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UID:pretalx-foss4g-2022-Z3HJLM@talks.staging.osgeo.org
DTSTART;TZID=CET:20220825T151500
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DESCRIPTION:Our digital maps are not always up to date with the real world.
  New road constructions and road blockages could reduce the accuracy of th
 e map data. In a logistics company like Gojek that serves millions of user
 s per day in South East Asia\, the core undertaking revolves around routin
 g and ETAs. Any inaccurate local map data can lead to a direct negative im
 pact on business metrics.\n\nSo how do we ensure that map inconsistencies 
 are detected and fixed promptly to minimise interference of our services? 
 When manual detection is labor intensive and not scalable to millions of r
 oad networks in vast regions\, how can we effectively automate this at sca
 le? \n\nThis talk is a story of how we\, at Gojek\, built a pipeline that 
 uses bad customer experience as the trigger to identify potentially faulty
  data in OpenStreetMap. Our solution makes use of noisy GPS traces and Ove
 rpass\, an open source tool\, to automate this detection. \n\nThis solutio
 n enabled us to identify 100s of potential issues per day\, categorise the
 m\, associate business impact to each map issue and allow our map analysts
  to fix them seamlessly.
DTSTAMP:20260403T220248Z
LOCATION:Modulo 0
SUMMARY:Use of FOSS4G at Gojek to automate map error detection at scale - S
 riram Ravichandran\, Chia Li Juan
URL:https://talks.staging.osgeo.org/foss4g-2022/talk/Z3HJLM/
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