With the evolution of human–robot collaboration in advanced manufacturing, multisensor integration has increasingly become a critical component for ensuring safety during human–robot interactions. Given the disparities in range scales, densities, ...

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• A method for sensor fusion in human–robot environment is proposed.
• A coarse localization algorithm is proposed to address point cloud scale differences.
• An improved FPFH algorithm based on overlap ratio for coarse registration.

Inadequate training poses a significant risk of injury among young firefighters. Although Human Activity Recognition (HAR) algorithms have shown potential in monitoring and evaluating performance, most existing studies focus on daily activities ...

• A novel multimodal sensor data fusion for firefighting activity recognition.
• Hybrid fusion models with inertial and sEMG data from multiple positions.
• Wearable sensors integrated into lightweight and custom-designed devices.
• ...

The present research develops a framework to refine the classification of an individual’s activities and recognize wellness associated with their routine. The framework improves the accuracy of the classification of routine activities of a person,...

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• IoMT seamlessly integrates multimodal sensors, revolutionizing healthcare through real-time ADL monitoring.
• Multimodal ADL data fusion provides comprehensive insights into elderly living patterns and events.
• AI algorithms enable ...

The micro-electro-mechanical technology facilitates the development of low-cost orientation estimation solutions using inertial and magnetic sensors. However, the magnetic disturbances challenge the robust pitch and roll measurements ...

• Analyzing the coupling reason for magnetic information affecting roll and pitch.