Where does the video surveillance camera go? The advanced chip with artificial intelligence (AI) is an important core part of the next generation Internet Protocol (IP) camera, which enables the camera to collect valuable information about relevant events.
Thanks to advanced chip technology, surveillance cameras can now easily perform complex analysis operations, which will promote the all-round development of AI in the IP camera market.
Expand the global IP Camera Market
According to IHS Markit, the video surveillance equipment market grew to US $18.5 billion in 2018 and is expected to continue to grow this year. The latest research shows that ubiquitous video, edge computing and AI will have a significant impact on the commercial and consumer markets.
Edge computing means that the processor inside the camera is powerful enough to encode and transmit video streams while running AI processing locally, and can realize all functions with low power consumption to adapt to the limited thermal budget of IP cameras. The new SOC chip will be able to perform all processing on the camera and provide accurate AI information without sending data to the server or cloud for processing.
Now, we can directly analyze the data in the camera itself, so as to provide high performance, real-time video analysis and low delay. The new generation SOC makes this new AI mode possible, which is the key driving force behind the growth of IP camera market.
Enable video analysis for microprocessor
Microprocessor enabled analysis makes it easier for users to extract valuable data from video streams. What are insiders’ views on retail customer behavior? Consider using cameras in department stores to monitor shoppers’ behavior, traffic conditions and areas of concern. Will the next generation of cameras be able to identify how long shoppers stay in front of specific displays? Did the shopper leave and return? And whether the shopper finally purchased the goods?
The next generation of cameras will be able to create heat maps of stores to see where people spend the most time, so retailers will be able to adjust product distribution accordingly. Video analysis can also help determine the free and busy time of the day, so retailers can arrange their work accordingly. By understanding the behavior of customers, retailers can determine the interaction with customers, determine the best position for advertising, and prompt shoppers about which products are doing activities in time!
Achieve rapid response and processing at the municipal level
Urban surveillance and smart city rely on advanced video surveillance and intelligence to monitor people and vehicles, identify criminals, mark suspicious behaviors and identify potential dangerous situations. For example, wandering, a large number of people gathering or the wrong direction of the car, etc.
Local quick decision-making on the camera can also be used to help analyze traffic conditions, adjust traffic lights, identify license plates, automatically charge for parking, find lost vehicles in the city or create real-time and accurate traffic maps.
Real Time HD video monitoring and recording
In terms of home monitoring, what will the next generation of video surveillance cameras provide? The real-time monitoring and notification function can detect whether personnel are in the backyard or approaching the door, whether there are suspicious vehicles or packages in the lane, and whether they have been transported (or stolen). Advanced cameras can determine when notification is required and not required, because users do not want to receive error alarm notification caused by rain, branch movement, etc.
The next generation video camera function can also help monitor your family or pets, so that you can feel at ease at work or on vacation.
Next generation IP Camera
The IP camera may be powered by the next generation SOC chip. What does this mean for you:
Save network bandwidth, cloud computing and storage costs. There is no need to continuously upload videos to the server for analysis. The camera can perform analysis locally and only upload relevant videos.
Faster reaction time. Decisions are made locally without network delays. This is critical if there are situations where you need to alert on a particular event.
rights of privacy. In the most extreme case, the video does not need to leave the camera, but only send the metadata to the cloud or server. For example, you can recognize and manipulate faces in the camera, but the video will never reach the cloud.
Search is easier. Instead of viewing hours of video content, the server only needs to store / analyze metadata and easily perform search.
Flexibility / personalization. Compared with the general server, each camera at the edge can be personalized to make it work better in a specific scene.
No cloud computing required. For cameras in remote areas or with limited network bandwidth, users can perform all analysis locally without relying on uploading videos to the server / cloud.
Higher resolution / quality. When AI processing is performed locally, the full resolution of the sensor (up to 4K or higher) can be used, and the video streaming to the server will usually have a lower resolution, i.e. 1080p or less. This means that there are more pixels available locally for the AI engine, so you can recognize faces from a longer distance than streaming video from the camera.
By 2020, we will begin to see the availability of consumer cameras that enable real-time video analysis at the edge of the home. With the rapid development of technology and the growth of customer demand, artificial intelligence is on the edge of explosive development. In terms of image quality and video analysis, the new generation of IP cameras will play an important role in department stores and urban streets.
Responsible editor: GT