Location-Based Video Analytics for Mobile Security Cameras
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Solution Overview
Problem
Existing mobile security devices lack effective methods and systems for performing suitable video analytics in diverse environments, such as drones operating indoors and outdoors, requiring improved algorithms and systems for various surveillance tasks.
Innovation Solution
Mobile security devices, like drones, are equipped with video cameras and position sensors to determine their location and select appropriate video analytics algorithms based on predefined coordinates or regions, enabling on-device or cloud-based processing of captured video to perform analytics efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single video analytics algorithm is used for all environments, then the system is simple to operate, but the detection accuracy decreases in specific locations
Solution Approach 1:
The system dynamically selects video analytics algorithms based on the mobile device's current location. The controller determines the device position using position sensors and automatically switches between different analytics algorithms (e.g., people counting indoors, vehicle detection outdoors) without requiring manual intervention, thus adapting to changing environments while maintaining operational simplicity
Solution Approach 2:
Different video analytics algorithms are applied to different geographic locations. The system associates specific analytics algorithms with predefined locations or regions, ensuring that the most appropriate algorithm is used for each specific environment (indoor facilities, outdoor areas, parking lots, etc.), thereby optimizing detection accuracy for local conditions
2Measurement precision
If multiple video analytics algorithms are stored and executed, then detection accuracy for different environments improves, but the device complexity increases
Solution Approach 1:
The controller automatically performs algorithm selection based on position data without requiring user input or manual configuration. The system self-manages the complexity by autonomously determining which analytics algorithm to execute based on the current location, freeing the user from dealing with algorithm selection complexity while still providing multiple specialized algorithms
Solution Approach 2:
Multiple video analytics algorithms are pre-loaded and stored in the device memory before operation. The system prepares various specialized algorithms (people counting, vehicle detection, crowd analysis, etc.) in advance, so that when the device reaches a specific location, the appropriate pre-prepared algorithm can be immediately activated without delay or manual setup
Data Source
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AI summary
A mobile security device such as a drone includes a video camera, a memory that is configured to store a plurality of video analytics algorithms, a position sensor, a transceiver and a controller. The controller is configured to determine a position of the mobile security device based on information provided by the position sensor and to select one or more video analytics algorithms of the plurality of video analytics algorithms based at least in part upon the determined position of the mobile security device. The controller is configured to instruct the video camera to capture video and to perform the selected one or more video analytics algorithms on the captured video, resulting in one or more video analytics results. The controller is configured to transmit one or more of the video analytics results to a remote device via the transceiver.