Ambulance placing problems

I suggest a new Emergency Management Hot Spots (EMHS) model as the patches of current EMS spatial distribution. This model works differently from the existing ambulance location and relocation models. EMHS consists of two parts; the first part is to identify the hot spots based on the experiences. The second part is the algorithm that selects the places for the new patches of mobile ambulance service areas. In the first part, we use the Cross Table, ANOVA, Correlation Coefficients, and grouping of factors to find special characters and patterns in the EMS records from Taichung city in the past decade. Then, we design an EMS problem locations selection method to determine the hot spots of EMS that could be the potentially busy areas of EMS requests. In the second part, we suggest a method to arrange the service areas to cover all the problem areas. With this method, we believe that it can assist the ambulance redeployment or reschedule schema and at the same time can solve the business problems in the study area. The results show that in 2008 the hot spots are 113 cells and in 2020 are 105 within Taichung city. In 2008, the study area needs five additional mobile ambulance sties to cover most of the problem areas. The pattern of hot spots shifts toward north and west of the city from 2008 to 2020, on the other hand, on the south side and the center of the city the hot spots are receding. These results can profit by location evaluation, deployment scheduling, and management of ambulances in the future.