Autonomous Aerial Data Relay for Offline Farm Yield Collection
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Solution Overview
Problem
Agricultural data transfer and processing challenges arise due to poor network connectivity in rural areas, leading to unreliable data collection and loss, which hampers real-time decision-making and accurate yield determination in precision agriculture, especially with automated harvesters and machinery.
Innovation Solution
A data-centric computing platform enabling edge and cloud computing for reliable data transfer and processing, using aerial drones to collect and normalize yield data, and providing two-way communication between data delivery vehicles and compute nodes to facilitate real-time decision-making in areas with limited network connectivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If USB sticks are used to store data on farm machinery, then data can be collected offline in areas with poor network connectivity, but data loss occurs due to lost, erased, stolen, or misplaced USB sticks
Solution Approach 1:
The patent introduces aerial vehicles (drones) as intermediary devices to collect data from multiple sources including USB sticks on farm machinery, then transfer the aggregated data to locations with network connectivity. This mediator approach prevents data loss by providing a centralized collection point and eliminates the risk of individual USB sticks being lost or misplaced.
2Productivity
If manual collection and transfer of USB sticks to offices is used, then data can be ingested from machinery, but the process is unreliable and leads to complete failure and data loss
Solution Approach 1:
The system enables self-service data transfer where aerial vehicles autonomously navigate to collect data from multiple machinery locations, automatically aggregate the data, and transfer it to processing locations. This eliminates manual USB stick collection and reduces human error while improving both reliability and productivity.
Solution Approach 2:
The patent combines multiple data collection methods (USB sticks, sensors, onboard monitors) into a unified system where aerial vehicles aggregate data from multiple sources simultaneously. This merging approach streamlines the data collection process and improves overall system reliability.
3Measurement precision
If sophisticated data analytics systems are deployed, then accurate yield determination and real-time decision-making are enabled, but network connectivity requirements cannot be met in rural areas
Solution Approach 1:
The patent introduces aerial vehicles operating in three-dimensional space to bridge the connectivity gap. By moving data collection and transfer operations vertically (aerial dimension) rather than relying solely on ground-based network infrastructure, the system enables sophisticated analytics in remote rural areas without requiring extensive ground network deployment.
Data Source
AI summary
Disclosed herein are systems and methods for enabling at least one autonomous device to traverse a three-dimensional space. An example system may comprise a first autonomous vehicle comprising a first sensor suite. The first autonomous vehicle may traverse the three-dimensional space in accordance with a path planned vector. The path planned vector may be dynamically updated based on a first vector associated with a first object identified based on data received from the first sensor suite. The example system may comprise a first aerial vehicle comprising a second sensor suite. The first aerial vehicle may traverse the three-dimensional space based on at least one of data provided by the second sensor suite, the first sensor suite, and other aerial vehicles. The path planned vector may be dynamically updated based on data received from at least one of the first sensor suite, the second sensor suite, and cloud interface data.