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teaching:projh402 [2020/10/22 14:18] ezimanyi [Implementing TSBS on MobilityDB] |
teaching:projh402 [2020/12/23 22:53] ezimanyi [Distributed Moving Object Database on MS Azure] |
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MobilityDB is engineered as an extension of PostgreSQL. MS Azure supports distributed PostgreSQL databases using [[https://www.citusdata.com/|Citus]]. We have made successful tests for integrating MobilityDB and Citus on a local cluster. The goal of this project is to repeat this work on MS Azureintegrate MobilityDB with these products. The key outcomes are a comprehensive assessment of which MOD API can/cannot be distributed, and an assessment of the performance gain. These outcomes should serve as a base for a thesis project to achieve effective integration. | MobilityDB is engineered as an extension of PostgreSQL. MS Azure supports distributed PostgreSQL databases using [[https://www.citusdata.com/|Citus]]. We have made successful tests for integrating MobilityDB and Citus on a local cluster. The goal of this project is to repeat this work on MS Azureintegrate MobilityDB with these products. The key outcomes are a comprehensive assessment of which MOD API can/cannot be distributed, and an assessment of the performance gain. These outcomes should serve as a base for a thesis project to achieve effective integration. | ||
+ | **Status**: taken | ||
===== Map-matching as a Service ===== | ===== Map-matching as a Service ===== | ||
GPS location tracks typically contain errors, as the GPS points will normally be some meters away from the true position. If we know that the movement happened on a street network, e.g., a bus or a car, then we can correct this back by putting the points on the street. Luckily there are Algorithms for this, called Map-Matching. There are also a handful of open source systems that do map matching. It remains however difficult to end users to use them, because they involve non-trivial installation and configuration effort. Preparing the base map, which will be used in the matching is also an issue to users. | GPS location tracks typically contain errors, as the GPS points will normally be some meters away from the true position. If we know that the movement happened on a street network, e.g., a bus or a car, then we can correct this back by putting the points on the street. Luckily there are Algorithms for this, called Map-Matching. There are also a handful of open source systems that do map matching. It remains however difficult to end users to use them, because they involve non-trivial installation and configuration effort. Preparing the base map, which will be used in the matching is also an issue to users. | ||
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* [[https://github.com/cyang-kth/fmm|Fast Map Matching]] | * [[https://github.com/cyang-kth/fmm|Fast Map Matching]] | ||
+ | **Status**: taken | ||
===== Geospatial Trajectory Data Cleaning ===== | ===== Geospatial Trajectory Data Cleaning ===== |