Transportation reliance grows in lockstep with population expansion. Since automobiles have been more widely available and used in recent years, a range of practical problems have arisen, making it more challenging to obtain a place to park. The concept offers an innovative way to solve the problem of wasting time trying to find a parking space at business premises. In order to determine when a car pulls into or pulls out of a parking space, sensors like IR sensors are utilized. This particular approach provides information about unfilled spaces which are currently obtainable but fails to offer details about the precise position of spots to park in this huge area. It requires a period of time to find an accessible location, and even when the parking lot is large, it will take an extended period of time, which is a major disadvantage of the traditional ways. The suggested auto parking system employs infrared sensors that detect cars at the entry and departure points before allocating and redistributing the available garages to the vehicles using the LabVIEW toolkit. This technology prominently shows the variety of parking stalls offered along with the ratio of occupied and idle gaps on the LCD display screen to enable individuals to confirm the slots before reaching the parking area. By adopting cutting-edge detecting and reporting methods, smart parking management intends to monitor and optimize the use of parking places inside gigantic parking complexes. It also attempts to make parking less challenging for those who drive by directing them towards suitable parking places, so minimizing needless anxiety and delay that exacerbates transportation issues. The LabVIEW console’s red and green LED’s indicate whether or not there are any available spots in the parking lot, which is monitored by IR sensors. A red indicator shows that the space is vacant, while a green indicator shows that the spot is filled.


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    Titel :

    SMART CAR PARKING SYSTEM USING LabVIEW


    Beteiligte:


    Erscheinungsdatum :

    02.05.2024


    Format / Umfang :

    969140 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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