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Urban energy planning. Optimized.

I’d like to register for a free trial of sympheny’s software

We have received your request. Thanks!
You will receive an email from us as soon as possible.
You will receive an email from us as soon as possible.
Oops! Something went wrong while submitting the form.
June 1, 2021
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Sympheny - Google Summer of Code 2021 projects

Leveraging GIS based open-source data and GIS-functionalities to provide data driven analytics to optimise distributed energy system design, urban planning developing a web-based approach.

Background

  • QGIS open-source software provides advanced GIS functionalities, and direct access to open-source plugins allowing to leverage open-source datasets. However, QGIS provides limited potential in handling advanced calculation and optimization process within the python QGIS environment. ​
  • The development of an open-source package enabling the utilization of advanced GIS functionalities, and the query of GIS based open-source data (energy infrastructure, buildings, networks, etc..) from a web-based user interface is key to provide the complete set of tools to be integrated with open-source advanced planning tool (e.g.: energydata.info/apps).

Scope of work (2 to 3 projects)

  • The goal of the project is to use existing open source web package for QGIS (https://github.com/qgis/qwc2-demo-app), and integrate the web-based GIS functionalities with OSM query APIs. It includes functionalities to query open source data on urban infrastructure in an automated fashion, to make use of open access data for urban planning (infrastructure, building, power, network data, etc.). The web-based framework includes advanced data visualization on the based of the queried data.​​
  • Development of a simplified user interface to interact with the platform functionalities.
  • Integration of GIS functionalities (network constraints, selection lines, points, polygons, overlay .shp/geojson) from web-based using open layer services.
  • Integration of open-source data query functionalities similar to overpass or quickOSM functionalities.
  • A second project make use of the GIS data from python-based application to create data driven knowledge based on queried data (network constraint, infrastructure constraint), additional GIS analysis provided, and combined with advanced data mining (clustering) and optimization packages provided to the student. The generated knowledge is integrated with ER database, using postgre SQL / postGIS.  
  • Development of the application programming interface connected with the visualization platform developed in 1)
  • Development of the ER- database to enhance the management of the GIS data queried and analyzed
  • Use of the data knowledge in connection to solving urban planning related problems, such as network constraint, optimization of the allocation/location of EVs charging station according to amenities, etc.

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