AI Skyway Control for Congested Flying Vehicle Airspace
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Solution Overview
Problem
The increasing use of flying vehicles poses challenges in managing air traffic congestion and ensuring safety in congested airspace, with potential for physical harm and property damage.
Innovation Solution
An artificially intelligent air traffic control system utilizing AI sensors, local and cloud servers, and AI SIM cards to detect, authorize, and control flying vehicles, employing blockchain technology for verification and e-commerce for transactions, with deep learning and machine learning to manage traffic and prevent unauthorized access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the number of flying vehicles increases to provide widespread benefits, then productivity and service coverage improve, but air traffic congestion and safety risks worsen
Solution Approach 1:
The air traffic control system is segmented into multiple components: AI sensors for detection, local servers for regional coordination, and cloud servers for centralized management. This segmentation allows the system to handle increasing numbers of flying vehicles by distributing control functions across multiple nodes, thereby improving service coverage while managing congestion through decentralized processing.
Solution Approach 2:
The AI-based air traffic control system acts as an intermediary between flying vehicles and airspace management. The system uses AI sensors to detect vehicles, processes their information through local and cloud servers, and coordinates their movement to prevent congestion and safety incidents, thereby enabling widespread vehicle deployment without proportionally increasing risks.
2Reliability
If AI sensors and servers are deployed to detect and control flying vehicles, then safety and traffic management improve, but system complexity increases
Solution Approach 1:
The AI sensors and servers are designed with multi-functionality to handle various tasks including detection, tracking, authorization, and control of flying vehicles. This universal design reduces the need for separate specialized systems, thereby improving safety through comprehensive monitoring while managing complexity through consolidated multi-purpose components.
Solution Approach 2:
The system performs preliminary actions by pre-authorizing flying vehicles before they enter controlled airspace and pre-planning their flight paths. This advance coordination allows the system to maintain high safety standards through proactive management while reducing real-time complexity by resolving conflicts and coordinating movements before vehicles encounter each other.
3Productivity
If real-time detection and control of multiple flying vehicles is implemented, then traffic management effectiveness improves, but processing time and computational requirements increase
Solution Approach 1:
The system segments processing tasks between local servers that handle real-time detection and immediate control responses, and cloud servers that manage less time-critical functions like authorization verification and flight path optimization. This segmentation enables effective traffic management through distributed processing while reducing overall processing time by handling critical functions locally without waiting for centralized computation.
Data Source
AI summary
An artificially intelligent air traffic control system is provided. The system can include an artificially intelligent (AI) sensor configured to detect and remotely communicate with one or more flying vehicles and an AI local server communicatively coupled to the AI sensor. The artificially intelligent local server can send control instructions including authorization for the one or more flying vehicles to fly in an airspace and a flight path to fly through the airspace. The system can also include an AI cloud server communicatively coupled to the AI local server. The AI cloud server can receive data from the AI local server and the AI sensor associated with the one or more flying vehicles. The AI local server can send the authorization and the flight path to the one or more flying vehicles via the AI sensor based on the received data stored on the AI cloud server.