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Data & The City - Guido Legemaate - Brandweer Amsterdam Amstelland

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Data & The City
Big Data, Open Data, Deep Data,
Data Analytics, Business Intelligence, Dashboards, Monitors

8:30-18:00 uur
maandag 3 oktober 2016
Raadzaal Stadhuis Amstel 1 Amsterdam

#amsboda1 #data #bigdata #opendata #deepdata
@AmsTechCity (Twitter Instagram Facebook)
Amsterdam Tech City (YouTube MeetUp)

PROGRAMMA
08:30 – 09:00 inloop & inschrijving
09:00 – 09:15 Gemeente Amsterdam opening Nuray Gokalp
09:15 – 09:30 Gemeente Amsterdam DataLab Berent Daan
09:30 – 09:45 Gemeente Amsterdam CTO Office Tamas Erkelens
09:45 – 10:00 Gemeente Amsterdam Bedrijfsvoering AMI Lieke van Bers
10:00 – 10:15 Gemeente Amsterdam Ruimte OOV Eric Aart & Kees Rooij
10:15 – 10:30 Gemeente Amsterdam Sociaal GGD Thijs Houtenbos

10:30 – 11:00 pauze
11:00 – 11:15 Gemeente Amsterdam Dienstverlening Mellijn Hartman
11:15 – 11:30 Gemeente Amsterdam Veranderkunde Ingmar Kappers
11:30 – 11:45 Brandweer Amsterdam Amstelland Guido Legemaate
11:45 – 12:00 Vital 10 Roderick
12:00 – 12:15 ADS + UvA + KPMG Sander Klous
12:15 – 12:30 Scyfer Jorgen Sandig

12:30 – 13:30 lunch
13:30 – 13:45 Omnichannel.store Roger Olivieira
13:45 – 14:00 IceMobile Floor Wijnen + Guido Jetten
14:00 – 14:15 Xomnia Martijn Imrich
14:15 – 14:30 Ynformed Martijn Minderhoud
14:30 – 14:45 Open State Foundation Tom Kunzler
14:45 – 15:00 Teamily Maarten Lens-Fitzgerald

15:00 – 15:30 pauze
15:30 – 15:45 ADS + UvA + FD + MIcompany Martin Heijnsbroek
15:45 – 16:00 KLM Leon Gommans
16:00 – 16:15 ING Jos Schenning
16:15 – 16:30 GoDataDriven Rob Dielemans
16:30 – 16:45 Teradata Natalino Busa
16:45 – 17:00 Dell EMC Kenny Pool
17:00 – 17:15 VR Base Launch Daan Kip
17:15 – 18:00 borrel

WAT?
Big Data, Open Data, Deep Data, Data Analytics technologie voor lokale overheid onderzoeken.
Samen met nationale en internationale experts de mogelijkheden en onmogelijkheden verkennen voor de Gemeente Amsterdam.

HOE?
Koppelen van maatschappelijke vraagstukken en oplossingen. Vraagstukken worden gepresenteerd door ambtenaren van de Gemeente Amsterdam. Oplossingen worden gepresenteerd door experts van andere overheidsinstellingen, kennisinstellingen, stichtingen, bedrijfsleven, grote bedrijven, MKB, startups, scaleups en freelancers. Presentaties zijn blokken van 15 minuten, waarvan 10 minuten presenteren aan publiek en 5 minuten interactieve vraag & antwoord.

WIE?
• Ambtenaren van de gemeente Amsterdam en overheidsinstellingen
• Experts op het gebied van big data, open data, deep data, analytics…
• Kennisinstellingen (universiteiten, hogescholen, etc.)
• Stichtingen, NGO’s
• Bedrijfsleven
• Startups & Scaleups
• Freelancers
(50% overheid + 50% “rest”)

CONTACT
Nuray Gokalp
Mobiel +31(0)6-46068985
Email n.gokalp@amsterdam.nl
Twitter & Instagram @NurayG
LinkedIn NurayGokalp
Skype Nuray.Gokalp

Published in: Technology
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Data & The City - Guido Legemaate - Brandweer Amsterdam Amstelland

  1. 1. (Fire) Data & The City Amsterdam, 3 oktober 2016 Data Driven Public Safety Guido Legemaate Brandweer Amsterdam-Amstelland Centrum Wiskunde & Informatica
  2. 2. Overview ● Business Intelligence ● Data Vault ● Data Science
  3. 3. Fire Data
  4. 4. Data Vault The 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.
  5. 5. Risk Profiles The 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
  6. 6. 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.
  7. 7. source: Geodan @ https://youtu.be/DD4m_Vna5uU
  8. 8. Location of fire stations Optimizing fire station locations. Pieter van den Berg Guido Legemaate Rob van der Mei
  9. 9. Location of fire stations Decisions: ● 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
  10. 10. 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…€€€
  11. 11. 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.
  12. 12. source: Dimitrii Usanov, Ph.D. student CWI
  13. 13. GPS routes Mapping 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.
  14. 14. Vital Logistics Emergency 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?
  15. 15. Guido Legemaate g.legemaate@brandweeraa.nl @gaglegemaate g.a.g.legemaate@cwi.nl

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