Mobile Image Capture Device Dynamic Sampling for Mapping Data
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Solution Overview
Problem
Existing geo-located image data collection methods are inefficient, as they do not capture data relevant to specific industries' needs, are not up-to-date, and are collected using dedicated vehicles following specific routes, which is not cost-effective compared to vehicles performing other functions.
Innovation Solution
A method using an image capture device with a camera, GPS, compass, and communications module mounted on vehicles or carried by individuals, which captures images based on location and orientation, transmitting data in real-time or periodically, with variable sampling frequency influenced by data density, age, and demand, and utilizes object recognition algorithms to prioritize data capture.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If dedicated vehicles follow specific routes to capture image data, then data coverage is ensured, but cost-effectiveness deteriorates
Solution Approach 1:
The patent applies multi-functionality by enabling ordinary vehicles (taxis, delivery vehicles, personal cars) to serve dual purposes: their primary function (transport, delivery, etc.) and the secondary function of capturing image data for mapping. This eliminates the need for dedicated data collection vehicles, significantly reducing costs while maintaining data coverage through the vehicles' existing route networks.
Solution Approach 2:
The system allows vehicles to autonomously determine whether to capture image data based on their own location, orientation, and the current state of the map database. The vehicle's onboard processor automatically makes capture decisions without external control, enabling self-service data collection that adapts to real-time conditions while reducing operational complexity.
2Loss of information
If image data is captured continuously, then data completeness is improved, but energy consumption increases
Solution Approach 1:
The patent implements dynamic capture decision-making where the vehicle's processor continuously evaluates multiple factors (location, orientation, map data currency, item detection requirements) to determine whether capture is necessary. This dynamic approach adjusts capture frequency based on real-time conditions, ensuring data completeness only where and when needed, thereby minimizing unnecessary energy consumption compared to continuous capture.
Solution Approach 2:
The system changes the parameter of capture frequency from a fixed continuous value to a variable value determined by evaluating multiple conditions. The processor adjusts capture behavior based on parameters such as whether the vehicle is at a location of interest, the age of existing map data, and whether specific items need to be captured, optimizing the balance between data completeness and energy usage.
3Quantity of substance
If generic image data is captured, then data volume is increased, but data relevance to specific industries deteriorates
Solution Approach 1:
The patent applies local quality by making capture decisions specific to particular locations and orientations rather than uniform capture everywhere. The system identifies locations of interest and orientations that capture items of interest, ensuring that image data is captured with specific quality and relevance to industry needs at each location, rather than generic uniform capture.
Solution Approach 2:
The system performs preliminary analysis using object recognition algorithms to identify items of interest before capturing images. By pre-processing data to detect relevant items and determining capture necessity in advance, the system ensures that captured images are relevant to specific industry requirements, filtering out unnecessary data before it consumes storage resources.
4Speed
If capture decisions are made without real-time evaluation, then processing speed is improved, but data relevance deteriorates
Solution Approach 1:
The patent replaces manual or pre-programmed capture decision-making with an automated electronic system that uses object recognition algorithms and real-time data evaluation. The processor automatically analyzes location, orientation, and map data to make capture decisions, substituting mechanical/manual processes with electronic automation that achieves both high processing speed and high data relevance through rapid real-time evaluation.
Data Source
AI summary
A method of collecting visual data using a mobile image capture device is provided. The method comprises the steps of: capturing image data with the mobile image capture device and associating time and location data with each image; and storing the image data and associated time and location data. The method further comprises monitoring the position and orientation of the image capture device. The method further comprises: defining an area surrounding or next to the location of the mobile image capture device; and identifying a characteristic of the defined area based on one or more of: the density of the image data in the area; the age of the image data in the area; and/or data demand values associated with locations within the defined area. The timing of capture of image data is based on the characteristic of the defined area.