Application of Sensors Technologies and Embedded Artificial Intelligence in Industrial Field
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".
Deadline for manuscript submissions: 15 January 2025 | Viewed by 788
Special Issue Editor
Interests: embedded system; deep learning; signal processing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Embedded artificial intelligence (AI) is increasingly being used in various industrial applications to improve efficiency, productivity, and decision-making processes. This Special Issue mainly focuses on:
- Predictive Maintenance: AI algorithms are used to constantly monitor and analyze data from sensors embedded in machinery. This allows for the early detection of potential failures or equipment malfunctions, enabling timely maintenance and minimizing downtime.
- Quality Control: Embedded AI algorithms can analyze images or sensor data in real-time to identify defects or anomalies in production processes, which helps in ensuring high-quality standards are met, reducing waste, and improving customer satisfaction.
- Robotics and Automation: AI-powered robots and autonomous systems are increasingly being used in industrial environments. These systems can perform complex tasks, adapt to changing conditions, and learn from their experiences, leading to improved efficiency, safety, and productivity.
- Energy Management: AI algorithms can analyze energy consumption patterns and optimize energy usage in industrial facilities. This helps in reducing energy costs, identifying areas of inefficiency, and implementing energy-saving measures.
- Process Optimization: AI techniques, such as machine learning, can be used to analyze large volumes of data collected from various sensors and systems to identify bottlenecks, optimize workflows, and improve overall process efficiency.
- Fault Detection and Diagnosis: Embedded AI systems can analyze sensor data and patterns to detect and diagnose faults or anomalies in industrial equipment or processes. This helps in addressing issues promptly, reducing downtime, and preventing costly breakdowns.
Overall, embedded AI enables real-time decision making, automation, and optimization, leading to improved productivity, cost savings, and operational efficiency.
Dr. Hao Luo
Guest Editor
Manuscript Submission Information
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