system

JP2026104441APending Publication Date: 2026-06-25SOFTBANK GROUP CORP
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Patent Information

Authority / Receiving Office
JP · JP
Patent Type
Applications
Current Assignee / Owner
SOFTBANK GROUP CORP
Filing Date
2024-12-13
Publication Date
2026-06-25

AI Technical Summary

Benefits of technology

【0005】 本発明は、映像取得装置から取得した映像をリアルタイムで解析する人工知能モジュールを備え、該モジュールによって、不審人物や不審行動を検知するシステムを提供するものである。本システムは、検知結果に基づき音声警告を発する指令を生成し、これにより現場に警告音を出力する。また、検知された情報は即時に利用者に送信され、リアルタイムでの状況確認を可能とするため、迅速な対応が可能である。この結果、犯罪行為の発生を未然に防ぐ効果を高め、安全性を向上させることができる。

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Abstract

We provide the system. [Solution] A means of acquiring real-time video from a video acquisition device, The system includes a machine learning module for analyzing the acquired video, and the module has means for detecting abnormal behavior patterns. A means for generating a command to emit a warning sound based on the detection of the abnormal behavior, means for outputting a sound based on the aforementioned warning sound command, Means for transmitting the detected information to an information terminal, The aforementioned information terminal includes means for viewing live video and remotely controlling audio warnings, A system that includes this.
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Claims

1. A means of acquiring real-time video from a video acquisition device, The system includes a machine learning module for analyzing the acquired video, and the module has means for detecting abnormal behavior patterns. A means for generating a command to emit a warning sound based on the detection of the abnormal behavior, means for outputting a sound based on the aforementioned warning sound command, Means for transmitting the detected information to an information terminal, The aforementioned information terminal includes means for viewing live video and remotely controlling audio warnings, A system that includes this.

2. The system according to claim 1, characterized in that the information transmitted to the information terminal includes an access link to real-time video.

3. The system according to claim 1, characterized in that the machine learning module detects abnormal behavior using motion pattern analysis and biorecognition technology.