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Are we there yet? An Analysis of Cobb County Fire Department's Response Times. Ph.D. Students in Analytics and Data Science : Bogdan Gadidov , Lili Zhang, and Yiyun Zhou Faculty Advisors: Dr. Joe DeMaio, Dr. Kurt Schulzke, And Dr. Gene Ray

  1. Are we there yet? An Analysis of Cobb County Fire Department's Response Times. Ph.D. Students in Analytics and Data Science : Bogdan Gadidov , Lili Zhang, and Yiyun Zhou Faculty Advisors: Dr. Joe DeMaio, Dr. Kurt Schulzke, And Dr. Gene Ray

  2. Reducing Traveling Time for CCFD Getting emergency vehicles quickly to an incident is critical in saving lives and property. • Measured at the 90 th percentile of the response times - National Standards: 4 mins - Cobb County: 8 mins • 29 fire stations and 272 fire zones • 168 incidents per day • Population 717,190 (50% increase since ‘95) 2 22 2

  3. You may have noticed… 3 3

  4. 4 4

  5. 5 5

  6. Reducing Roll time for CCFD Historically, fire zones were created over the past few decades by driving around in a vehicle and eyeballing where zones should begin and end. 6 6

  7. Historical Fire Station Zones 7 7

  8. Reducing Roll time for CCFD Population growth and surrounding infrastructure has changed dramatically in Cobb County over the past two decades. Town Center Mall in the late 80s. 8 8

  9. Reducing Roll time for CCFD Population growth and surrounding infrastructure has changed dramatically in Cobb County in the past decades. Town Center Mall more recently. 9 9

  10. Objective • Find the most important variables that can influence the traveling time of CCFD • Goal of CCFD: traveling time within 4 minutes 90% of the time. • Then, see if the variables can be combined with Google maps to optimize the zones. 10 10

  11. Variables from the datasets provided by clients • Population: < 1 st Quantile (<2299): pop = 1; 1 st ~ 2 nd Quantile (2299~4278): pop = 2; 2 nd ~ 3 rd Quantile (4278~6481): pop = 3; otherwise: pop = 4 • Fire (Yes/No) • Medical (Yes/No) • Rescue (Yes/No) • Unit (Vehicle Type) 11 11

  12. • Unit (Vehicle Type) 12 12

  13. Variables from the dataset collected online • Temperature: < 32 0 F: Cold; ° F 32 ~ 59 0 F: Freeze; 59 ~ 85 0 F: Warm; > 85 0 F: w_Hot. • Visibility (in miles): > 3: indvisib = 1; <= 3: indvisib = 0. 13 13

  14. Variables from the dataset collected online • Day_of_Week: 1, 2, 3, 4, 5, 6, 7 • Interval_of_day: 5 ~ 10 AM: Morning 10 ~ 16 PM: Mid 16 ~ 20 PM: Evening Otherwise: Night 14 14

  15. Variables from the dataset collected online • Events 15 15

  16. Variables created by meaningful interactions • Rain and Interval of day • Snow and Interval of day • Population and Interval of day 16 16

  17. Response Variable (traveling time) Delete observations with traveling time > 95 th percentile • since these observations are potential outliers; • Traveling time <= 4 min then GOODBAD = 0, denoting the success to meet the goal; • Traveling time > 4 min then GOODBAD = 1, denoting the failure to meet the goal. 17 17

  18. Model Performance: Area under ROC Receive Operating Characteristic Curve (ROC curve): a graphical plot that illustrates the performance of the classification method. X-axis: false positive rate Y-axis: true positive rate Decision Tree: 0.636 Logistic Regression: 0.674 Random Forest: 0.639 18 18

  19. Model Performance: Misclassification Rate 19 19

  20. Directions of Variable Effects Variable Name Influence on Traveling Time Pop_eve Increase Pop Increase Pop_mid Decrease Vehicletype (= MEDOP) Decrease Fire (= Yes) Decrease Humidity Increase Pop_morn Decrease Temperature Decrease Medical (= Yes) Decrease Visibility Decrease Other (= Yes) Increase Events (= Snow-Thunderstorm) Increase 20 20

  21. Reducing Traveling Time for CCFD Cobb County – Historical Traveling Time Data Google Maps – New Traveling Time Data 21 21

  22. Reducing Traveling Time for CCFD 22 22

  23. Algorithm Implementation: Step 1. Retrieve relevant information of all incidents. t • Address • Zone • Assigned station • Traveling time of the unit that responded • Time interval 23 23

  24. Time Interval For Each Day 5 : 00 to 10 : 00 Morning 10 : 00 to 16 : 00 Mid 16 : 00 to 20 : 00 Evening 20 : 00 to 5 : 00 Night 24 24

  25. Algorithm Implementation Step 2. Retrieve the addresses of all 29 Cobb County fire stations. best station suggested by Google Maps to the historical corresponding station. STATION ADDRESS 1 5656 Mableton Pkwy SW, Mableton, GA 30126, USA 2 208 Barber Rd, Marietta, GA 30060, USA 3 580 Terrell Mill Rd, Marietta, GA 30067, USA 4 1901 Cumberland Pkwy SE, Atlanta, GA 30339, USA 5 4336 Paces Ferry Rd SE, Atlanta, GA 30339, USA 6 5075 Hiram Lithia Springs Rd SW, Powder Springs, GA 30127, USA 7 810 Hurt Rd, Austell, GA 30106, USA 8 2380 Cobb Pkwy NW, Kennesaw, GA 30152, USA 9 7300 Factory Shoals Rd, Austell, GA 30168, USA 25 25

  26. Algorithm Implementation Step 2. Retrieve the addresses of all 29 Cobb County fire stations. best station suggested by Google Maps to the historical corresponding station. Ideally, we would check all 29 fire stations for their Google Maps travel time to each incident. Unfortunately Google Maps access is only free up to 2,500 requests per day. station suggested by Google Maps to the historical corresponding station. Premium access is available at 50 cents per 1000 requests with a limit of 100,000 requests per day. . 26 26

  27. Algorithm Implementation Step 3. Create a list of neighoring stations to check for each incident. 27 27

  28. Algorithm Implementation Step 4. Use Google Maps Distance Matrix API to calculate traveling time from an incident to its neighboring stations at midday for 2016. Corr_statio Google_stati Google_ti Zone Hist_time n on me 24E 515 24 24 281 26C 192 26 26 196 22D 287 22 22 385 1C 195 1 1 284 9C 243 7 1 47 22F 160 22 22 143 15B 402 16 14 362 5B 304 5 5 385 27C 156 27 27 119 28 28

  29. Python Code To Retrieve Google Data 29 29

  30. Algorithm Implementation: Step 5. Reshape Zones. Note that zone 8 is Kennesaw State University which exploded in population and infrastructure over the past two decades. 30 30

  31. Travel Time Reduction Zone Old Time New Station New Time Time Savings 17K 521 10 383 138 8I 490 24 375 115 26G 631 11 517 114 8H 521 17 419 102 19F 318 3 222 96 18F 497 3 412 85 11B 345 28 319 26 18A 321 24 298 23 1C 269 27 260 9 31 31

  32. Limitations • Google Time impacted by current traffic outliers • I-85 Collapse • Unusually large accidents • Bad weather • ?????? • Units may not drive from station to incident location • Available data from Google Maps • Slightly under $1000 to run all incidents from 2011 during midday 32 32

  33. Future Work • Reshape zones for other times of day • Morning • Evening • Night • Reshape zones for summer when school is out • Reshape zones for Braves games • Use Premium API key or low-tech parallel processing 33 33

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