Grid-Based Proximity Monitoring for Scalable Device Notifications
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Solution Overview
Problem
Existing proximity monitoring systems face significant computational demands and delays when scaling to large numbers of objects, making it impractical to generate notifications on personal computing devices and reducing system performance.
Innovation Solution
A method and system that define subspaces using a grid to determine the proximity of objects, allowing devices to subscribe to and publish their presence within these subspaces, thereby eliminating the need for distance calculations and reducing computational requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing systems calculate the distance between a given object and all other objects to generate proximity notifications, then proximity monitoring can be performed, but computational demand increases significantly when scaled to systems with many objects
Solution Approach 1:
The system divides the spatial environment into discrete grid cells. Instead of calculating distances between all object pairs, each object is assigned to a grid cell based on its location. Objects only need to check for proximity with other objects in the same or adjacent grid cells, dramatically reducing computational complexity from O(n²) to approximately O(n/k) where k is the average number of objects per cell.
2Measurement precision
If distance calculations are performed for all object pairs to ensure accurate proximity detection, then notification accuracy is maintained, but system performance and response time deteriorate
Solution Approach 1:
The system applies different processing strategies to different spatial regions. Objects in the same grid cell undergo detailed proximity checks, while objects in different cells are handled through grid cell comparisons. This localized approach maintains notification accuracy for nearby objects while improving overall system performance by avoiding unnecessary distance calculations for distant objects.
3Quantity of substance
If proximity monitoring is scaled to systems with large numbers of devices, then coverage and utility increase, but computational requirements become unsustainable for personal computing devices
Solution Approach 1:
The grid cell structure acts as an intermediary data structure between objects. Instead of objects directly interacting with all other objects, they interact through their grid cell assignments. The device manager uses grid cell information to efficiently determine which objects need to be compared, enabling the system to scale to large numbers of devices while keeping computational requirements manageable for personal computing devices.
Data Source
AI summary
A method of monitoring the proximity of two or more monitoring devices. The method includes defining a series of subspaces within the space containing the devices and determining the subspace containing the location of each device. The method also includes subscribing each device to one or more subspaces and publishing the presence of each device to other devices that are subscribed to the subspace containing the device's location. The series of subspaces are defined by a grid.