Determining the availability of personnel in firefighting using Premergency and DIVERA 24/7
The availability of firefighters marks one of the most important factors in strategic planning. Knowing, how many team members are available at a certain time, gives you a strategic advantage. This allows you to plan efficiently and predictive. Based on a three month case study, we will show you how to identify the availability of personnel for your fire department using Premergency and DIVERA 24/7. Moreover, you will learn, how you can use this data to derive predictions and recommendations for the future.
Our study is based on data from the application DIVERA 24/7. This app allows firefighters to easily communicate their status to headquarters using their smartphone. With the help of DIVERA 24/7, we assessed time frames and availabilities of team members (e.g. “at the station” or “available within 5 minutes”). The data set is fully anonymous at all time. However, it is possible to trace back anonymous team members to their respective units.
Subsequently, we model the availability of firefighters as a stochastic process using Bayesian statistics. As a result of the calculations, we receive a probability distribution for the availability of personnel. After that, we derive a prognosis for the amount of available team members for each firefighting unit, combining the modelled availability of all team members.
The image shows the predicted daily activities of smokedivers within a unit, available within 10 minutes on a weekday. The expected fluctuation ranges are displayed in grey. (Verfügbares Personal = Availbale personnel, Atemschutzgeräteträger = smokedivers, Uhrzeit = time, Anzahl = amount).
Results and perspective
In the previous paragraph we have shown you the methods and procedure of our study. But what are the advantages of our calculations? As a result of our study, we can now predict how many firefighters will be available at a specific time.
This allows mission control, to quickly and predictively react to shortages of personnel and plan accordingly. Thus, you can make sure to always have enough firefighters at your disposal. Furthermore, you can derive recommendations for your master fire plan.
With this case study, we were able to show how to create a data-driven foundation for availability prognoses using Premergency and DIVERA 24/7. In order to further improve our predictions, we are planning on linking the DIVERA 24/7 data set with personalized and demographic data.This will enable us to group firefighters according to age, profession and many more factors. With the classification into user groups, we hope to improve our predictions and to establish reliable prognoses within only a few weeks, comparing the data to fire departments in other cities. When using DIVERA 24/7 for several months to assess the availability of personnel, it is possible to predict seasonal trends, which can thus be taken into account for your strategic planning.
Finally, we can establish that you can make valuable prognoses for the availability of personnel, by combining Premergency and DIVERA 24/7 . This increases the efficiency of fire departments and serves as a valuable foundation for your master fire plan.
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