In the next generation technological revolution, the Internet of Things, who will play the role of “vanguard”?

The Internet of Things (IoT) is widely regarded by the industry as the next technological revolution after the Internet, and is said to be the dawn of a new era of wearable devices, smart homes, self-driving bikes, smart factories, smart cities, and more.

The Internet of Things (IoT) means the Internet and the interconnection of all things with accessible devices. It combines the potential advantages of the industry: cheap and widely available bandwidth, low-energy microprocessors, and big data analysis tools. The development and growth of the IoT is closely related to two key technologies: edge computing and machine learning.

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The continued evolution of edge computing

The number of IoT access endpoints, such as connected devices, sensors, and gateways, is growing exponentially. IT industry analyst Gartner predicts that the growth rate of IoT terminals will be about 30%, and the total number of IoT access devices will reach 20 billion by 2020. The explosion of access devices has brought new challenges to data analysis and data processing. These terminal devices will generate a large amount of data. If this data is transferred to the cloud for data management, analysis, and decision-making, it will not only be expensive and inefficient, but it may also hinder the development of network infrastructure, resulting in network latency issues.

Therefore, edge computing and edge analytics are playing an increasingly prominent role in large-scale IoT deployments. In edge computing, computing power is decentralized and closest to sensors and devices. The data of devices comes from the edge of the network, and the data analysis and processing work is completed at the edge of the network, rather than on a centralized server or cloud.

Its advantages include: the ability to effectively support real-time applications and a reduced burden on infrastructure because most of the data is processed at the edge network and only necessary data is sent to the cloud for further processing and storage.

This does not mean that edge computing will conflict with traditional data centers and cloud computing. On the contrary, edge computing is more likely to coexist with cloud computing to distribute computing power and workloads to where it makes the most sense. Sensor data will be collected and processed on the edge gateway, and edge analysis can use rule-based algorithms. Filtered data can be sent to the cloud, aggregated with data from other sources, and then fed back to the cloud's analysis engine to generate a model that can be sent back to edge analysis.

Machine Learning

With the rise of the Internet of Things, a technology that can form a good complement to edge computing is machine learning. Often mentioned together with artificial intelligence, machine learning refers to the method of generating automatic analytical models that do not need to be explicitly programmed by humans. Although the knowledge of machine learning has been available for decades, it is only in recent years that the development of computing power has been able to meet the needs of machine learning.

As computing power gets better, machine learning will be increasingly integrated into IT architecture, especially in cloud and edge computing. Machine learning can not only centralize analytical functions in the cloud, but also greatly improve the efficiency of edge analysis.

With the development of IoT adoption and the explosion of data, edge computing and machine learning will play a key role in the future IoT architecture. The three major public cloud service providers AWS, Microsoft and Google are all committed to integrating edge computing and machine learning into their products, providing machine learning as a service on their cloud platforms. AWS and Microsoft have already launched related edge computing software, which can run on chip vendors' systems (SOC) or on edge gateways.

As with all new technologies, only time will tell how these technologies will play out, but one thing is clear: the era of the Internet of Things is coming, and edge computing and machine learning are two essential protagonists of the Internet of Things era.