Drone Parking and Charging Allocation for Secure Ground Operations
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Solution Overview
Problem
Current drone equipment operators face challenges in managing the logistical needs of drone maintenance, charging, and storage, as there are no integrated facilities that provide comprehensive solutions for parking, charging, and maintenance services, similar to those available for automotive vehicles.
Innovation Solution
A system comprising network equipment with a processor, memory, and sensors that identifies drone equipment, allocates parking and charging spaces, and provides secure storage, using computer vision-based AI and multiparty blockchain verification to manage drone operations, including charging, maintenance, and cargo handling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If integrated facilities for drone parking, charging, and maintenance are introduced, then operational efficiency and service completeness are improved, but system complexity and infrastructure investment increase
Solution Approach 1:
The patent combines multiple drone support functions (parking, charging, maintenance, storage) into integrated ground stations and aerial ports. These facilities serve multiple purposes simultaneously - for example, ground stations provide both charging and maintenance capabilities, while aerial ports handle both docking and cargo operations. This merging of functions resolves the contradiction by achieving high operational efficiency through service integration while managing system complexity through standardized multi-functional platforms.
Solution Approach 2:
The ground stations and aerial ports are designed as universal facilities that can serve multiple drone types and operations. The system provides adaptable charging interfaces, standardized maintenance bays, and flexible storage solutions that work across different drone configurations. This multi-functionality improves productivity by allowing single facilities to handle diverse operations while avoiding the complexity of specialized infrastructure for each function.
2Reliability
If comprehensive monitoring and verification systems are implemented, then security and operational reliability are improved, but device complexity and computational requirements increase
Solution Approach 1:
The system implements continuous monitoring with real-time feedback loops. Ground stations and aerial ports constantly track drone status, charging levels, and operational parameters, providing feedback to both the drones and operators. Blockchain verification creates immutable feedback records of all transactions and operations. This feedback mechanism improves reliability by enabling proactive issue detection and resolution while managing complexity through automated monitoring rather than manual oversight.
Solution Approach 2:
The patent introduces blockchain technology as an intermediary layer that mediates between drones, ground stations, and operators. The blockchain network verifies transactions, records operations, and ensures security without requiring direct complex interactions between all system components. This intermediary approach improves reliability through tamper-proof verification while reducing overall system complexity by centralizing trust management in the blockchain protocol rather than in individual system components.
3Productivity
If automated allocation and management systems are deployed, then resource utilization and operational speed are improved, but computational requirements and system complexity increase
Solution Approach 1:
Drones are equipped with autonomous capabilities to self-manage their operations. The system automatically allocates charging slots, schedules maintenance, and manages cargo without requiring constant operator intervention. Drones can independently navigate to ground stations, initiate charging sequences, and report their status. This self-service approach improves resource utilization and operational speed while managing computational complexity by distributing intelligence to the drones themselves rather than requiring centralized control of all decisions.
Solution Approach 2:
The system performs preliminary allocation and preparation actions before drones arrive at facilities. Ground stations pre-configure charging parameters based on drone specifications, prepare maintenance equipment in advance, and allocate optimal parking positions. This preliminary action improves resource utilization by ensuring facilities are ready when drones arrive, reducing wait times. Computational complexity is managed by performing calculations in advance when information is available rather than making complex decisions in real-time under pressure.
Data Source
AI summary
An architecture to provision one-stop parking, charging, storage, and/or maintenance facilities and/or functionalities for drone equipment. A method can comprise identifying a drone entering a defined airspace monitored by the network equipment; in response to establishing a communication channel with the drone, receiving data representing a physical dimension associated with the drone; based on the physical dimension associated with the drone, allocating a space within a defined area to which the drone is to navigate and then cease moving; and sending, to the drone via the communication channel, notification data that notifies the drone to navigate to the space.