Crowd-Sourced Asset Monitoring via Beacon-Triggered Image Capture
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Solution Overview
Problem
The increasing prevalence of IoT devices in public spaces necessitates a mechanism for periodic monitoring of the status and quality of deployed assets, products, and structures, as well as the IoT devices themselves, which current fixed security cameras cannot effectively address.
Innovation Solution
A system utilizing broad and aimable beacons to crowdsource image capture from opted-in user devices, allowing for periodic monitoring of assets and structures by capturing images from various angles and perspectives, which can be stored and analyzed over time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If fixed security cameras are used for monitoring, then continuous surveillance is achieved, but device complexity and installation cost increase
Solution Approach 1:
The patent enables ordinary user devices to automatically serve as monitoring cameras when they detect beacons and opt-in to capture images, eliminating the need for dedicated fixed camera installations. Users' devices self-organize into a distributed monitoring network through beacon detection and automated enrollment processes.
Solution Approach 2:
The system allows ordinary mobile devices to perform multiple functions: daily computing tasks and periodic monitoring capture. The same device serves both general-purpose computing and specialized monitoring roles, eliminating the need for dedicated monitoring hardware.
2Area of stationary object
If fixed security cameras are deployed throughout public spaces, then comprehensive coverage is achieved, but loss of time for installation and maintenance increases
Solution Approach 1:
The monitoring network transitions from static fixed installations to dynamic mobile participants. Devices move freely through public spaces, automatically enrolling when detecting beacons and capturing images at varying locations, providing flexible coverage without permanent installations.
Solution Approach 2:
The system divides the monitoring function across numerous individual mobile devices rather than relying on few fixed cameras. Each device independently captures images when encountering beacons, collectively providing comprehensive area coverage through distributed participation.
3Measurement precision
If more monitoring devices are deployed, then measurement precision and coverage improve, but use of energy and operational cost increase
Solution Approach 1:
Instead of continuous operation, devices perform monitoring captures periodically when they encounter beacons in their natural movement patterns. This event-driven approach replaces constant energy consumption with intermittent capture based on beacon detection events.
Solution Approach 2:
The system uses existing mobile devices that users already possess and operate, rather than deploying additional specialized monitoring hardware. These existing devices are copied across the population, leveraging their built-in cameras and processing capabilities without requiring new energy-intensive infrastructure.
Data Source
AI summary
A method, computer system, and computer program product for utilizing crowdsourcing of images captured by individuals to determine the status of a subject is provided. The embodiment may receive, by a processor associated with a broad beacon, an impulse. The embodiment may also transmit a request to each client device within a preconfigured distance through the broad beacon based on the received impulse. The embodiment may further, in response to an acceptance of the transmitted request by a user associated with a client device, initializing a pairing sequence between the client device and an aimable beacon. The embodiment may also transmit information to identify a subject of photographic capture from the aimable beacon to the client device. The embodiment may further receive an image captured by the user based on the received information.