Disclosed is an accident-free forklift using machine learning. According to the present disclosure, the accident-free forklift using machine learning comprises: a first sensor for capturing images around the forklift; an object recognition unit for detecting an object approaching around the forklift by applying the image around the forklift to a deep learning-based object recognition model, and then classifying the type of the detected object; and a vibration generating unit which generates vibrations in different vibration patterns according to the types of the classified object. The vibration generating unit includes a plurality of vibration sensors, wherein the plurality of vibration sensors may be located on at least one among a driver's seat, a driver's work clothes, a seat belt, and a waist belt according to a predetermined pattern.

    머신러닝을 이용한 무사고 지게차가 개시된다. 머신러닝을 이용한 무사고 지게차는, 지게차 주변 영상을 촬영하는 제1 센서; 상기 지게차 주변 영상을 딥러닝 기반 객체 인식 모델에 적용하여 상기 지게차 주변으로 접근하는 객체를 검출한 후 상기 검출된 객체의 유형을 구분하는 객체 인식부; 및 상기 구분된 객체의 유형에 따라 서로 다른 진동 패턴으로 진동을 발생하는 진동 발생부를 포함하되, 상기 진동 발생부는 복수의 진동 센서를 포함하되, 상기 복수의 진동 센서는 미리 정해진 패턴에 따라 운전석 의자 시트, 운전자 작업복, 안전 벨트 및 허리띠 중 적어도 하나에 위치될 수 있다.


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    Title :

    Accident-free forklifts using machine learning


    Additional title:

    머신러닝을 이용한 무사고 지게차


    Contributors:

    Publication date :

    2021-07-19


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Korean


    Classification :

    IPC:    B66F HOISTING, LIFTING, HAULING, OR PUSHING, NOT OTHERWISE PROVIDED FOR, e.g. DEVICES WHICH APPLY A LIFTING OR PUSHING FORCE DIRECTLY TO THE SURFACE OF A LOAD , Hub-, Verhol- oder Schubvorrichtungen, soweit nicht anderweitig vorgesehen, z.B. Vorrichtungen mit unmittelbarer Krafteinwirkung auf die Last / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / G08B SIGNALLING OR CALLING SYSTEMS , Signalisier- oder Rufsysteme



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