From February 5 to 7, a strong wind and temperature drop occurred in the Xiong'an New Area of Hebei, China. Based on the latest forecast, the Xiong'an New Area's start-up urban operations center system automatically adjusted the road cleaning plan from the previous routine optimization mode to a low-temperature wet sweeping mode. Integrating the Xiong'an Ruisi hourly temperature forecast results, it precisely identified an operation window from 11:00 to 14:00 on February 5 when temperatures were still above 0°C, automatically generated work orders for wet sweeping and flushing, and pushed them to the operation teams. Upon receiving task reminders, workers pre-checked vehicle antifreeze and equipment status, and carried out concentrated mechanized joint operations during the forecasted window period to ensure safe urban operations.

Behind this precise mode adjustment is the meteorological logic algorithm embedded in the Xiong'an New Area's start-up urban operations center system.

On February 1, the urban operations management module of the system completed the real-time integration of meteorological information. By constructing spring, summer, autumn, and winter road cleaning operation scenarios, the system can scientifically adjust road cleaning operation modes based on real-time meteorological monitoring and short-term forecasts.

"In winter, based on real-time temperatures and considering factors such as road surface temperature, wind speed, and relative humidity, the system dynamically assesses the risk of road icing. Once it predicts the road surface temperature will approach freezing within the next three hours, it automatically suspends sprinkling and wet sweeping operations, switching to dry sweeping or mechanical vacuum modes to eliminate traffic safety hazards at the source," explained LU Quanyan, Deputy Director of the Start-up Area Management Committee. Furthermore, during windy periods in spring, the system schedules cleaning vehicles in advance to avoid peak dust times; before summer convective weather, operation plans are automatically adjusted to safe periods; during the peak leaf-fall season in autumn, the system optimizes cleaning frequency based on wind forecasts; and upon winter snow warnings, snow-melting and de-icing plans are immediately activated.

"Meteorological data is truly integrated into the 'nerve endings' of urban operation decision-making. This pilot application not only improves public service efficiency but also represents an exploration of the 'data-driven decision-making' development path for smart cities," said HUA Jiajia, Deputy Director of the Xiongan New Area Meteorological Department.

Author: CHEN Xuejiao, LU Shuo

Editor: JIANG Zhiqing