Doorbell Device Local Image Matching for Latency Reduction
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Solution Overview
Problem
Existing doorbell systems consume significant time and processing power by remotely processing ambient images against large databases to identify relevant individuals, leading to latency and security vulnerabilities.
Innovation Solution
A doorbell device with a processor, local memory, and camera that compiles a custom image database with user-inputted images, allowing for local matching of ambient images against this database without cloud server communication, using extracted features and facial recognition characteristics via an artificial intelligence model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If remote cloud server processing is used to identify individuals in ambient images, then comprehensive database matching capability is improved, but processing time and latency increase significantly
Solution Approach 1:
The patent segments the image database into two parts: a compressed subset stored locally in the doorbell device for quick matching, and a complete database stored remotely in the cloud for comprehensive matching. This segmentation allows the system to perform rapid local identification while maintaining the option for thorough remote verification when needed.
Solution Approach 2:
The patent performs preliminary action by pre-compressing and storing a subset of the image database locally in the doorbell device before runtime. This preparation enables the device to conduct immediate local matching without requiring real-time cloud communication, thus reducing latency for common identification scenarios.
2Adaptability or versatility
If remote cloud server processing is used for image identification, then comprehensive database access is improved, but security vulnerabilities increase due to cloud disconnection risks
Solution Approach 1:
The patent segments database functionality by maintaining both local and remote database capabilities. The local subset enables the doorbell device to function independently for identification purposes even when cloud connection is unavailable or attempted to be severed, while the remote database remains available for enhanced matching when connected.
Solution Approach 2:
The patent implements self-service by enabling the doorbell device to perform image matching autonomously using its locally stored compressed database subset. This self-sufficient capability allows the device to maintain security and identification functionality without relying on continuous cloud server communication.
3Measurement precision
If large unrestricted databases are processed remotely, then identification accuracy is improved, but processing power consumption increases
Solution Approach 1:
The patent segments the database into a compressed local subset and a complete remote database, enabling the system to perform rapid low-power matching locally for common cases while reserving high-power remote processing for situations requiring comprehensive database searching.
Solution Approach 2:
The patent applies partial action by using only the necessary portion of the database (local subset) for routine identification tasks, consuming minimal processing power. The complete database is accessed remotely only when local matching fails or enhanced verification is needed, optimizing the balance between accuracy and power consumption.
Data Source
AI summary
Systems and methods for identifying user-customized relevant individuals in an ambient image at a doorbell device are provided. Such systems and methods can include receiving user input that includes image information, using the image information to compile a custom image database containing a plurality of images that depict such relevant individuals, and storing the custom image database in local memory of the doorbell device. Then, such systems and methods can include capturing an ambient image with a camera of the doorbell device, determining whether any person depicted in the ambient image matches any of the relevant individuals by comparing the ambient image to the plurality of images at the doorbell device, and generating an alert when any person depicted in the ambient image matches any of the relevant individuals.