Automated Virtual Load Tracking in Agricultural Harvesting
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Solution Overview
Problem
Current agricultural logistics face inefficiencies in tracking and managing product loads during harvesting and transportation, leading to manual errors and lack of real-time data integration from field to storage and sale.
Innovation Solution
A system that uses GPS and sensors to automatically collect and aggregate data on product location and quantity, triggering alerts for load management and offloading, and linking this data with mobile transport containers for seamless product transfer and traceability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual tracking and data entry methods are used for agricultural product loads, then operational flexibility is maintained, but accuracy and efficiency deteriorate due to manual errors and lack of real-time data integration
Solution Approach 1:
The system uses universal GPS receivers and communication modules that serve multiple functions: tracking vehicle location, monitoring product quantity, coordinating between harvesters and transport containers, and providing real-time data to the server. This multi-functionality improves measurement precision without proportionally increasing device complexity
Solution Approach 2:
The server acts as an intermediary that receives data from multiple GPS receivers (harvester and transport container), processes the information, and coordinates loading operations. This intermediary approach enables accurate load tracking and real-time data integration without requiring direct complex communication between all system components
2Productivity
If automated data collection and alert systems are implemented, then operational efficiency and real-time data integration improve, but device complexity and initial costs increase
Solution Approach 1:
The system automatically generates alerts before the harvester storage container reaches full capacity, allowing transport containers to be dispatched in advance for loading operations. This preliminary action improves operational efficiency by preventing downtime and ensuring seamless product transfer without requiring complex real-time intervention systems
Solution Approach 2:
The server receives continuous feedback from GPS receivers regarding product quantity and location, automatically coordinates loading operations when transport containers are positioned correctly, and provides real-time status updates. This feedback mechanism enables automated decision-making and coordination, improving productivity through intelligent system responses rather than simple automation
3Loss of information
If real-time GPS tracking and automatic alerting are used, then load management accuracy and data aggregation improve, but energy consumption and system complexity increase
Solution Approach 1:
The GPS receivers and sensors transmit data to the server at periodic intervals rather than continuously, and alerts are generated based on threshold conditions (storage container capacity levels). This periodic action ensures complete data integration for load tracking while significantly reducing energy consumption compared to continuous monitoring and transmission
Data Source
AI summary
One or more techniques and/or systems are disclosed for automating the collection aggregation, and processing of data relating to harvesting or dispersion of an agricultural product. During harvesting and planting operations, data related to the product harvested or planted can be collected, aggregated, and used to improve the operation, and to help identification of the product at point of sale or point of dispersion. Further, certain operations can be automated during the harvesting or planting, such as automatic deployment of a field cart to offload/load product from/to the agricultural vehicle in the field. Additionally, load data can be automatically collected, aggregated, and identified, to follow the product through all stages.