Four predictions about the future of AIoT

The intelligent Internet of Things technology integrates AI technology and IoT technology, generates and collects massive amounts of data through the Internet of Things, and stores them in the cloud and at the edge. Then, through big data analysis and higher forms of artificial intelligence, all things are digitized and intelligently connected.
Smart IoT applications that are convenient, time-saving, cheap and safe will soon be implemented in areas closely related to people’s lives, such as the popularization of homes, shopping/consumption, transportation, medical care, factories, disaster prevention, etc. will completely change people’s lives. life. Telecommunications, consumer, retail, business services, healthcare, automobiles, law, public sector, insurance, etc. are the main business scenarios for future AIoT applications.
Domestic industry giants have long been eyeing the "big cake" of AIoT, and Internet companies, smart manufacturers, and security vendors have begun to cross-border and transform. In 2017, Alibaba proposed the "All Things Awakening Plan"; Huawei launched the Huawei Smart Choice for AIoT's two major platforms, HiAI and HiLink; at the JD IoT strategy conference, the brand-new brand "Jingyuzuo" was launched to fully increase the AIoT; *Except for autonomous driving , It also started the deep cultivation of AIoT security field first. The giants integrate core technologies such as "artificial intelligence + Internet of things + big data" to achieve cloud-to-cloud docking, open up multiple platforms, and empower the intelligent Internet of things.
The application prospect of AIoT technology is very bright, and its development trend mainly includes the following aspects.
1. The popularity of multi-dimensional heterogeneous sensors. Sensors are also called "electronic facial features" and are the core of the entire AIoT device information collection. At present, the global sensors have eight sensitive categories including sound, force, light, magnetism, air, temperature and humidity, RFID, and biology, and there are about 31,000 types of components, of which there are about 22,000 in China. In this new* epidemic detection field, there are more than 130 product types such as non-contact thermometers, blood pressure, blood lipids, blood oxygen, pulse, and carbon dioxide gas. Based on the development of MEMS process technology, sensor data can be processed on a very small chip, which will accelerate the cost and miniaturization. At the same time, the use of new materials will bring about a sensor revolution, and countless new sensitive components will emerge that can obtain multi-dimensional heterogeneous data.
2. NB-IoT will become popular. AIoT with front-end edge computing capabilities makes it possible to seamlessly switch backhaul applications of small data packets and high bandwidth. NB-IoT will promote the traditional evolution path of "from scenario to algorithm, from algorithm to architecture" to a perfect exchange. change.
3. AIoT chips dominate*. AI reasoning at the edge requires a lot of calculations. Heterogeneous fusion chips with advantages in low energy consumption, low cost, and parallel computing will greatly increase computing power and add neuronal synapses to IoT devices. It is an excellent hardware combination for embedded IoT and AI applications and will lead The second revolution of intelligent IoT equipment.
4. Rapid iteration of machine learning technology. In all current mainstream neural network models (including AlexNet, GoogleNet, ResNet, VGG, Faster-RCNN, Yolo, SSD, FCN and SegNet) and layer types (including convolution and deconvolution, expansion, FC, pooling and deconvolution) In addition to pooling, various normalization layers and activation functions, tensor reshaping, element-wise operations, RNN and LSTM functions), new neural networks and new layers that are more advanced and easier to use will be quickly iterated.
If the B2B application scenarios where AIoT is most likely to generate value are carefully identified, and the market granularity is large enough and can be kept away from fragmentation, there are only two areas where value is most likely to be generated: autonomous driving and visual Internet of Things.
With the maturity of deep learning, it will bring about a violent chemical reaction between the Internet of Animals and artificial intelligence, and traditional industries are accelerating their transformation to the Internet of Smart Things. Visual IoT is one of the most important data portals in the future of the Internet of Things. The ability to use visual data in the era of intelligent IoT will also be greatly improved. It can not only enhance the ability to restore three-dimensional information, but also create greater value based on visual big data. The development trend of intelligent IoT platformization will also break the industry barriers of "fragmentation" in the IoT industry.

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