Drone Delivery Beaconing for Precise Drop Location Confirmation
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Solution Overview
Problem
Conventional delivery systems lack efficient methods for accurately directing deliveries to specific locations, particularly in residential or secure areas, and fail to provide reliable confirmation of delivery through visual or image-based tracking.
Innovation Solution
A delivery data server and client device system that uses image capture and processing to generate delivery location data, allowing users to select and confirm delivery locations on captured images, with options for street or sky views, and integrates with drone delivery systems for precise locationing using beacons or mats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional delivery systems use traditional tracking methods, then delivery status can be monitored, but accurate location identification in residential or secure areas cannot be achieved
Solution Approach 1:
The patent introduces beacons and mats as intermediary devices placed at delivery locations. These intermediaries enable precise location identification by serving as reference points for image capture and processing, resolving the contradiction between tracking capability and location precision in residential or secure areas.
Solution Approach 2:
The patent replaces traditional mechanical tracking systems with image-based tracking using cameras and image processing. This substitution enables accurate delivery location identification by capturing and analyzing images of beacons or mats at the delivery site, achieving both monitoring and precise location identification.
2Reliability
If image capture devices are integrated into drone delivery systems, then visual confirmation of delivery is achieved, but system complexity increases
Solution Approach 1:
The patent integrates image capture devices into the drone system to serve multiple functions: navigation, delivery location identification, and visual delivery confirmation. This multi-functionality approach achieves reliable delivery confirmation while justifying the increased system complexity through enhanced versatility.
Solution Approach 2:
The patent implements feedback mechanisms where captured images are processed to confirm delivery at the correct location. The system uses image recognition of beacons or mats to provide feedback on delivery status, enabling reliable confirmation while managing system complexity through automated processing.
3Measurement precision
If beacons or mats are deployed at delivery locations, then precise delivery positioning is enabled, but implementation cost and complexity increase
Solution Approach 1:
The patent employs beacons and mats as simple, inexpensive deployment objects at delivery locations. These objects serve as temporary but effective reference points for image-based tracking, enabling precise delivery positioning without requiring complex or expensive infrastructure.
Data Source
AI summary
A system can be used with a drone delivery service that facilitates a service delivery via at least one drone delivery device. The system includes a code generator configured to generate beacon data that identifies a subscriber. A beacon generator is configured to generate a wireless homing beacon that indicates the beacon data, wherein the wireless homing beacon is detectable by the at least one drone delivery device to facilitate the service delivery to the subscriber by the drone delivery device at a location selected by the subscriber and a network interface is configured to communicate via a network. The system receives delivery image data captured after the service delivery by the drone delivery device.