Surveillance Device Edge Processing Bandwidth Optimization
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Solution Overview
Problem
Smart home surveillance systems face challenges in reducing transmission bandwidth, response time, and power consumption due to large image data, which often requires sacrificing visual verification accuracy and increasing false alarm probabilities.
Innovation Solution
The implementation of edge computing in surveillance devices, which processes images locally to determine object presence, adjusts image capture and transmission parameters, and prioritizes transmission of high-resolution images containing detected objects, thereby reducing bandwidth, time, and power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all captured images are transmitted to the CMS or end user for visual verification, then visual verification accuracy is maintained, but transmission bandwidth consumption increases and response time increases
Solution Approach 1:
The patent extracts and transmits only the essential information (detected objects) from the captured images rather than transmitting the entire image data. The surveillance device identifies and extracts object information, then transmits only this extracted data to the CMS or end user, significantly reducing transmission bandwidth while maintaining visual verification accuracy.
Solution Approach 2:
The patent creates a simplified copy or representation of the image data by generating thumbnails or reduced-resolution versions of detected objects for transmission. Instead of transmitting full-resolution images, the system creates condensed copies that convey the essential visual information with much lower bandwidth requirements.
2Measurement precision
If all captured images are transmitted for visual verification, then detection accuracy is maintained, but response time increases
Solution Approach 1:
The patent performs preliminary processing of images at the surveillance device before transmission. The system pre-identifies and pre-extracts object information from captured images, preparing the data in advance for transmission. This preliminary action at the edge device reduces the processing time required at the CMS and accelerates overall response time.
Solution Approach 2:
The system extracts only the relevant object information from full images before transmission, sending only the essential detected elements rather than complete image data. This extraction process reduces the amount of data that needs to be transmitted and processed, thereby reducing response time while maintaining detection accuracy.
3Measurement precision
If high-resolution images are transmitted frequently, then visual verification quality is maintained, but power consumption increases
Solution Approach 1:
The patent applies different quality levels to different parts of the image data based on local requirements. High-resolution data is transmitted only for detected objects where visual verification is critical, while other areas use lower resolution or are omitted entirely. This localized quality adjustment maintains verification quality where needed while reducing overall power consumption.
Solution Approach 2:
The system transmits only the partial information necessary for effective visual verification - specifically, only the detected objects rather than complete high-resolution images. This partial action approach provides sufficient verification quality for security purposes while dramatically reducing the energy required for image transmission and processing.
4Productivity
If fewer images are transmitted to reduce bandwidth consumption, then transmission efficiency improves, but visual verification accuracy decreases
Solution Approach 1:
The patent extracts the most critical visual information (detected objects) from the captured images and transmits this extracted data. By taking out only the essential object information rather than transmitting fewer complete images, the system maintains visual verification accuracy while achieving high transmission efficiency through reduced data volume.
Solution Approach 2:
The system changes the parameter of image data representation by converting full images into extracted object information or thumbnails. This parameter transformation allows the transmission of condensed data that preserves verification accuracy while dramatically improving transmission efficiency through reduced bandwidth consumption.
Data Source
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AI summary
A security system includes a surveillance device that monitors a predetermined event and captures images in a monitor scene; and a controller that controls the surveillance device and transmits the captured images. The surveillance device adjusts image capture amount, image transmit amount, image transmit order or image resolution when the predetermined event is detected and an object is detected on the captured images.