Drone Swarm 5G Mapping for Hazardous Unknown Environments
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Solution Overview
Problem
In environments with unknown or outdated layouts, especially those affected by hazardous elements like gases or fires, existing technologies face challenges in efficiently mapping and monitoring these areas due to limitations in drone communication and data processing capabilities.
Innovation Solution
A deployable ad-hoc 5G network is established using master and swarm drones equipped with 5G capabilities, enabling precise location identification and real-time data collection through 5G technologies like millimeter wave and massive MIMO, allowing for accurate mapping and hazard detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional drone communication systems are used in hazardous environments, then device simplicity is maintained, but measurement precision and reliability of mapping data deteriorate
Solution Approach 1:
The patent combines multiple drone units into a swarm that functions as an integrated mapping system. Each drone contributes sensor data and location information to a collective effort, merging individual capabilities into a unified high-precision mapping system that overcomes limitations of single drone operations in hazardous environments.
Solution Approach 2:
The patent introduces a base station as an intermediary that receives data from multiple drones, processes location information using time difference of arrival calculations, and coordinates the swarm's mapping activities. This intermediary enables precise location determination and data consolidation without requiring complex communication between individual drones.
2Productivity
If more drones are deployed to improve mapping coverage and precision, then productivity increases, but device complexity and coordination requirements worsen
Solution Approach 1:
The patent divides the mapping task into segments performed by multiple drones simultaneously. Each drone independently maps a portion of the hazardous environment while the base station coordinates their positions and consolidates data, enabling parallel processing that increases productivity without requiring complex inter-drone coordination.
Solution Approach 2:
Each drone in the swarm autonomously performs its mapping tasks using onboard sensors and navigation, determining its own position through time difference of arrival calculations with the base station. This self-service capability allows drones to operate independently while contributing to the collective mapping effort, reducing coordination overhead.
3Loss of information
If real-time data collection is implemented in hazardous environments, then information completeness improves, but loss of time due to data processing and communication increases
Solution Approach 1:
The patent implements preliminary actions by having drones continuously collect and transmit data in real-time as they navigate hazardous environments. Location information and sensor data are captured and communicated during the mapping process itself, rather than requiring post-mission processing, ensuring data completeness while minimizing time loss through concurrent data collection and transmission.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This solution provides detailed, real-time mapping of physical environments with high precision and reliability, even in hazardous conditions, enhancing safety and efficiency for emergency response and environmental assessment.
Implementation Method 1
determine a location for the swarm drone using differences in time-of-arrival
Data Source
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AI summary
Sets of drones are deployed to create an ad-hoc 5G network in a physical environment to collect sensor data and generate a map of the physical environment in real time. Master drones configured with 5G capabilities are deployed to the physical area to create the 5G ad-hoc network, and swarm drones configured with sensors are deployed to gather environmental data on the physical environment. The gathered data is transmitted to the master drones to generate a map. The deployable 5G network is leveraged to identify precise locations for the swarm drones and each instance of sensor data collected by the swarm drones in order to create an accurate and detailed map of the environment. The map can include information regarding the structural layout of the space and environmental characteristics, such as temperature, the presence of smoke or other gases, etc.