The world of massive GPS tracking and spatiotemporal data analysis is rapidly evolving. A lot of companies that have a large fleet with GPS tracking have experienced the hectic changes and challenges in their businesses when it comes to the GPS tracking of more than 20.000 vehicles. Getting deep insights into spatiotemporal data within a few seconds, regardless of data size, became the first world problem number one. What was required for these companies last year may not be what they need this year. How does the automotive industry meet these new sophisticated challenges and stay competitive?
This chapter provides an in-depth description of using spatiotemporal data in our everyday lives. Several typical examples of spatiotemporal Big Data use cover topics about safety public transport tracking on a large scale based on India AIS-140 case, reducing traffic congestion, and usage-based insurance.
Existing telematics solutions often have big problems with a lack of flexibility, expensive scalability, poor precision, and poor responsiveness. Customers are usually looking for an all-in-one solution with an emphasis on real-time data analysis. A brief overview of the issues among commercially available solutions reveals which of them are fully covered within the SpaceTime solution.
Several different technologies can be used in working with big geospatial data. This chapter provides a systematic overview of the existing spatiotemporal data analysis solutions — detailed information with proofs about why is SpaceTime solution more powerful and efficient than competitors.
SpaceTime is a software platform for storing and processing geotagged and timestamped data. It can collect an enormous amount of data and get real-time analysis for an unlimited number of vehicles. For a better understanding of our spatiotemporal data analyzing solution, the way how does SpaceTime works is described in detail.
We are taking benefit of the global positioning technology to provide organizations and individuals travel on roads easier, safer, and more efficient. To enhance understanding of our work, this section provides a snapshot of the most popular terms we use in our everyday life at Mireo.
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Existing telematics solutions provide customers with many various reports. However, adding new reports is an expensive and long-lasting process. Customers would like to have a solution where they can generate any report almost in real-time. They don't want to have some predefined reports, and they don't want to depend on anybody if there is a need for change.
Reports should be generated instantly to provide the customers with a great user experience. Existing telematics solutions often have big problems with creating real-time reports. In some cases and industries, real-time reporting is crucial, so poor responsiveness is not an option.
Usually, fleet management solutions handle spatiotemporal data from less than 20.000 vehicles perfectly. Adding new vehicles into the GPS tracking system with more than 20.000 vehicles is hard, and in most cases, it doesn't work well. Analytical processing of data would eventually require exponentially more time as the data are inserted, and the number of records surpasses a few billion. In that case, customers typically use more than one fleet management solution, which at some point can become hard to handle. Customers are looking for a solution where scalability could ensure simultaneous tracking, real-time analysis, and reporting for an unlimited number of objects. To clarify why is the scalability of crucial importance for all systems which are processing data produced by moving objects, we wrote a more detailed blog article that can be found here.
GPS satellites broadcast their signals in space with precise accuracy. But many things can reduce GPS positioning accuracies, such as atmospheric conditions or satellite signal blockage due to buildings, bridges, etc. GPS is accurate to within 5 meters 95% of the time. The problem is the remaining 5% because customers need correct information, not just indications. It is up to fleet management provider to process GPS data and reconstruct trajectories precisely and accurately.
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SpaceTime is a software platform for storing and processing spatiotemporal (geotagged and timestamped) data collected from GPS tracking devices. SpaceTime can track data from any kind of moveable object (vehicles, humans, etc.), although here in Mireo, we mostly work with tracking data gathered from vehicles. The design of the system allows scaling to the size which handles simultaneous tracking and real-time analysis for an unlimited number of vehicles.
SpaceTime Cluster is an Automatic Vehicle Location (AVL) tracking system for monitoring, detailed behavioral analysis, and management of moveable objects. It uses a GSM radio packet network for communication with tracking devices in moveable objects. SpaceTime Cluster collects and stores data into a SpaceTime database in real-time. It also keeps historical objects' records for an indefinite time.
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