Time-Geospatial Tile Structure for Low-Latency Interactive Maps
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Solution Overview
Problem
Conventional systems and methods are inefficient in processing and displaying large amounts of streamed geospatial data in real-time without latency, particularly in interactive maps that support temporal and spatial zooming.
Innovation Solution
The system employs an application server to generate and store multi-dimensional tiles based on temporal and geospatial information, allowing for efficient processing and display of time-related geospatial data on interactive maps with low latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional mapping applications process large amounts of streamed geospatial data in real-time, then the amount of data to be processed, stored and analyzed increases, but the system demand on input/output, bandwidth and processing time increases significantly causing inefficiency and inability to process data with low latency
Solution Approach 1:
The patent segments geospatial data into hierarchical levels (e.g., country-level, state-level, county-level, city-level, neighborhood-level, building-level) with varying degrees of detail. This segmentation allows the system to process and transmit only the necessary level of detail for each query, significantly reducing data volume and processing time while maintaining productivity.
Solution Approach 2:
The patent introduces a temporal dimension to the geospatial data structure, organizing data not only by spatial hierarchy but also by time periods. This multi-dimensional organization enables efficient querying of historical data without requiring processing of all available data, thus reducing latency while maintaining high productivity in processing time-related geospatial queries.
2Loss of information
If conventional systems display all available geospatial data on interactive maps, then the completeness of information is improved, but the system demand on input/output and bandwidth increases significantly
Solution Approach 1:
The patent applies local quality by providing different levels of data detail for different spatial regions. High-level aggregate data is provided for broad regions, while detailed data is provided only for specific areas of interest or higher hierarchical levels. This ensures data completeness where needed while minimizing bandwidth consumption in other areas.
Solution Approach 2:
The system implements partial action by transmitting only the subset of geospatial data necessary for the current query and display requirements, rather than all available data. The hierarchical structure allows the system to provide sufficient information for each level without excessive data transmission, balancing completeness with bandwidth efficiency.
3Adaptability or versatility
If conventional mapping applications store all historic geospatial data for querying, then the ability to query historic data is improved, but the storage requirements and processing time to retrieve specific historic data increases
Solution Approach 1:
The patent segments historic data by time periods and spatial hierarchies, organizing data into manageable chunks rather than storing all data in a single structure. This segmentation enables efficient retrieval of specific historic periods and regions without requiring access to the entire dataset, reducing storage complexity while maintaining versatile query capabilities.
Solution Approach 2:
By adding temporal dimension to the hierarchical structure, the system can efficiently organize and retrieve historic data across multiple time periods. This multi-dimensional organization allows queries to target specific time ranges and spatial levels independently, enhancing adaptability for historic data analysis while managing storage complexity through structured organization.
Data Source
AI summary
System and method for processing time-related geospatial data from one or more data sources. For example, a system includes an application server; and a storage. The application server is configured to: receive data including temporal information and geospatial information for each data object of one or more data objects, send the data to a client device to display the data on a map, and generate one or more first multi-dimensional tiles based at least in part on the temporal information and the geospatial information. The one or more first multi-dimensional tiles correspond to a temporal dimension associated with a first temporal width. The application server is further configured to send the one or more first multi-dimensional tiles to store in the storage for retrieval by the client device.