Applied Intelligence for Industry 4.0

This text discusses the use of text mining and IoT applications for monitoring and controlling smart industrial systems, as well as Big-data analytics, security, and optimization for industrial applications. It provides context-aware insights and human-centric industry, smart computing for the next-generation industry.

Format: Hardback
Length: 260 pages
Publication date: 11 January 2023
Publisher: Taylor & Francis Ltd

Text mining and Internet of Things (IoT) applications play a crucial role in monitoring and controlling smart industrial systems. This comprehensive guide delves into the key principles and techniques of big-data analytics, security, and optimization for industrial applications. By leveraging context-aware insights, human-centric industry, and smart computing, we can envision a future where next-generation industries thrive.

Big-data analytics encompasses a wide range of methods and technologies for extracting valuable insights from large and complex datasets. It involves techniques such as data mining, machine learning, and natural language processing to analyze and understand the patterns and trends within the data. In the context of industrial applications, big-data analytics helps manufacturers optimize their production processes, improve quality control, and identify potential bottlenecks.

Security is another critical aspect of IoT and industrial applications. With the increasing interconnectedness of devices and systems, there is a growing risk of cyberattacks and data breaches. Therefore, robust security measures must be in place to protect sensitive information and prevent unauthorized access. This includes encryption, authentication, and access control mechanisms, as well as regular security audits and monitoring.

Optimization is another key area of focus in industrial applications. By analyzing data and identifying inefficiencies, manufacturers can optimize their processes and reduce waste. This includes techniques such as supply chain management, inventory optimization, and energy management. Optimization not only improves efficiency but also reduces costs and enhances sustainability.

Context-aware insights are another important aspect of big-data analytics for industrial applications. By leveraging sensors and other IoT devices, manufacturers can gain real-time insights into the performance and behavior of their systems. This information can be used to optimize operations, predict maintenance needs, and improve safety.

Human-centric industry is a key concept in the development of smart industrial systems. It focuses on designing systems that are user-friendly, intuitive, and customizable. This includes the use of human-machine interfaces, voice recognition, and natural language processing to enhance the interaction between humans and machines. Human-centric industry not only improves productivity but also enhances safety and job satisfaction.

Smart computing is a fundamental technology that enables the development of smart industrial systems. It involves the use of advanced computing technologies, such as artificial intelligence, machine learning, and cloud computing, to enable the automation and optimization of industrial processes. Smart computing not only improves efficiency but also enhances safety and reduces costs.

In conclusion, text mining and IoT applications play a crucial role in monitoring and controlling smart industrial systems. Big-data analytics, security, and optimization are key principles and techniques that enable manufacturers to optimize their production processes, improve quality control, and identify potential bottlenecks. By leveraging context-aware insights, human-centric industry, and smart computing, we can envision a future where next-generation industries thrive.

Weight: 670g
Dimension: 254 x 178 (mm)
ISBN-13: 9781032164151