Implementation of an Embedded System into the Internet of Robotic Things

Area of Science:

• Robotics
• Embedded Systems
• Industrial Internet of Things (IIoT)

Background:

• Industrial robots generate vast amounts of data crucial for performance optimization and maintenance.
• Integrating advanced sensing and processing capabilities directly onto robots is essential for real-time insights.
• The Industrial Internet of Things (IIoT) paradigm offers a framework for connecting and analyzing industrial assets.

Purpose of the Study:

• To present a case study of an embedded system for industrial robots.
• To demonstrate the benefits of such systems for monitoring robot behavior and long-term condition.
• To highlight the system's capability for collecting diverse environmental and operational data.

Main Methods:

• Development of a small, mobile, wireless embedded system with an advanced microcontroller.
• Direct integration of the system onto an industrial robot.
• Measurement of robot operational parameters, vibrations, and environmental factors (e.g., air pollution, humidity).
• Data transmission to a cloud platform for storage, processing, and analysis.

Main Results:

• The embedded system successfully collects critical data from industrial robots and their surroundings.
• The system provides insights into robot behavior and condition, enabling proactive maintenance.
• The wireless and mobile design ensures easy application to various industrial robots.
• Potential for expanded data collection, including environmental parameters, was demonstrated.

Conclusions:

• Embedded systems are vital for enhancing industrial robot capabilities within the IIoT.
• The proposed system offers a flexible and effective solution for real-time robot monitoring and data analysis.
• This technology facilitates improved operational efficiency, predictive maintenance, and a deeper understanding of robot performance in industrial settings.