Attention has recently been focused on AI as the key technology in a variety of fields. Network cameras are no exception. With AI, the accuracy of data analysis has improved exponentially. But the technology has raised several issues.
Through advancements in Edge AI, i-PRO has been engaging in research and development to further draw on the power of AI with greater precision, and to develop systems that offer greater security. Here, we’d like to tell you more about what’s behind the strategy.
Present Status of Network Cameras and Issues That Need Solving
One of the important technologies that supports AI is deep learning. This is a type of machine learning by which characteristics or patterns are automatically detected and extracted from large volumes of unprocessed data (such as images, sounds, etc.).
By harnessing deep learning, network cameras can achieve a tremendous boost in image analysis power, and greatly improve accuracy in the detection and recognition of objects—this is just one example of how it is helping our lives.
As AI becomes even more prevalent in the future, some concerns will need to be addressed. We at i-PRO are considering three main issues: cost, data confidentiality, and delays.
Issue 1: Cost
To do AI processing, a massive amount of computating power is required. Building up sufficient computing resources, such as GPUs and CPUs, and introducing the technology involves high cost barriers.
Issue 2: Data Confidentiality
Normally, image and audio data are transmitted via the network to a server or a cloud for processing. Even when this step is protected with a variety of security measures, concerns exist that, during the transmission process, data might leak or be tampered with.
Issue 3: Delays
Video and audio data, and particularly video, comes in very large volumes, and between the time this data is transmitted back to the network and processed, and before the results are fed back, a small time lag may occur. As a result, data cannot be confirmed in real time.
Edge AI provides solutions to all three of these issues.
What i-PRO’s Edge AI, Which Harnesses the Best of Technology, Is Revolutionizing
“Edge” means “terminal”—or in other words, the edge of the security system as a whole, which is the network camera, another i-PRO product that’s installed on the front lines. So Edge AI refers to AI processing on the edge, not on a server or in the cloud. In the case of network cameras, a camera equipped with an AI processor analyzes video, audio, and other data.
This eliminates the need for data processing over the network. So server installation or cloud maintenance costs can be reduced, without concerns about leakage or data tampering. What’s more, since the video and audio can be captured and analyzed immediately, data is obtained in real time, without delays.
Edge AI not only provides solutions to the above issues, but also greatly improves the accuracy of image analysis.
Because of the large volume of data involved with video and audio, in general the data must be compressed when being transmitted over the network. This can affect the accuracy of the analysis. But with Edge AI there’s no need to compress the data since it does not go through the network. And since the terminal analyzes the RAW data (data before processing), high accuracy can be maintained.
In addition, the camera is able to check and analyze changes in the environment (such as in the weather) and immediately reflect these changes via measures such as video quality control to prevent loss of accuracy.
Developing terminals that can use Edge AI has not been an easy task. In addition to quickly incorporating new improvements in deep learning, i-PRO’s efforts on the research and development of Edge AI harness our video and audio control technologies, terminal development technologies, and overall manufacturing know-how.
The end result allows you to make use of distributed processing technology, even from compact Edge terminals.
Software Development: Another Key to Realizing Edge AI
A wealth of applications for video and audio analysis are available to run on servers and in the cloud. For Edge AI, seamless migration of these applications to the terminals is essential. Here, i-PRO is working on developing technology to enable applications that run on servers or in the cloud to run on terminals.
Applications that run in the cloud are subjected to distributed processing, through a technology called containerized virtualization. This allows the system to be maintained even in the event of a failure or malfunction of a single terminal, and also has the advantage of distributing the load on the system, making it easier to manage operation of applications and expansion of the system.
However, distributed processing technology demands an environment with ample computing and memory resources, making incorporation into a terminal a high hurdle. i-PRO is also taking up the challenge of incorporating such technologies into small terminals with limited resources, or to perform processing in the same class of terminals.
Thanks to the future development and expansion of Edge AI, i-PRO customers will be able to expect security systems boasting even greater accuracy and security.