Our 3 highlights from Wherecamp 2019
On November 14th, it was time for the 2019 rendition of the GeoIT Wherecamp Conference, taking place in TU Berlin’s atrium. We were happy to sponsor the event again and want to summarize our highlight talks on mobility predictions, design patterns for geo applications, and a platform for traffic accident analysis.
As a conference about digital mapping, GeoIoT, (autonomous) mobility and spatial intelligence, the talks of the Wherecamp were once again quite diverse. Our data analyst Lasse and CEO Jens attended the conference and found the presentations of Jesse Hinrichsen (civity Management Consultants), Shoaib Burq (Geografia, Deep Learning Box), and Will Jones (Orbica) particularly interesting.
Prediction of movement patterns
How can the demand for public transport and other mobility services be determined? civity intends to answer this question with a demand model they created: Based on aggregated mobile network data, it is possible to predict the movement of people in urban areas. To do so, various machine learning approaches and geo-statistical data sources were tested.
Infrastructural challenges of geo applications
How should a geo application be structured? Shoaib Burq showed how design patterns of applications based on geo data can and should look like, using the Spendmapp as a use case. During development, the application was iteratively extended by workflows to meet the typical challenges of geo applications, such as the automation of data management, the monitoring of machine learning processes, the security and performance of the database structure, and the integration of real-time data.
Accident analysis platform for the New Zealand Transport Agency
How can available funds be used most effectively to make roads safer? Orbiqa presented their customer case "Crash Analysis System" for the New Zealand Transport Agency: Based on an old system, they developed a modern web-based application with a focus on UX/UI. The web app simplifies the analysis of the extensive road traffic accident database and the identification of measures to improve road safety.