Doorbell Camera Package Detection via Computer Vision
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Solution Overview
Problem
Current package delivery and pick-up services lack security, leading to issues such as improper notifications, delayed notifications, theft, and failure to inform users about package details like delivery person, size, and timeliness.
Innovation Solution
The implementation of a camera-based system that uses computer vision technology to detect packages and individuals through image analysis, recognizing visual parameters like shape, color, texture, and motion, and sends notifications based on probability thresholds, with the ability to monitor and prevent unauthorized interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a camera-based system with computer vision is implemented to detect packages and send notifications, then package security and notification accuracy are improved, but device complexity and cost increase
Solution Approach 1:
The patent replaces manual package monitoring and notification systems with an automated computer vision system using cameras and image analysis algorithms. The system automatically detects packages, identifies their characteristics, and sends notifications without human intervention, thereby improving reliability while the automation handles the complexity internally.
Solution Approach 2:
The system performs self-monitoring and self-notification functions. The camera system automatically detects package events and generates notifications without requiring external security personnel or manual checking, making the system self-sufficient and improving reliability through continuous automated surveillance.
2Measurement precision
If image analysis is performed on multiple parameters (shape, color, texture, motion) to accurately identify packages, then detection accuracy is improved, but processing time and computational resources increase
Solution Approach 1:
The system analyzes multiple image parameters (shape, color, texture, motion) simultaneously to achieve high detection accuracy. By performing comprehensive multi-parameter analysis rather than sequential or partial analysis, the system maintains high precision while optimizing processing efficiency through parallel evaluation of all relevant visual characteristics.
3Reliability
If the system monitors packages for unauthorized interaction and sends notifications based on probability thresholds, then package protection is improved, but false positives and notification errors may increase
Solution Approach 1:
The system uses probability thresholds to evaluate package events and determines whether to send notifications based on assessed risk levels. This feedback mechanism allows the system to adjust its notification behavior based on the confidence level of detected events, improving package protection while reducing false positives by only notifying when probability thresholds are confidently exceeded.
Data Source
AI summary
A method for security and/or automation systems is described. In one embodiment, the method includes identifying image data from a signal, analyzing the image data based at least in part on a first parameter, identifying a presence of an object based at least in part on the analyzing, and detecting an object event based at least in part on the identifying.