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teaching:projh402 [2020/10/03 18:20] ezimanyi [VODKA Indexes for MobilityDB] |
teaching:projh402 [2020/10/22 14:18] ezimanyi [Visualization of Moving Objects on the Web] |
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| However, these platforms are used for static spatial data and are unable to cope with moving objects. The goal of the project is to extend one of these platforms with spatio-temporal data types in order to be able to display animated maps. | However, these platforms are used for static spatial data and are unable to cope with moving objects. The goal of the project is to extend one of these platforms with spatio-temporal data types in order to be able to display animated maps. | ||
| + | {{:teaching:trips2.gif?direct|}} | ||
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| + | Animated visualization of car trajectories | ||
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| + | **Status**: taken | ||
| ===== Implementing TSBS on MobilityDB ===== | ===== Implementing TSBS on MobilityDB ===== | ||
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| ===== 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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| + | {{:teaching:original.png?direct&400|}} | ||
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| + | Original trajectory | ||
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| + | {{:teaching:mapmatched.png?direct&400|}} | ||
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| + | Map-matched trajectory | ||
| The goal of this project is to build an architecture for a Map-Matching service. The challanges are that the GPS data arrives in different formats, and that Map-Matching is a time consuming Algorithm. This architecture should thus allow different input formats, and should be able to automatically scale according to the request rate. Another key outcome of this project is to compare the existing Map-Matching implementations, and to discuss their suitability in real world problems. | The goal of this project is to build an architecture for a Map-Matching service. The challanges are that the GPS data arrives in different formats, and that Map-Matching is a time consuming Algorithm. This architecture should thus allow different input formats, and should be able to automatically scale according to the request rate. Another key outcome of this project is to compare the existing Map-Matching implementations, and to discuss their suitability in real world problems. | ||