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GithubSingTown Technology基於OpenMV嘅AI智能相機系統,可以應用於大型自動駕駛車輛,用於識別鋪設喺地面嘅高壓電纜位置並自動規劃行駛路線。透過機器視覺同圖像識別算法,該系統能夠喺不平坦嘅地面環境中準確檢測電纜路徑,令車輛能夠沿住電纜自動組織或進行維護,實現智能、低功耗嘅自主導航同操作控制。

In large engineering vehicles, mining area transport vehicles, and automated maintenance operations, ground cable management is a tedious and high-risk task. SingTown Technology's AI smart camera solution, based on the OpenMV platform, integrates machine vision and image recognition technology to achieve automatic identification and path following of high-voltage cables on the ground.
This embedded vision solution captures real-time images of the ground ahead of the vehicle via a camera. Its on-device AI algorithm accurately identifies the position and direction of cables by analysing colour, texture, and edge features. The system operates stably under complex lighting conditions, uneven terrain, and environments with obstacles such as stones or pits, automatically filtering background interference and dynamically correcting the recognition path.
Once the cable trajectory is determined, the vehicle's navigation system can adjust its direction and speed in real time based on the recognition results, automatically moving along the cable to achieve integrated "recognition-following-organization" operations. Users can also customise models to train the system to recognise cables of different colours, materials, or thicknesses, adapting to multi-scenario task requirements.
This solution features a compact structure, rapid response, and extremely low power consumption, enabling seamless integration with autonomous driving control systems. Thanks to edge deployment, cable maintenance efforts are significantly simplified.
SingTown Technology leverages the high-efficiency visual computing capabilities of the OpenMV smart camera to equip autonomous cable channel inspection vehicles with reliable visual navigation and operational abilities. This enables AI to accurately "see" and operate efficiently in complex terrains.

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