Drone Line-of-Sight Control Using Wearable Location Tracking
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Solution Overview
Problem
Current drone technologies lack effective methods to ensure continuous line-of-sight between drones and humans, particularly in dynamic environments, which is crucial for safety regulations and tracking applications.
Innovation Solution
The system employs drones equipped with sensors and wearable devices that use GPS, beacons, and image sensors to determine and maintain line-of-sight, with a computing platform that processes data to control the drone's movement and trigger alerts based on predefined rules, ensuring the drone remains within visual range of the human.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If drones are used for tracking and monitoring individuals, then productivity and monitoring capability are improved, but reliability of maintaining continuous line-of-sight deteriorates in dynamic environments
Solution Approach 1:
The system continuously receives location information from wearable devices and uses this feedback to dynamically adjust drone positioning. The computing platform processes real-time location data and sends control signals to move the drone toward individuals when line-of-sight is lost, creating a closed-loop control system that maintains reliable monitoring in dynamic environments.
Solution Approach 2:
The drone operates autonomously by receiving control signals based on processed location data without requiring constant manual intervention. The system automatically determines when line-of-sight is lost and directs the drone to reposition itself to restore visual contact, enabling self-correcting monitoring capability.
2Reliability
If drones automatically adjust position to maintain line-of-sight, then reliability of line-of-sight maintenance is improved, but device complexity increases due to sensors and control systems
Solution Approach 1:
A computing platform serves as an intermediary between the wearable devices and the drone control system. This centralized processor receives location data from multiple devices, determines which individuals require monitoring, and generates appropriate control signals, thereby simplifying the overall system architecture while maintaining reliable line-of-sight maintenance.
Solution Approach 2:
The control system is designed to handle multiple functions: receiving location data from various wearable devices, processing this information to determine monitoring priorities, generating control signals for drone positioning, and managing communication between components. This multi-functional approach reduces the need for separate specialized systems.
3Measurement precision
If multiple sensors and processing systems are added to ensure line-of-sight, then measurement precision of line-of-sight detection is improved, but device complexity increases
Solution Approach 1:
The computing platform acts as a central intermediary that receives and processes location information from wearable devices. By consolidating processing functions in a centralized system rather than distributing complex sensor arrays across multiple drones, the system achieves precise line-of-sight detection while minimizing overall device complexity.
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 enables reliable tracking and monitoring of individuals while adhering to safety regulations, allowing for real-time alerts and efficient drone movement to maintain line-of-sight, enhancing safety and usability in various applications such as child monitoring and agricultural supervision.
Implementation Method 1
wearable devices that use GPS, beacons, and image sensors to determine and maintain line-of-sight
Implementation Method 2
wearable devices that use GPS, beacons, and image sensors to determine and maintain line-of-sight
Implementation Method 3
wearable devices that use GPS, beacons, and image sensors to determine and maintain line-of-sight
Data Source
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AI summary
Examples disclosed herein relate to control of a drone. In one example, aerial movement of the drone is controlled. In the example, it is determined, based on a plurality of devices, whether the drone is within a line- of-sight with at least a respective one of a plurality of humans within a physical proximity to a respective one of a the devices.. In the example, the devices are used by the drone to track the humans. In the example, when the drone is determined to lack the !ine-of-sight, aerial movement of the drone is controlled to move the drone to become within the line-of-sight.