Cutting edge technology

Introduction: It is predicted that by 2025, the AI ​​market will grow at a compound annual growth rate (CAGR) of 50%, with revenue mainly focused on the use of smart vision technology. With the deepening of deep learning in the field of smart home applications, including facial recognition, iris and gesture monitoring, object and free space detection will be widely used.

With the development of modern science and technology and the improvement of people's living standards, the penetration rate of smart devices has become higher and higher, and the intelligentization of residential homes will be an important development trend. In recent years, the research on smart homes has begun to take shape at home and abroad, and the existing home monitoring system is relatively low in intelligence and cannot adapt to new application requirements. Therefore, it is very important to develop a safer and convenient smart home system. The meaning.

Artificial intelligence can act on multiple systems in a smart home. Among them, the visual branch of artificial intelligence-image recognition technology, involving image processing, pattern recognition, computer vision, neural network and many other disciplines, is an important auxiliary tool for smart home systems, which combines embedded operating system and embedded hardware. The platform strengthens the combination of itself and smart home applications, and has the characteristics of new concept and strong practicability. At present, image recognition in smart home systems is mainly based on face recognition and has been widely used in multiple scenes. This article will focus on AI vision applications in home scenarios.

Image Recognition Technology in Home Intelligence Security

Image recognition refers to the technique of using computers to process, analyze, and understand images to identify targets and objects in various modes. Image recognition is an important field in artificial intelligence. It is mainly used in the security home in the security level.

Smart Camera: The camera captures the image and can recognize the content of the image through image recognition technology to make different responses. Some home camera machine learning techniques adapt to new information in a similar way to the neural network in the brain, identifying whether there are dogs, cats, or courier packages on your porch. Some home monitors automatically analyze the recorded video, showing only a few minutes or a few screenshots to let the user know what information is needed, rather than reviewing the entire day. Some home monitors can identify differences between family and intruders, rather than triggering false alarms and even monitoring renovation workers during renovations.Every move, once a violation occurs, the user will be notified as soon as possible.

It is worth mentioning that compared with the pixel competition of the home camera, whether the function of video call, environment-aware, object recognition, and behavior recognition will gradually become the "smart" and "mental barrier" of the home camera. The watershed, artificial intelligence technology allows the camera to not only provide the function of shooting, discovery, identification, verification, shooting, transmission, one step in place.

Intelligent lock: The method of opening the smart lock has been updated following the development of biometric technology. The push-type fingerprint recognition technology is based on the rapid development of the fingerprint recognition module on the mobile phone. Under the empowerment of AIOT, the smart lock can realize face recognition through the combination of face recognition, remote vision and smart door lock. It can accurately and quickly and efficiently perform face recognition. No perception pass. The multi-function alarm connected by smart lock can connect the community property platform and the public security system to provide users with a safe and comfortable home environment.

However, the current face recognition smart lock faces two major challenges. One is the cost issue. The cost of the face recognition module is much higher than that of the fingerprint recognition module. Whether the product can be accepted by the public is worth considering. The other is battery life, as the unresolved problem in the face recognition industry, smart locks currently have no good solution.

Access Control System: Under the large system of smart communities, smart access control has become a standard in the community. Artificial intelligence + video surveillance can realize face recognition, vehicle analysis, video structuring algorithm to extract video content, detect moving targets, classify into a variety of target information such as personnel attributes, vehicle attributes, human body attributes, etc., combined with public security system, analyze criminal suspects clue. At the same time, artificial intelligence processing massive video and surveillance in the security field will also promote the performance improvement of artificial intelligence algorithms, and mature in other industries. In the smart community, the intelligent management system including smart access control, vehicle gates, parking locks and other functions can achieve the following scenarios: the real name of the mobile phone, the ID card, the access card binding, the ability to accurately identify the personnel, and effectively help the property management .

AI identification security system has been applied in the Pearl River Delta region of China. All relevant departments of Shenzhen City joined hands to launch the "Snow Bright" video project, which is to install security monitoring under the residents' buildings.And smart access card reader. At present, Shenzhen, Guangzhou, Zhongshan, Dongguan, Zhuhai, Foshan, as well as Hangzhou, Xiamen and other places are also launching the "Snow Bright" project.

AI vision technology widely empowers smart home items

Today, intelligent robots in the home can identify objects through image recognition technology and achieve follow-up to people. With an artificial intelligence system, it can tell which owner you are and can do some simple interaction. For example, if you detect an elderly person at home, it may measure blood pressure for you; if it is a child, it may tell you a story.

In addition, computer vision, gesture recognition and other interactive methods have become the auxiliary of voice interaction. Many manufacturers have introduced screen speakers, while smart TVs analyze video content through computer vision in addition to voice interaction. The next step in the content-related data, including short video clips, while watching and buying, such as the "spot" function of the Yi+ in the Tmall Box. For example, in a smart refrigerator, computer vision is used to analyze the food in the refrigerator, and the functions of user health management and online shopping are derived. A variety of interaction modes will be unified in the home life scene, thereby providing a more natural Interactive experience.

For women, the face recognition analysis function is more grounded. The mirror in the bathroom has the functions of smart makeup test, facial health analysis, etc. It can also record the user habits generated by the user during use, collect user preferences, and combine the e-commerce platform, as long as the consumer is satisfied with the effect of the test makeup. You can also buy it in the shopping cart with one click, and your favorite cosmetics will soon "fly" to the hands of consumers. The smart mirror can also be connected to the smart home system through the central control platform, which can realize the visual intercom function and control the switches of lights, sounds, curtains and air conditioners. It can be said that the mirror is one of the most interactive smart homes.

Talking about the development and innovation of AI vision technology

At present, many studies in the AI ​​field focus on the ability to analyze images from the visual system. Among them, artificial neural networks have become the most popular research field. Mathematical models such as the topology of the connections between neurons, the aggregate functions used, threshold functions, and backpropagation methods are all part of the field of artificial intelligence, which we call "deep learning" and are divided into two parts - training And reasoning. If the training is performed correctly, the neural network will provide an output response that is very similar to the input values ​​of the training data set. The inference engine is a software algorithm that corresponds to the simulation of deductive reasoning. The software is usually embedded in smart home devices.

In the past few years, deep learning has been very successful in the field of smart homes. Image-based technologies include facial recognition, iris and gesture monitoring, object and free space detection, and recent behavior recognition. It is predicted that by 2025, the AI ​​market will grow at a compound annual growth rate (CAGR) of 50%, with revenue mainly focused on the use of smart vision technology.

The development of artificial intelligence is also inseparable from the development of specialized hardware. It is worth noting that designers and builders of visual processors also provide software layers through embedded operating systems and/or SDKs (software development kits). This makes it easy to implement software solutions and allows hardware to get the most out of it, while also requiring platform-specific development skills that require tools such as Arm's embedOS, NVIDIA's Jetson, Xilinx's XSDK, and CEVA's CDNN.

Companies developing AI for embedded systems must consider this imposed software layer when developing their solutions and designing compatible hardware types.


As the momentum of AI continues to rise, the application of AI in intelligent vision systems presents a very bright future. On the hardware side, dedicated processors have emerged; in terms of software, there are increasingly powerful algorithms that recognize objects, faces and poses.

From the perspective of market application of AI, the first is smart home and smart security market; the second is mobile security system for personal identity authentication (unlocking, payment); finally, biometrics and its intelligence Applications in buildings and smart cities. There have been a lot of investment, acquisitions and partnerships in the AI ​​field, and the market will be quite large in the next few years, with both market and revenue growing rapidly.

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