Error detection and visualization method using Automotive Intelligence Knowledge-Base based on Digital Twin

摘要

A method is provided for detecting errors in construction equipment in the physical real world through digital twin technology and providing information in which the detection results are formed to Automotive Intelligence service users. Error detection and shaping method according to an embodiment of the present invention comprises the steps of: collecting location data, work data and status data of construction equipment; and updating the virtual space model implemented as a digital twin type that can be intuitively shaped based on the collected data, and detecting an error condition of the updated virtual space model. Accordingly, regardless of the type of data collected from construction equipment, it can be classified if only the normal/abnormal range is determined. By universally detecting errors in construction equipment in the physical real world through digital twin technology, and shaping the detection results, It is possible to provide a safe environment for using construction equipment.