NanoMQ is an open-source edge computing project released in early 2021, designed as a next-generation lightweight and high-performance MQTT message server for IoT edge computing scenarios. In the IoT era, data is the primary productive force, and the edge is where data is generated. Quickly aggregating and distributing data in complex edge network environments is … Read more
1968 Dick Morley invented the Programmable Logic Controller (PLC) and began deploying them in the automatic transmission manufacturing at General Motors, marking the era of precise control by controllers in various production stages of the manufacturing chain. 1975 Honeywell and Yokogawa Electric launched the world’s first Distributed Control Systems (DCS) TDC2000 and CENTUM, which allowed … Read more
Good season of the beginning of autumn，but Mr. Zhang from the air compressor factory is not happy at all，as the scale of the factory expands，the need for manpower is increasing，finding an experienced technician is really difficult these days！ While Mr. Zhang is at a loss, his son Xiao Zhang came up with a good idea, … Read more
Hello everyone, today I’m going to take you to explore a super interesting field – TinyML! Are you still worried about insufficient computing power of devices? Or are you concerned that AI models are too large to run? TinyML was born to solve these problems. It can make AI models lightweight, make smart devices smarter, … Read more
Editor’s Note: The author, Jose Vicente Sáez Ibáñez, is a senior ML and software development engineer with international experience. He has been dedicated to researching the intersection of artificial intelligence and the Internet of Things (AIoT). Over the past few years, he has been deeply involved in the smart city industry across China, Spain, and … Read more
Author: Wu Nü Wang (Peng Zhao) IoT Think Tank Original Reprint must indicate the source and origin Introduction The most widely distributed IoT devices are often very small and have limited power. They serve as terminal hardware, collecting various data through embedded sensors; their computing power is limited and extremely sensitive to power consumption. Can … Read more
AI chips can be categorized based on their application scenarios into cloud AI training and inference, edge AI inference, and terminal AI inference. In our article on the Top 10 Domestic AI Chips, we listed the cloud AI training and inference chips from 10 domestic AI chip companies. This article will focus on edge and … Read more
According to reports from Electronic Enthusiasts (Written by Li Wanwan), in the era of artificial intelligence, more and more AI applications need to extend from the cloud to the edge, such as smart headphones, smart cameras, smart bracelets, logistics robots, etc. Deploying AI at the edge has become a trend. With the rapid development of … Read more
▲Click above Lei Feng Network Follow Zhang Yongqian stated that the contradiction between the data generated at the edge and the limited processing capacity of the backbone network is becoming increasingly prominent. To solve this contradiction, a combination of cloud, edge, and terminal is essential. Written by | Bao Yonggang The integration of AIoT is … Read more
Author | Li Xiangjing Editor | Wu Chunqiu Source | Zhidin Technology At the hardware level, NVIDIA has proposed the Jetson product family, creating a leading edge AI platform. Meanwhile, at the software level, NVIDIA has also launched the NVIDIA TAO Toolkit and Metropolis SDK to help enterprises accelerate the creation, deployment, and expansion of … Read more