Aerial Data Ferry for Edge Computing in Network-Constrained Fields
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Solution Overview
Problem
Farmers face challenges in connecting farm machinery and in-field sensors to cloud analytics systems due to poor network connectivity, leading to unreliable data transfer and loss, which hampers real-time decision-making and affects crop yield in precision agriculture.
Innovation Solution
A data-centric computing platform that enables device and edge computing, standardizes IoT data ingestion, and automatically scales data-processing tasks, allowing for robust data collection and processing even in areas with little or no network connectivity, using aerial drones or similar technology for data transport and processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If cloud-based analytics systems are used for processing agricultural data, then data processing capability and insights are improved, but network connectivity requirements increase, making the system unusable in rural areas with poor connectivity
Solution Approach 1:
The system segments computing operations into three distinct layers: device-level computing (on the farm machinery itself), edge computing (at local gateways or hubs), and cloud computing (for heavy analytics). This segmentation allows data processing to occur at multiple levels, reducing dependency on continuous cloud connectivity while maintaining advanced analytics capabilities where network is available.
Solution Approach 2:
The patent introduces edge computing devices as intermediaries between farm machinery and cloud systems. These edge devices can process and pre-analyze data locally, buffering and queuing data transmissions when network connectivity is unavailable, thus mediating between the need for cloud-based analytics and the reality of poor rural network infrastructure.
2Reliability
If data is stored locally on USB sticks for later transfer, then network connectivity requirements are reduced, but data loss and corruption risks increase due to physical handling and storage issues
Solution Approach 1:
The system enables self-service data management through automated data collection, validation, and transmission protocols built into the farm machinery. Data is automatically uploaded when connectivity is available, reducing the need for manual USB stick handling while maintaining the ability to operate independently of network infrastructure.
Solution Approach 2:
The patent implements preliminary data validation and error checking at the source (on the machinery itself) before data leaves the device. This preliminary action ensures data integrity is maintained throughout storage and transmission, reducing the risk of corruption even when data must be temporarily stored locally during periods of poor connectivity.
3Loss of time
If real-time data processing is implemented for immediate decision-making, then response time is improved, but network bandwidth requirements increase, exacerbating the problem in areas with limited connectivity
Solution Approach 1:
The system applies local quality by processing different types of data with different priorities and bandwidth requirements. Critical real-time data (such as equipment malfunction alerts or immediate field conditions) is processed locally with minimal bandwidth consumption, while less time-sensitive data is batched for later transmission, optimizing the balance between response time and bandwidth usage.
Data Source
AI summary
The present invention is for an autonomous aerial vehicle that enables near real-time and offline data processing among heterogenous devices that are in unreliable or unconnected network service areas, wherein the heterogenous devices are associated with heavy industrial systems. The autonomous aerial vehicle may obtain data from a first physical asset, and segment the obtained data as suitable for a local area compute node and/or a cloud compute node. The autonomous aerial vehicle may identify a location associated with the one or more destination devices and may compute a flight path to the destination location. The aerial device may thereafter travel to the destination location and upload relevant data to the at least one destination upon arrival.