Industrial Artificial Intelligence Technologies and Applications

Industrial edge AI is revolutionizing the manufacturing industry by enabling machines to make decisions during production processes using sensors and actuators. This allows for increased efficiency, reduced costs, and improved safety. Intelligent connectivity combines IIoT, wireless/cellular, and AI technologies to support new autonomous industrial applications. However, there are critical issues to consider when introducing AI to industrial IoT applications, such as training AI models at the edge, deploying AI-trained inferencing models on target edge hardware platforms, and benchmarking solutions compared to other implementations.

Format: Hardback
Length: 211 pages
Publication date: 11 September 2023
Publisher: River Publishers

The advancements in industrial edge artificial intelligence (AI) are revolutionizing the way industrial equipment and machines interact with the physical world, as well as with other machines and humans during manufacturing processes. These advancements enable Industrial Internet of Things (IIoT) and edge devices to make decisions during manufacturing processes through the use of sensors and actuators.

Digital transformation is reshaping the manufacturing industry, and industrial edge AI aims to harness the potential benefits of edge computing, including low latency times, reduced bandwidth, distributed architecture, improved trustworthiness, and more, alongside the transformative powers of AI. In industrial environments, the deployment of highly distributed intelligent industrial applications in remote sites that require reliable connectivity over wireless and cellular connections is possible. Intelligent connectivity combines IIoT, wireless/cellular, and AI technologies to support new autonomous industrial applications by enabling AI capabilities at the edge and allowing manufacturing companies to enhance operational efficiency, reduce risks, and cut costs for industrial applications.

When introducing AI to industrial IoT applications, several critical considerations must be taken into account, such as training AI models at the edge, deploying AI-trained inferencing models on target edge hardware platforms, and benchmarking solutions against other implementations.

Next-generation trustworthy industrial AI systems prioritize dependability in terms of their design, transparency, explainability, verifiability, and the implementation of standardized industrial solutions across various industrial sectors.

Furthermore, new AI techniques, such as federated learning, deep learning, and transfer learning, are being explored to enhance the capabilities and performance of industrial AI systems. These techniques enable the integration of data from multiple sources, the optimization of algorithms for specific tasks, and the development of more robust and accurate models.

In conclusion, the advancements in industrial edge AI are driving a transformative shift in the manufacturing industry, enabling manufacturers to achieve greater efficiency, productivity, and competitiveness. By leveraging the power of edge computing, AI, and intelligent connectivity, manufacturers can unlock new opportunities for innovation, growth, and success in the years to come.

Weight: 526g
Dimension: 162 x 241 x 19 (mm)
ISBN-13: 9788770227919