The development of smart sensors can be a high degree of integration of mechanical, electrical, software/firmware, circuit, and sensor knowledge.

With the rapid development of the automotive industry in smart driving, safety assistance, automotive electronics, and human-machine interface-related technologies, the integration of virtual and real superimposed displays, driver monitoring systems (DMS), interactive functions, Internet of Things (IoT) of the smart cockpit system have become the current trend.

To realize the smart city of the future, it is indispensable to build a safer and more efficient traffic environment, and smart vehicles with networking and various advanced functions are the key.

In recent years, smart door lock technology has developed rapidly. As an important part of smart home access control, the smart lock market will grow substantially in the next few years.

Artificial Intelligence, Machine Learning, Deep Learning, and Big Data are topics that have been frequently discussed recently. These technologies are used in many fields, including the financial industry, logistics industry, business analysis, unmanned vehicles, computer vision, natural language processing, etc., and have spread in every corner of life.

Artificial intelligence has brought in a new generation of robotics technology: Robotics 2.0. The principal challenge is the transformation from original manual programming methods to true autonomous learning. Faced with this challenge for innovation in AI robotics, how can Taiwan's manufacturing industry best seize the opportunity?

Information is power. Information can not only adjust decision-making but also help discover market opportunities. Use advanced motion control technology to optimize the performance of automated machines.

The development of smart sensors can be a high degree of integration of mechanical, electrical, software/firmware, circuit, and sensor knowledge.

By embedding dynamic force sensors in the machine and matching them with analysis software, it provides an intelligent solution for the machine. Expand the scope of application, increase production capacity and reduce waste in the customer's manufacturing process, thereby reducing energy consumption and moving towards energy saving and waste reduction.

"Efficiency" is the most important key in the pursuit of success in the manufacturing process and the entire industry.

Nowadays, the traditional industry combines the technology of the Internet of Things, towards the innovation of Industry 4.0 and the development of intelligent manufacturing.

In the trend of industrial automation, motion control is a key part of it. Automating operations through machines can avoid a lot of human error, and can also speed up production efficiency and efficiency. How to make the machine act according to the command is the application category of machine motion control.

Additive manufacturing is playing an increasingly important role in the manufacturing industry and is mainly used in toolmaking and prototype construction.

5G is recognized as a key enabler of Industry 4.0. With its high network speed and low power consumption, 5G facilitates the connectivity of every sensor in the upcoming unmanned factory to the cloud. This connectivity allows for the extraction of data for analysis, ultimately fueling advancements in artificial intelligence.

Recently, there has been widespread discussion about Artificial Intelligence, Machine Learning, Deep Learning, and Big Data. These technologies find application in various domains such as the financial industry, logistics, business analysis, unmanned vehicles, computer vision, natural language processing, and more, permeating every facet of daily life.

In recent years, developed nations have initiated comprehensive power grid upgrade initiatives. In line with its commitment to energy conservation and carbon reduction policies, Taiwan has advanced the implementation of Automated Metering Infrastructure (AMI) as part of its national energy-saving strategy. The plan encompasses the integration of 4G/5G and other communication industries. The noteworthy progress in the development and integration of smart grid applications with 5G communication technology represents a significant industrial advancement deserving of attention.

The behavior of robots is frequently modeled as a computational graph, wherein data flows from sensors to computational technology, extending to actuators and then looping back. To enhance performance capabilities, robotic computing platforms need to adeptly map these graph-like structures to CPUs and specialized hardware, such as FPGAs and GPUs.

The conventional manufacturing sector stands at a crossroads necessitating a shift towards intelligent transformation. By incorporating advanced production technologies, a new era of industrial development is inaugurated.