NEXT-SYSTEM Releases New Guide Video for Fall Detection with VP-Motion
Fukuoka, Japan — May 30—NEXT-SYSTEM Co., Ltd. has released a new video guide demonstrating how to automatically detect falls using its AI Behavior Analysis System, VP-Motion.
As workplace safety remains a top priority, many companies have adopted AI-based solutions to help prevent accidents especially in factories. While VP-Motion has been introduced to support this effort, some users have found it challenging to understand how to fully utilize the system after installation. To address this, NEXT-SYSTEM has created a new guide video focusing on fall detection, one of the behaviors most commonly linked to workplace accidents.
“This guide video offers a clear example of how VP-Motion can be effectively used in such situations. I believe it will help companies improve safety and overcome challenges after they begin using VP-Motion.”says Tabira, leader of the Design Department at NEXT-SYSTEM.
This video is designed to help resolve issues that may arise after product implementation.
VP-Motion is designed to automatically recognize predefined actions from video footage using AI trained with user-defined behavioral data. This guide focuses specifically on fall detection, offering viewers a clear, step-by-step explanation of the system’s features and how to set it up for real-world applications.
About VP-Motion
VP-Motion is an AI-powered application that analyzes and recognizes human behaviors in video footage. Users can train the integrated AI to detect a wide range of action patterns, allowing the system to improve its recognition accuracy over time.
Ideal for detecting operational mistakes, suspicious activity, and falls, VP-Motion supports the development of intelligent monitoring systems aimed at improving both safety and workplace efficiency.
System Overview
VP-Motion is composed of two main components—one for AI training and another for real-time detection and monitoring. Each component comes with its own dedicated application, allowing responsibilities to be divided easily among team members. For example, engineers can handle AI training, while supervisors manage on-site monitoring.
VP-Motion Annotator
Used to label specific actions within video footage, Annotator lets users define action categories and apply them to individuals within a scene. These labeled segments become the foundation for the AI’s training data.
VP-Motion Trainer
Trainer enhances the system’s recognition abilities by introducing variations in training data—especially helpful for learning different types of falls. It also allows users to evaluate performance and select the most accurate models.
VP-Motion Monitor
Monitor is where the action happens in real time. Users can fine-tune detection thresholds and connect the system to external devices, enabling automated alerts when a fall is detected.
This newly released guide video provides an accessible starting point for anyone looking to implement fall detection using VP-Motion. With its customizable training features and real-time monitoring capabilities, VP-Motion offers a practical and scalable solution for safety-focused environments.
For more details and product information, visit the official VP-Motion website.