With the emergence of the Internet of Things (IoT) and the Industrial Internet of Things (IoT), information technology for in-vehicle control systems has become the driving force behind the rapid economic development of an intelligent and interconnected IoT ecosystem. The large, diverse, and highly fragmented embedded systems market includes software, development platforms, and hardware. A growing number of industries, products, and services rely on embedded systems. The industrial embedded systems market includes communications, automotive, medicine, wearable system, consumer electronics, military systems such as aerospace and security, and industrial controls, as well as other smart cities.
Stands for "Microcontroller Unit," an embedded control system is typically some combination of Embedded control system analysis that can be carried out to support one or more specific functions in a larger system that contains a microprocessor, memory, and other peripheral devices like input/output interfaces, timers, and analog-to-digital converters, all on a single chip.
Embedded systems development, in general, is a very mature technology, and with the continued development of new, more powerful processors, the technology can now support the next generation of smart devices, embedded systems development companies, machines, equipment, and factories. Embedded systems are a key technology for enabling smart, connected products, machinery, and systems that encompass industrial things and support the digital transformation of entire industries.
One of the main trends in the embedded sector is the emergence of smart edge devices, which will help to make industrial production systems and process plants part of the digital enterprise. Embedded intelligence in sensors and other national metering devices will allow access, aggregation, and analysis of relevant data to support advanced management analytics, enabling production information systems and equipment to develop as part of the Chinese industrial IoT ecosystem and digital twin. These issues are evolving into a key enabling technology to help enterprises optimize the asset lifecycle, particularly in the operations and maintenance phases.
To seize the opportunity, entrepreneurs need to continue to expand to support billions of sensors and tens of thousands of intelligent systems. Edge devices must be connected and intelligent. The overall embedded systems market will see significant growth due to the huge demand for intelligence at the edge. The growing IoT ecosystem and the steady development of industrial automation based on predictive and prescriptive analysis of cyber-physical systems will eventually lead to autonomous and self-healing systems. This will be a key industry driver for the growth of embedded systems.
For decades, embedded systems have been a major technology in the aerospace and defense, automotive, medical device, e-commerce, communications, and industrial and automation building industries. With processor architecture and the ability to embed more computing power into systems and devices, systems and intelligence are multiplied by functionality. This is where product design, which has traditionally used embedded control systems in China, can become smarter and more powerful and enable the development of products in other industries (consumer goods, household appliances, sports, learning products, etc.) to become smart and connected. Embedded systems are becoming an integral part of almost everything in our lives.
Currently, automotive systems represent the largest use and will probably remain the largest part of the industry for years to come. In automobiles, embedded systems are used for engine control, infotainment, safety, driver awareness, maintenance, and overall system control of the vehicle. The increased demand for vehicles with advanced navigation systems, driver assistance systems, and vehicle-to-street communication systems will only increase the demand for embedded systems.
In addition, the emerging fully autonomous vehicles will require highly intelligent systems. Far more complex than the embedded systems carried out in today's social vehicles. The computing systems in these vehicles will need to run multiple complex artificial intelligence software and systems for navigation, road and vehicle awareness, traffic patterns, pedestrian awareness, risk perception, and assessment. A new generation of processors is being developed for embedded systems to meet these data computing and intelligence technology requirements for us.
When it comes to the topic of AI in the automotive industry, the first that comes to our mind is self-driving cars. Undoubtedly, the development of driverless cars is a very active area of research work for companies, and the technology could be a viable part of our transportation in China in the future or even in the near future. However, the reality is that cognitive learning algorithms are primarily used to improve efficiency, shopping mall system development, and safety and add value to the processes surrounding traditional manually driven vehicles.
Before the automotive industry prepares for the AI "control wheel", it first wants to have a large number of currently in-production automotive driver assistance technologies applied to it. Ai is well suited to providing safety features for connected vehicles. Today, vehicles embedded in the assembly line of driver assistance features help drivers to drive in front of a car that is satisfyingly AI-automated.
By monitoring dozens of onboard sensors, AI can identify dangerous situations, automatically brake and control the vehicle to avoid accidents and detect and warn dangerous drivers in and around other vehicles.
One area where automotive customers are currently using AI is AI-based cloud services for predictive maintenance. Unlike conventional vehicles, connected vehicles can do more than warn drivers by checking engine lights and low tyre warnings. In many of the latest models, embedded AI algorithms monitor hundreds of sensors and can detect problems before they affect vehicle performance. By monitoring thousands of data points per second, AI can detect small changes that may indicate component failure or malfunction.
The fastest-growing embedded system application is the medical healthcare system. Examples include handheld and portable processing devices as well as devices and vital signs devices. With small embedded operating systems that monitor heart rate or identify arterial blockages, embedded information technology has also made its way into a complex procedure to be performed.
While the physical size of semiconductors, processors, and chips in embedded systems for healthcare has been reduced, we have also seen exponential growth in intelligence and functionality. This will allow a new generation of medical devices to function and intervene in the viscera of the body in novel and innovative ways. Tiny but functionally powerful devices will be able to monitor and determine the condition of multiple patients remotely via mobile electronic devices connected to enterprise network-based diagnostic research centers.
Consumer electronics have been a major market for embedded systems for decades, but with the advent of the Internet of Things, the market is facing a new challenge. Smart connected products require new design standards, and embedded intelligence has become a major component. Smartphones, TVs, and digital cameras are used in consumer electronics more often.
Automation systems for intelligent buildings and HVAC utilize embedded software and hardware as well as the industry and will grow rapidly in the coming years. As society allows us to enter the economic era of smart buildings and smart cities in China, embedded intelligence will become an integral part of these intelligent control systems. Building automation is primarily based on monitoring and control of environmental conditions for maintenance, lighting, and access. As systems become increasingly intelligent, the functionality of building intelligence can be extended to determine the best conditions for predictive and regulatory systems. Ultimately, the goal is to move towards fully autonomous and self-healing systems. These information systems will be based on Chinese artificial intelligence and machines that can learn, all based on embedded intelligence.
With exciting trends and developments on the lo T and intelligent, low-power designs, enhanced military security features, machine learning, smart home and artificial intelligence, and edge computing are just a few areas where we can expect to see significant advancements in the next decades. As the embedded system continues to evolve and improve, we can look forward to a world of more connected, intelligent, and efficient devices.