Light Sensor Wakes Camera to Save Battery
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Solution Overview
Problem
Battery-operated surveillance cameras face challenges in maintaining long battery life while continuously monitoring and communicating, as they lack the power budget to operate continuously without sacrificing battery life, especially when integrated with power-demanding analytics and AI.
Innovation Solution
Integration of a low-power, low-resolution light detecting sensor that operates independently to detect movement and conserve battery life by waking up the high-resolution sensor only when user-defined criteria are met, optimizing battery life and reducing false notifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the high-resolution sensor operates continuously to maintain monitoring capability, then detection accuracy is improved, but battery life deteriorates
Solution Approach 1:
The monitoring system is segmented into two functional layers: a low-power light detecting sensor for continuous motion detection and a high-resolution camera sensor for detailed image capture. This segmentation allows each component to operate at its optimal power consumption level, with the light sensor continuously monitoring for motion while the camera only activates when motion is detected, thus resolving the contradiction between continuous monitoring accuracy and battery life.
Solution Approach 2:
The high-resolution camera operates periodically rather than continuously, activating only when the light detecting sensor detects motion. This periodic operation pattern significantly reduces power consumption while maintaining effective monitoring capability, as the camera captures detailed images only when necessary rather than continuously consuming power.
2Reliability
If the camera operates continuously to detect movement and send notifications, then monitoring reliability is improved, but power consumption increases
Solution Approach 1:
The light detecting sensor serves as an intermediary component between the environment and the high-resolution camera. It pre-processes the monitoring task by detecting motion and filtering out non-critical events, allowing the power-intensive camera to remain dormant until needed. This intermediary layer maintains monitoring reliability by ensuring the camera captures images only when actual motion occurs, while dramatically reducing overall power consumption.
Solution Approach 2:
Instead of using the full-capability camera for all monitoring tasks, the system applies partial action by using only the light-detecting capability of the sensor for continuous monitoring and reserving the full camera functionality for specific moments when motion is detected. This partial utilization of the camera's capabilities maintains reliability for critical events while avoiding excessive power consumption during idle periods.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This solution extends battery life by minimizing unnecessary power consumption and reducing false notifications, allowing battery-operated cameras to effectively monitor and communicate without frequent battery replacements, while maintaining accurate detection of human and animal movement.
Implementation Method 1
a camera that is configured to generate first image data at a first time... the camera is further configured to generate second image data at a second, later time
Data Source
AI summary
A method includes generating, by a camera of a monitoring system that is configured to monitor a property, first image data at a first time, analyzing the first image data, determining that the first image data includes a first object that likely corresponds to a person, generating, second image data at a second, later time, analyzing the second image data, determining that the second image includes a second object that likely corresponds to a person, comparing the first object that likely corresponds to a person to the second object that likely corresponds to a person, based on comparing the first object that likely corresponds to a person to the second object that likely corresponds to a person and based on a difference between the first time and the second, later time, determining that a person is likely moving towards the camera, and performing a monitoring system action.