Cloud-Connected Drone Inspection With Real-Time Mission Feedback
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Solution Overview
Problem
Human surveyors face challenges in inspecting hazardous or hard-to-reach assets due to limitations in adaptability and data collection capabilities of conventional unmanned systems, which are limited by onboard processing power and lack of real-time command and control feedback.
Innovation Solution
Implementing cloud-based connectivity for unmanned vehicles to enable real-time data exchange and command/control operations, utilizing extended computational power for complex simulations and machine learning, and providing remote operation services through a server that connects with the vehicle for enhanced mission control and data validation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If conventional unmanned systems are used for inspections, then human safety is improved by eliminating surveyors from hazardous environments, but the system's adaptability and data collection capabilities deteriorate due to limited onboard processing power
Solution Approach 1:
A cloud-based server acts as an intermediary between the drone and the operator, receiving real-time sensor data from the drone, performing complex simulations and machine learning analysis, then sending back operational instructions. This mediator enables the drone to access extended computational power without carrying it onboard, resolving the contradiction between safety (keeping human away) and adaptability (needing smart processing).
Solution Approach 2:
The system moves computational processing from the physical dimension (onboard drone hardware) to the cloud dimension (remote server infrastructure). By transitioning to another dimension of computation, the drone gains access to unlimited processing power and adaptability while maintaining its lightweight, mobile form factor for safe operation in hazardous environments.
2Extent of automation
If cloud-based connectivity is implemented for real-time data exchange, then decision-making capabilities are improved, but device complexity increases due to additional communication infrastructure
Solution Approach 1:
The system implements self-service by having the cloud server automatically perform simulations, analyze sensor data, and generate operational instructions without human intervention. The server autonomously processes the data exchange between drone and operator, improving decision-making capabilities while the complexity is managed automatically rather than requiring complex manual configuration.
3Reliability
If real-time operational data is collected and processed, then operational reliability is improved, but data transmission requirements and system complexity increase
Solution Approach 1:
The system extracts complex data processing and simulation tasks from the drone itself and relocates them to the cloud server. Only essential sensor data needs to be transmitted from the drone, while the heavy computational work is performed remotely. This extraction maintains operational reliability through thorough analysis while minimizing the data transmission burden and system complexity on the drone side.
Data Source
AI summary
Aspects of the current subject matter relate to enhanced operation services provided by an unmanned vehicle with cloud-based connectivity for real-time exchange of data and command/control operations. Data collected during a mission for an operation service, such as a particular inspection activity, is transmitted in real-time to a server for analysis to provide real-time or near real-time feedback in the form of command and/or control signals to the unmanned vehicle to improve the operation service while it is being carried out. The collected data is also used for simulations and to create historical content for future operation services.