Drone Capture Instructions Using User Images and Social Graph Data
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Solution Overview
Problem
Current drone technology faces challenges in efficiently capturing images in diverse scenarios due to regulatory complexities, limited operational flexibility, and high costs, particularly in mass utilization and inhospitable environments.
Innovation Solution
A system comprising a server device that communicates with user and drone devices to provide capture instructions, manage drone registry, and facilitate image sharing, allowing drones to operate autonomously or under operator control, while optimizing resource allocation and reducing the number of drones required for coverage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple drones are deployed to provide coverage for multiple users, then image capture coverage and user service capability are improved, but operational costs and system complexity increase
Solution Approach 1:
The patent implements a drone registry system where a single drone can be registered and made available to multiple users through a server-mediated platform. The drone device can service multiple users sequentially or concurrently, eliminating the need for each user to own or exclusively operate a separate drone. This multi-functionality approach allows one drone to fulfill multiple capture needs across different users and scenarios.
Solution Approach 2:
The server acts as an intermediary between users and drones, managing the registry, matching users with appropriate drones, and coordinating capture instructions. This intermediary layer enables efficient resource allocation where the server can optimize drone deployment based on user needs, drone availability, and capture requirements, reducing the total number of drones needed while maintaining service quality.
2Productivity
If drones operate autonomously without operator control, then operational efficiency and speed are improved, but reliability and safety may deteriorate
Solution Approach 1:
The system implements a dynamic control model where the degree of autonomy is flexible and adaptable. Drones can operate in autonomous mode for routine capture tasks based on server-provided instructions, yet maintain the capability to switch to operator-controlled mode when complex or safety-critical situations arise. This dynamic control architecture allows the system to optimize between efficiency and safety based on real-time conditions.
Solution Approach 2:
The server continuously receives status information from drones and can provide updated capture instructions or intervene when necessary. This feedback loop ensures that autonomous drones remain accountable and can be redirected or stopped if safety concerns arise, maintaining reliability while preserving operational efficiency during normal autonomous operation.
3Measurement precision
If capture instructions are explicitly provided by users, then measurement precision and control are improved, but ease of operation deteriorates
Solution Approach 1:
The server performs preliminary analysis of user needs and drone capabilities before generating capture instructions. By pre-processing capture parameters, geographical areas, and temporal information based on user preferences and contextual data, the system reduces the manual input required from users while maintaining precise capture control. Users provide high-level preferences rather than detailed technical parameters.
Solution Approach 2:
The system enables self-service capture operations where the server automatically generates and transmits capture instructions to the drone based on registered user preferences and contextual information. This automated instruction generation eliminates the need for users to manually configure complex capture parameters, significantly easing operation while maintaining precision through algorithmic optimization of capture settings.
Data Source
AI summary
Methods, Systems, and Devices are disclosed for using drone imaging to capture images. Capture instructions are provided to a drone device to aid in image capture. The capture instructions may include factors-of-interest. The factors-of-interest may include subject faces derived from a collection of images stored at a user device such as a cell phone. The factors-of-interest may also include information derived from images associated with an event, geographical and temporal information associated with the event and social graph information received from a social network and used to determine subject faces to target for image capture by the drone device. The factors-of-interest may also include current geographical location information of one or more friends identified in the social graph. This information may also be used to locate subjects for image capture. The social graph information may also be used to distribute any images captured to subjects appearing in those images.