The development of visual processing technology helps IOT video applications more intelligent
When collecting data with the camera and uploading it to the cloud, a big problem is how to tell which data is available and which ones are noise signals? Visual processing is to solve such a middle part of the problem. Last week, Intel announced the acquisition of Movidius Inc., a video processing chip maker, whose key product is its vision-processing chip (VPU), which is being aggressively developed for applications in the field of VR processing and IoT visual processing such as UAVs. This event once again aroused the industry's discussion of visual processing technology, the main purpose of this technology is to achieve the machine instead of the human eye to make measurements and judgments. The development of this technology will help those with video-enabled IoT applications intelligent. Why do you say that?  Under the forecast that the number of interconnected devices will reach 200 billion by 2020, it is undeniable that the development of the Internet of Things has encountered unprecedented opportunities and the commercial value it brings is incalculable. With this tide, the application layer of the Internet of Things is booming; a variety of new terminals emerge one after another. And of these, a large part of the terminal must have video capabilities. For example, in the area of ​​smart security, network cameras are required to collect enough image data to judge unexpected unexpected situations; in the field of smart home, networked cameras are needed to ensure the safety of family and property; in the field of car networking, networked cameras are needed to record unexpected situations As well as the daily travel scenery; in the field of smart retail, the need for webcam recording customer behavior to analyze their preferences. As Huawei founder Ren Zhengfei recently said at a forum in Japan: "I think the future of human information flow of 90% -95% should be an image." And video is one of the most important sources of images, Ren Zhengfei Added: "Our supreme program is to solve the problem of video algorithms." Admittedly, in the next five years, everything you do will have useful video capabilities, which is one of the future trends. If a traditional vendor wants to make his product intelligent, such as a doorbell or a sweeping robot, then adding networked video capabilities is a good choice and the process takes three steps: The first step is to install an IP camera to collect Video data. The second step is to select a cloud platform vendor that focuses on video wide data transmission, such as Wisdom of Intelligence, to transmit these data to the cloud. Thirdly, to further analyze video data and tap the value. When collecting data with the camera and uploading it to the cloud, a big problem is how to tell which data is available and which ones are noise signals? Visual processing is to solve such a middle part of the problem, through advanced graphics processing capabilities and more intelligent algorithms, can be collected from the terminal video data filtering out useless information, increase data value, make the application more intelligent. IoT & M2M Platform Solution Leader IWT wisdom said: "IWC's Kalay cloud platform provides partners with an image storage solution that brands and service providers can use to deliver to consumers. For example, Kalay cloud platform cloud video capabilities, when the traditional vendors for their products equipped with monitoring equipment, the device once detected items move, you can start the video function to synchronize the relevant images stored in the cloud at the same time send a warning message, the user View images in real time to confirm, but also after the incident through the cloud list playback event 60 seconds image. If manufacturers can combine products with visual processing technology, the terminal will be able to diagnose whether it really happened unexpectedly, rather than having to check it all the time to make the product more intelligent.
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