城市停车泊位平均停车时长数据

数据可用于查询城市内某路段泊位的平均停车时长情况，应用场景包括：政府决策分析、交通管理系统、停车运营单位管理数据查询等。当车辆驶入或驶出停车位时，安装在此停车位上的地磁检测到磁场变化，判断有车还是无车，将判断后的数据通过NB-IoT实时传输到云平台，
平台解析数据并根据数据库中存储的车位设备关系表，找到对应所属的车位编号和路段信息，根据数据更新车位的状态。
驶入则开始计时，驶出则结束计时并计算停车时长，之后对该路段的停车次数+1、停车时长累加，最后将数据存储到数据库中。据该路段的泊位数量、停车时长、停车次数计算出该路段泊位的平均停车时长。

This dataset can be applied to query the average parking duration of parking spaces on a designated road section within a city. Its applicable scenarios include government decision-making analysis, traffic management systems, and data query services for parking operation entity management.

When a vehicle drives into or out of a parking space, the geomagnetic sensor installed on the parking space will detect magnetic field changes to determine whether the space is occupied or vacant. The resulting judgment data is transmitted to the cloud platform in real time via NB-IoT.

The cloud platform parses the received data, retrieves the corresponding parking space ID and road section information based on the parking space-device association table stored in the database, and updates the parking space's status.

When a vehicle enters the space, timing starts; when the vehicle exits, timing stops and the parking duration is calculated. Subsequently, the total parking count of the road section increases by 1, and the total parking duration accumulates. Finally, the processed data is stored in the database.

The average parking duration of the parking spaces on the road section is calculated based on the total number of parking spaces, total parking duration and total parking times of the section.

AI搜集汇总

数据集介绍

特点

该数据集记录了城市停车泊位的平均停车时长，包含1064条记录，每日更新。数据通过地磁检测和NB-IoT技术实时采集，适用于政府决策分析、交通管理系统等场景。数据结构包括省份、城市、路段、日期、泊位数量、停车时长、停车次数等字段。