Abstract: An M-BUS receiving circuit (8) and an M-BUS-based 4G water meter collector. The M-BUS receiving circuit (8) is disposed between a control unit (2) and an M-BUS overcurrent protection circuit, and is used for connecting the control unit (2) and the M-BUS overcurrent protection circuit. The M-BUS receiving circuit (8) consists of a voltage-stabilizing chip U1, Schmitt triggers U5B and U5C, voltage comparators U3A and U3B, triodes Q2 and Q4, diodes D1, D2, D8-D11, operational amplifiers U15A and U15B, voltage-stabilizing diodes ZW10 and ZW11, and several resistance-capacitance circuits. The M-BUS receiving circuit (8) can greatly increase the signal-to-noise ratio, and the reliability and stability thereof are significantly improved. Similarly, the M-BUS-based 4G water meter collector can effectively improve the stability of water meter data collection.

Abstract: A plurality of variable data of personal attribute information associated with at least one vehicle insurance user is received at a prediction server. Based on a service scenario requirement, a pre-constructed prediction algorithm is selected. The plurality of variable data is processed by one or more processors using the pre-constructed prediction algorithm. At least one prediction result is generated as the prediction server.

Abstract: Embodiments of this specification disclose systems and methods for automotive part recognition based on a vehicle damage assessment image. A method includes: obtaining a damage assessment image of a target vehicle; obtaining an automotive part list of the target vehicle based on a vehicle identification code of the target vehicle, wherein the automotive part list comprises customized configuration information of automotive parts of the target vehicle; and determining a damaged automotive part of the target vehicle from the damage assessment image based on the customized configuration information of the automotive parts of the target vehicle and an image recognition algorithm, to obtain an automotive part identification serial number of the determined damaged automotive part.

Abstract: Embodiments of this specification disclose a method and an apparatus for automotive part recognition based on a vehicle damage assessment image. The method includes: determining a damaged automotive part of a vehicle by recognizing a damage assessment image of the vehicle based on an image recognition algorithm; obtaining an automotive part list of the vehicle, wherein the automotive part list comprises a plurality of automotive parts corresponding to a plurality of automotive part identification serial numbers; matching the damaged automotive part with the plurality of automotive parts in the automotive part list to determine an automotive part corresponding to the damaged automotive part; and outputting an automotive part identification serial number of the determined automotive part.

Abstract: Embodiments of this specification disclose systems and methods for automotive part recognition based on a vehicle damage assessment image. A method includes: obtaining a damage assessment image of a target vehicle; obtaining an automotive part list of the target vehicle based on a vehicle identification code of the target vehicle, wherein the automotive part list comprises customized configuration information of automotive parts of the target vehicle; and determining a damaged automotive part of the target vehicle from the damage assessment image based on the customized configuration information of the automotive parts of the target vehicle and an image recognition algorithm, to obtain an automotive part identification serial number of the determined damaged automotive part.

Abstract: Embodiments of this specification disclose a method and an apparatus for automotive part recognition based on a vehicle damage assessment image. The method includes: determining a damaged automotive part of a vehicle by recognizing a damage assessment image of the vehicle based on an image recognition algorithm; obtaining an automotive part list of the vehicle, wherein the automotive part list comprises a plurality of automotive parts corresponding to a plurality of automotive part identification serial numbers; matching the damaged automotive part with the plurality of automotive parts in the automotive part list to determine an automotive part corresponding to the damaged automotive part; and outputting an automotive part identification serial number of the determined automotive part.

Abstract: A plurality of variable data of personal attribute information associated with at least one vehicle insurance user is received at a prediction server. Based on a service scenario requirement, a pre-constructed prediction algorithm is selected. The plurality of variable data is processed by one or more processors using the pre-constructed prediction algorithm. At least one prediction result is generated as the prediction server.

Abstract: A predetermined field containing attribute information associated with an auto insurance user is received at a risk assessment server and from an insurance company server. A personal attribute variable associated with the auto insurance user and a value corresponding to the personal attribute variable are obtained by querying a database based on the predetermined field. An auto insurance standard score for the auto insurance user is generated by using a predetermined calculation method with the obtained personal attribute variable and the corresponding value for the personal attribute variable. The auto insurance standard score is returned to the insurance company server.