The existing solutions are mainly cloud and network-based software and hardware solutions such as smart gates, smart floor locks, and smart sensors, which rely on data processing and control in the cloud, and the parking business has extremely high requirements for real-time and fast response to data. When a large number of parking smart devices are connected to the cloud and the cloud needs to process the response in real time, the disadvantage of cloud computing becomes apparent. "Fog computing" may become the next-generation technology of the Internet of Things.
Like cloud computing, fog computing is very vivid. Clouds are floating in the sky, high above, out of reach, deliberately abstract; while fog is telemarketing list realistic, close to the ground, right beside you and me. Fog computing is an extension of cloud computing, which can be understood as a cloud on the ground to accommodate the emerging Internet of Things. Instead of relying primarily on remote servers at a central location, fog computing uses distributed computer resources closer to local devices to handle processes that require fast processing. In the smart parking industry, when each smart parking lot has fog computing capabilities, firstly, the real-time response will be effectively guaranteed. Direct communication and linkage, the underlying processing capability for the coverage of various parking scenarios, and a complete parking solution will be easier to solve.
Management side The core of smart parking management is unmanned. Based on technologies such as AI image recognition, face recognition and video recognition, it will play a key role in the management of parking lots. High-precision image and video recognition technologies are specifically applied to illegal parking. , billing management and other business scenarios. Combined with the construction of the social credit system, it assists the management system in the case of unattended parking lots, and establishes a parking credit investigation system through car owner portraits, parking trajectories, payment behaviors and LBS, and provides car owner credit big data for the construction of the city's overall credit system. resources, capital support and giant resources will stand out key.