform:
Example usecase
as an example usecase for using OpenCV from the Oracle AI Cloud Platform we like to outline a theoretical case where on a regular base pictures of a "old fashion" parking space at an airport are being uploaded to OpenCV. based upon the images that are being send to OpenCV on the Oracle AI Cloud Platform the system can detect on which part of the parking area most open spots are and direct visitors to this area.
Even though most parking spaces have a counter of how many cars are currently on the parking lot, when this is done for a large space it can still be hard to find the area where there are free spots. As you already would need some level of camera security for this area the costs for adding this feature are much lower compared to installing sensors in the ground who could detect where a car is parked or not.
Even though it might sound complex, detecting free parking space is a relative easy task to conduct with OpenCV and a large number of examples and algorithms are available. With relative ease you would be able to create a solution like this on the Oracle Cloud and by doing so improve the satisfaction of customers without the need to add sensors in every possible parking location.
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