Adaptive Sensor Synchronization via Spatial Grouping
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Solution Overview
Problem
Existing technologies for synchronizing active sensors in real-world environments face challenges such as interference, reduced performance due to multiplexing, and cumbersome data processing, leading to inaccurate and non-immersive collaboration of sensor data.
Innovation Solution
A computer-implemented method and system for location and space aware adaptive synchronization, which tracks device positions and orientations, classifies devices into groups likely to interfere, and controls active sensors to operate using multiplexing only within those groups, thereby optimizing sensor performance and reducing interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If all active sensors are multiplexed to reduce interference, then interference between sensors is reduced, but frame rate and performance of each sensor deteriorates significantly
Solution Approach 1:
The system segments the set of active sensors into multiple groups based on spatial proximity and potential interference. Each group is managed independently with its own multiplexing schedule, allowing sensors in different groups to operate simultaneously at full frame rate while only sensors within the same group are multiplexed to avoid interference.
Solution Approach 2:
The system applies multiplexing locally only to sensors that are in close proximity and likely to interfere with each other, rather than applying it globally to all sensors. Sensors that are far apart or not likely to interfere operate without multiplexing, maintaining their full performance capability.
2Quantity of substance
If active sensors operate simultaneously in the same region, then data collection coverage is improved, but data accuracy and consistency deteriorates due to interference
Solution Approach 1:
The system divides sensors into spatial groups based on their locations and fields of view. Within each group, sensors are coordinated through multiplexing to prevent interference, while maintaining comprehensive coverage across all groups. This segmentation allows the system to preserve both coverage and accuracy.
3Object-affected harmful factors
If multiplexing is applied to all active sensors, then interference is minimized, but system complexity and computational overhead increases
Solution Approach 1:
The system reduces complexity by segmenting sensors into groups and only applying multiplexing within each group rather than across all sensors. This localized approach significantly reduces the computational overhead and synchronization complexity while still preventing interference where it matters.
Data Source
AI summary
Disclosed is a computer-implemented method comprising: tracking positions and orientations of devices (104, 106, 204a-204f, A-F, 402, 404) within real-world environment (300), each device comprising active sensor(s) (108, 110, 206a-206f); classifying devices into groups, based on positions and orientations of devices within real-world environment, wherein a group has devices whose active sensors are likely to interfere with each other; and controlling active sensors of devices in the group to operate by employing multiplexing.