In recent years, the changes in the IT market have been fast and large, and there have been subversive technologies impacting the market, including cloud computing, Internet of Things, big data, and every new technology and new concept has brought destructive innovation to the technology industry. In the face of these new shocks, whether it is a single product or an overall structure, it must be adjusted at any time in response to new industry trends, especially another wave of AI that will emerge in 2017, and will be integrated with the existing Internet of Things as AIOT. Becoming a new generation of IT mainstream, but Zhou Xinxu, deputy general manager of Dalian Dapinjia Group Technical Support Center, believes that the current IoT architecture needs AI functions, and still has no grasp, including bandwidth, computing power, and security. The challenges that the IoT system will encounter when running, Zhou Xinxu pointed out: "Edge CompuTIng will be the answer to the future of AIOT." The Internet of Things is the first to capture data from the first layer of sensing network, and then send the data to the cloud platform for storage and calculation, and then optimize the analysis. Zhou Xinxu pointed out that the computing quality of the back-end platform is in addition to the processor itself. In addition to the ability, the amount of data sent back by the sensing network is also the key. "After all, the huge amount of data can accumulate enough sample numbers, and the AI's computing results are accurate enough." But with a lot of data comes the bandwidth problem. "Now the bandwidth of communication technology is big enough. It is not a problem to transmit a large amount of data. The problem is that broadband design is costly when the system is built and operated." The second problem of AIoT is computing power. The current IoT system is operated by the upper-level cloud platform. For systems with few sensing and control nodes, this centralized computing method is a better choice, but Zhou Xinxu It is pointed out that if the number of nodes is large enough, the computing power of the cloud platform may not be able to load high-volume operations. "And even if it can load, the whole system will run slower," especially most of them are equipped with AI. The system, the requirements for real-time performance is quite high, once the speed is slow, the system performance will be greatly reduced. To solve the problem of bandwidth and operation, Zhou Xinxu said that it is necessary to start from the enhancement of terminal equipment. "The practice of edge computing is to make the terminal equipment of the Internet of Things system have a certain degree of computing power." The data is first processed in the terminal device, and then processed. After that, the data is transmitted to the upper-level cloud platform. "In short, the data received by the cloud is processed and processed first, so that the quantity is not only less, but the content is also more accurate, so that the work can of course be faster and the burden is also In addition to pre-processing data, some simple tasks can be directly performed by the controller directly after the front-end operation, without having to be commanded by the cloud platform to make the system react more real-time. "As for the field of application of edge computing, Chen Hongji, director of the technical support department of Da Lian Da Pin Jia Group in Taiwan, said that there are many types of nodes such as smart city, augmented reality (AR), M2M, smart home, and intelligent manufacturing. For real-time demand, target applications, such as intelligently manufactured machine vision systems, can achieve real-time requirements through edge computing." Chen Hongji further pointed out: "In the future AIOT system, cloud platform and edge The computing operations of the equipment will be divided, the cloud is responsible for long-term decision analysis, and the work of high real-time requirements is handled by the terminal equipment." In this regard, whether it is computing power or bandwidth, edge computing is the best design method currently seen by AIOT, but Chen Hongji said that edge computing is a new design concept, which will be a big challenge for development engineers. Now, there are manufacturers to launch AI related development kits, such as Google's AIY Projects, which allows interested parties to DIY their own AI artificial intelligence products. Currently, the new generation of AIY processors use NXP (NXP). .MX 8M, "Google's choice of i.MX 8M is mainly optimistic about the processing power of this chip in voice, video and audio, coupled with his high compatibility and low power consumption features, all allow limited resources of makers or new Entrepreneurs are very useful." In addition to scalability and compatibility, Chen Hongji pointed out that the security design is also an important requirement of the Internet of Things chip. In the early stage of development, the security of the Internet of Things was not taken seriously, but it has become the design focus in recent years. "The IoT products that come out now will emphasize that they have a security design, but it is not easy to be complete." Chen Hongji takes NXP's IoT processing chip as an example. NXP has built a protection mechanism in the process. Through HSM certification, general engineers can not see the internal public and private keys through physical means, and NXP also has a random random number password design, which greatly enhances the security level of the Internet of Things. Chen Hongji said that the cooperation between the IoT design and the component supply of the Internet of Things is quite large. The experienced partners can help the equipment industry to shorten the development time. He takes the Dalian Lianjia Group as an example. Experience in the technology industry is very rich, and these experiences can help customers quickly identify their own needs, and at the same time propose appropriate component recommendations for their needs, speeding time-to-market." For the future application development of AI, Chen Junyi, senior manager of the product department of Dalian Lianjia Group, believes that it will move to a specific system in a specific field. Now every industry has a very deep professional, so the functions of the AIOT system required by each are different. "As for e-commerce platforms to strengthen security and localization services, ADAS has high requirements for reliability and low latency. Engineers must find suitable chips and solutions to meet these different needs." "From the current overall industry development point of view, there are already a large number of manufacturers in the market actively investing in AI research and development," so Zhou Xinxu is quite optimistic about the future, especially the edge computing. The latest research report can be seen, IDC pointed out that in 2022, the world In the IoT system, 43% will be in the terminal equipment, and the IEK also said that from 2017 to 2022, the edge computing will grow by 10.7% per year, which shows the future development potential. Zhou Xinxu Finally, it is pointed out that the development of AI is not to replace human beings, but to assist humans in the more intelligent processing. He uses the application of NXP products represented by the Grand Alliance Group in mainland China as an example. Now the smart homes in mainland China are very prosperous, NXP It is built into many home appliances, such as ovens, air conditioners, and even showerheads. As an intelligent voice control, "these products are already available, and the market response is very good. From these applications, you can see the edge."
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