Due to the pandemic, the need for more effective business procedures, as well as significant developments in the Internet of Things, 5G, and AI itself. The year 2021 saw a major increase in the demand for edge computing and edge AI. Last year, the development of edge AI grew significantly, allowing many manufacturers, businesses, and developers to enhance edge computing.
Business units have traditionally been responsible for managing edge solutions, but this role is moving to IT, and businesses are using IT resources to save costs. IT departments will use cloud-native technology to handle the edge computing concerns relating to management, security, and scaling. The most effective solution for managing large-scale edge AI applications has emerged as Kubernetes, a platform for containerized microservices.
Embedded systems have developed a certain level of "smartness" during the previous few years. Every month, a growing number of smart devices are introduced. At this stage, extremely primitive forms of artificial intelligence have already made their way into embedded technology. Smart home lighting systems, for instance, can be programmed to switch on and off depending on who is in the room. The system doesn't seem particularly attractive at first glance. But when you give it some thought, you see that the system is acting independently. The microcontroller/SOC determines whether to turn on the light based on the sensor's input. This embedded system AI is very primitive, isn't it?
There are plenty more instances of basic AI in embedded systems. What about the future, though? Will we have embedded AI systems that can perform human workers' tasks in their entirety? It appears that these systems are already under development.
So, let's look at how the interaction and development of embedded systems with AI.
Edge AI has a wide range of uses and is not exclusive to one industry. Facial recognition, object detection, proximity detection, and other functions are currently employed in self-driving cars, security cameras, smartwatches, smartphones, robotics, smart speakers, video games, and other devices.
Even though Edge AI is a relatively new technology, all the businesses are rushing to implement it. Edge AI will have certain practical applications, such as the following:
- Real-time detection and categorization, video analytics, computer vision, and other aspects of smart AI vision.
- Applications for smart energy include smart solar systems, smart grids, smart meters, and wind farms.
- Applications for AI in healthcare include remote surgery and diagnostics, patient vital sign monitoring, intelligent tracking devices, etc.
- Virtual reality, augmented reality, mixed reality, video streaming devices, etc. are all used in the entertainment sector.
- Applications for smart factories include gadgets for tracking productivity and safety, movement within the facility, etc.
- Intelligent transportation systems, such as automated trains, self-driving autos, etc.
This webinar is designed to bring together IIoT, Artificial Intelligence, and Industrial manufacturing subject matter experts from all around the world especially between India and Taiwan to share insights, product releases, and upcoming technological trends. Through the webinar, we expect to connect and discuss business opportunities and also learn from our industry experts.
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