(Fire)Data & The CityAmsterdam, 3 oktober 2016

Data Driven Public Safety

Guido Legemaate

Brandweer Amsterdam-Amstelland

Centrum Wiskunde & Informatica

Overview

● Business Intelligence

● Data Vault

● Data Science

Fire Data

Data VaultThe backbone of our data

management solution.

Arjen ter Heide

Over the last 4 years we have build a

robust data warehouse, modelled

according to “data vault” techniques.

All core data sources are integrated

and can be used for e.g. dashboarding,

but also (as was my initial goal when

starting the data collection) to use as

input for models/algorithms.

Risk ProfilesThe first real usage of our data

was the creation of risk profiles.

Barry van ‘t Padje et al.

source: BBC @ http://www.bbc.com/news/business-21902070

http://static1.squarespace.com/static/5150aec6e4b0e340ec52710a/t/51525c33e4b0b3e0d10f77ab/1364352052403/Data_Science_VD.png

1874

In 1874, the Dutch capital Amsterdam was the first city in

the Netherlands with a pro-fessional fire service.

With 144 people personnel and 9 fire stations covering 30 square

kilometers, it ensured fire protection safety for

approximately 285,000 inhabitants.

source: Geodan @ https://youtu.be/DD4m_Vna5uU

Location of fire stations

Optimizing fire station locations.

Pieter van den Berg

Guido Legemaate

Rob van der Mei

Location of fire stationsDecisions:

● How many fire stations do we need?

● Where to locate them?

● How to distribute the available fire trucks?

● How to distribute (types of) personnel?

Goal:

● Maximize coverage for different types of fire trucks

Constraints:

● Limit amount of fire stations and trucks

● Crew

Location of fire stations

Extensive analysis of a large dataset of historical incidents demonstrates:

● that, and how, response time can be improved by “simply” relocating only three

out of 19 base locations and redistribution of the different vehicle types over the

base locations

● that there is no need to add new base locations to improve performance:

optimization of the locations of the current base stations is just as effective

However…€€€

Relocating fire trucks during big

incidents.Maximize coverage / response

times in times of ‘shortage’.

Dimitrii Usanov

Peter van de Ven

Guido Legemaate

Moumna Rahou (student)

It is not uncommon that three or

more fire trucks/stations are

attending one big incident, like a fire.

Also, these incidents tend to last

longer than usual, potentially leaving

parts of the city with a less than

optimal coverage. In those cases fire

trucks are relocated, but there is no

clear method on how to do this. We

use mathematical programming to

propose a method.

source: Dimitrii Usanov, Ph.D. student CWI

GPS routesMapping and matching prognosed

routes with those routes that we

actually took.

Guido Legemaate

Arjen ter Heide

Anne-Frances Appelman (student)

We have extracted all GPS data from

all of our fire trucks from over the last

7 years. Datapoints are taken every 10

to 30 seconds and are comprised of

date/time, licenseplate no., lat/long

coordinates, speed.

Goal is to extend knowledge about

driving speed and vital infrastructure.

Vital LogisticsEmergency service logistics:

network design and dynamic

dispatching.

NWO granted project.

Work in progress.

Emergencies such as the breakdown of an

MRI-scanner or a domestic fire demand a timely

response. This means that the resources required

for addressing such incidents (spare parts and

fire trucks, respectively) need to be stored in

relative proximity of potential incidents and

dispatched on short notice. This requires a

network of resources in several storage locations.

Owners of such Emergency Resource Networks

(ERNs) face three issues: (i) Where should

resources be stored, and how many resources

need to be available at each location? (ii) How

should resources be dispatched in response to an

emergency? (iii) Can the performance of the

system be improved by proactive relocation of

resources?

Guido Legemaate g.legemaate@brandweeraa.nl@gaglegemaate g.a.g.legemaate@cwi.nl