Publication Details
Abstract
Urban fire and rescue service operates for unpredictable incidents, such as fires, explosions, road traffic accidents, and life support systems failure. Estimating incoming dispatch call flows is majorly critical for demand predictions and for establishing operational readiness. While the call streams from a given area may be assumed to be driven by a stationary Poisson process, dispatch activity at the city level will often present monthly and seasonal variation—an effect that can lead to less robust statistical verification if an entire year is treated as a single uniform flow. The analysis is made based on dispatch call data of the Termez city fire and rescue service units in 2022. Theoretical Poisson distributions were computed to match empirical daily call distributions. The agreement between empirical and theoretical results was tested with the Pearson chi square goodness of fit criterion (with the additional interpretation with the Romanov criterion). Seasonal variability was examined by dividing the year into three periods (January–March, April–August, and September–December). They found an average call intensity of about 1.7 calls/day, with monthly variability between 1.2 and 2.1 calls/day. When the seasonal grouping was recalculated the Pearson criterion test showed that stationarity can be accepted for the dispatch call flow and this flow can be described by the Poisson distribution. This data supports the continuous adoption of Poisson based mathematical models as a tool for forecasting dispatch demand as well as optimizing staffing and resource allocation for the overall efficiency of the fire and rescue service process.