Drone-Assisted GNSS Positioning for Offline Farm Machinery
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Solution Overview
Problem
Farmers face challenges in connecting agricultural machinery to network infrastructure due to poor network connectivity in rural areas, leading to unreliable data transfer and loss, which affects real-time decision-making and accurate yield determination in precision agriculture.
Innovation Solution
A system and method for enabling data-centric computing that includes device, edge, and cloud computing infrastructure for reliable data transfer and processing, using aerial drones to collect and process data in areas with limited connectivity, and normalizing yield data from various sources for accurate analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If farmers use traditional network infrastructure to connect agricultural machinery, then real-time data transfer is enabled, but network connectivity is unreliable in rural areas
Solution Approach 1:
The patent introduces aerial vehicles (drones) as intermediary devices to establish temporary communication relays between agricultural machinery and the network infrastructure. These aerial intermediaries fly above obstructions and transmit data when ground-based connectivity fails, resolving the contradiction by providing an alternative communication path that maintains reliability without requiring improved ground infrastructure.
Solution Approach 2:
The patent transitions from two-dimensional ground-based network connectivity to three-dimensional aerial communication by deploying drones in the air space above fields. This dimensional shift allows the system to bypass ground obstructions and reach areas with poor connectivity, simultaneously improving reliability and maintaining ease of operation by using existing aerial platforms.
2Ease of operation
If farmers use USB sticks to store data locally, then network connectivity requirements are reduced, but data loss occurs due to lost or misplaced USB sticks
Solution Approach 1:
The patent implements feedback mechanisms where aerial vehicles continuously monitor the status of data storage devices on agricultural machinery. When USB sticks are detected as lost, damaged, or full, the system automatically triggers data retrieval operations or alerts operators, preventing complete data loss while maintaining the benefit of local storage independence.
Solution Approach 2:
The aerial vehicle acts as an intermediary that periodically collects data from USB sticks on machinery and transfers it to secure cloud storage. This eliminates the risk of USB stick loss while preserving the advantage of local storage capability, as the intermediary handles the risky physical transfer operation.
3Reliability
If aerial vehicles are deployed to collect location data, then data coverage in remote areas is improved, but device complexity increases
Solution Approach 1:
The patent employs multi-functional aerial vehicles that can perform location data collection, network relay, and terrain mapping tasks simultaneously. By using a single versatile platform for multiple functions, the system improves location data coverage without proportionally increasing device complexity, as the same hardware serves multiple purposes.
Solution Approach 2:
The aerial vehicles are equipped with autonomous navigation and self-positioning capabilities that reduce the need for complex ground control systems. The vehicles independently collect location data and return it to the farm management system, minimizing the operational complexity required to deploy and manage the system.
4Productivity
If real-time data processing is implemented, then decision-making speed is improved, but network connectivity requirements increase
Solution Approach 1:
The patent pre-positions aerial vehicles and establishes communication relays before critical decision-making moments occur. Data collection and preliminary processing are performed in advance by aerial platforms, ensuring that real-time analysis can proceed without waiting for network connectivity, thus maintaining both decision-making speed and independence from continuous network availability.
Data Source
AI summary
Obtaining location data in a novel way is considered to be a part of this invention. An exemplary method for doing so includes identifying first positioning information for a data delivery vehicle based at least in part on a plurality of positioning signals received at the data delivery vehicle from a set of satellites of a global navigation satellite system (GNSS). The example method comprises obtaining relative position information associated with a position vector from the data delivery vehicle to a remote vehicle, the remote vehicle being unable to receive the plurality of positioning signals from the set of satellites. The example method comprises determining second positioning information for the remote vehicle based at least in part on the first positioning information and the relative position information. The example method comprises transmitting the second positioning information to the remote vehicle.