江苏省苏州市停车情况综合分析数据

提供江苏省苏州市道路停车数据，方便交通管理部门及停车运营单位查询江苏省苏州市内的停车情况，分析道路停车的各路段泊位周转率、日平均停车时长分布等，进行停车运营的管理。当车辆驶入或驶出停车位时，安装在此停车位上的地磁车位检测器检测到磁场变化，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以及路段信息。平台每小时按照省份、城市、路段的层次从数据库检索，并按照如下规则做数据统计： 统计最近一小时内，该路段下所有泊位地磁上报的有车总数据条数作为【停车次数】；统计当前时刻该路段下有车的泊位数量，作为【占用泊位】数量；统计当前时刻该路段下无车的泊位数量，作为【空闲泊位】数量；空闲泊位+占用泊位作为【泊位总数】；占用泊位/泊位总数作为【泊位占用率】；停车次数/泊位总数作为【周转率】；每个泊位停车时长总和作为【总停车时长】；总停车时长/停车次数 作为【平均停车时长】； 最后将省份、城市、路段、日期、统计时间、泊位总数、空闲泊位、占用泊位、泊位占用率、停车次数、周转率、总停车时长(分钟)、平均停车时长（分钟）存储到数据库中供后续查询。

This dataset provides road parking data for Suzhou City, Jiangsu Province, to enable traffic management authorities and parking operation entities to query parking conditions within Suzhou, Jiangsu, analyze indicators such as the turnover rate of parking spaces in each road section and the distribution of daily average parking duration, so as to support parking operation management. When a vehicle enters or exits a parking space, the geomagnetic parking space detector installed on the parking space detects magnetic field changes to determine whether the space is occupied or vacant, and transmits the determined data to the cloud platform in real time via NB-IoT. The platform parses the data and retrieves the corresponding parking space number and road section information based on the parking space-equipment relationship table stored in the database. The platform retrieves data from the database on an hourly basis in the hierarchy of province, city and road section, and conducts data statistics according to the following rules: 1. Count the total number of "occupied" status reports submitted by geomagnetic detectors of all parking spaces under the target road section in the latest hour as [Parking Times]; 2. Count the number of currently occupied parking spaces as [Occupied Parking Spaces]; 3. Count the number of currently vacant parking spaces as [Vacant Parking Spaces]; 4. Total Parking Spaces = Vacant Parking Spaces + Occupied Parking Spaces; 5. Parking Space Occupancy Rate = Occupied Parking Spaces / Total Parking Spaces; 6. Turnover Rate = Parking Times / Total Parking Spaces; 7. Total Parking Duration = Sum of the parking durations of all parking spaces under the target road section; 8. Average Parking Duration = Total Parking Duration / Parking Times; Finally, the platform stores the data including province, city, road section, date, statistical timestamp, total parking spaces, vacant parking spaces, occupied parking spaces, parking space occupancy rate, parking times, turnover rate, total parking duration (in minutes), and average parking duration (in minutes) into the database for subsequent query and analysis.