I cameras were designed to support algorithm

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rifattryo.ut11
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Joined: Mon Dec 23, 2024 6:12 am

I cameras were designed to support algorithm

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Generally, it will cooperate with the cloud for secondary calculation. Therefore, this type of camera is generally suitable for lightweight computing scenarios, such as personal and pet movement recognition in home monitoring, basic personal and vehicle entry and exit recognition, etc. Advantages This type of camera is cheap and the cost of deploying the equipment is not high. It basically meets most needs. i In addition, can the camera's built-in algorithm be upgraded? The earlier built-in I camera used a fixed algorithm. The I function and recognition model pre-installed at the time of purchase could not be updated after leaving the factory.



Later, as more and more high-end or new generation built-infirmware japan mobile number code updates, cloud connection updates, pluggable modules or expansion slots. . Acquisition camera plus I edge computing unit We can understand the edge computing device as installing another device next to the camera. The purpose is to process, analyze and make decisions on the spot before the data is transmitted to the cloud or data center. After the monitoring data is aggregated, it is preliminarily analyzed, processed and filtered before uploading it to the cloud or central management system.



Advantages Low latency: Since data processing occurs at the edge close to the data source, data transmission latency can be significantly reduced, which is critical for applications with high real-time requirements (such as autonomous driving and smart manufacturing). Improve response speed: Local processing capabilities enable the I edge computing gateway to respond quickly, improving the overall system operation efficiency and user experience. Reduce bandwidth requirements: By filtering, compressing and preprocessing data at the edge, the amount of data that needs to be uploaded to the cloud is reduced, saving network bandwidth resources. Disadvantages High cost: Edge computing gateways require special hardware equipment, which is expensive to purchase and maintain, especially when deployed on a large scale.
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