Autonomous Farm Machine Monitoring for Irregularity Recovery
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Solution Overview
Problem
Current methods for monitoring autonomous agricultural machines require a person to be present nearby to control and monitor them, limiting their autonomous operation and efficiency.
Innovation Solution
A method using sensor devices to detect operating and environmental parameters, with a control device and processing unit that automatically identifies irregularities, transfers the machine to a safe state, and generates instructions to resume normal operation, leveraging artificial intelligence and a database for data analysis and storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If an operator of a manned agricultural machine is used to visually monitor and control the autonomous agricultural machine, then the autonomous machine can be operated safely, but the operator must remain in close proximity to the autonomous machine, reducing productivity and efficiency
Solution Approach 1:
A remote monitoring center acts as an intermediary between the autonomous agricultural machine and the operator. The monitoring center receives data from the autonomous machine via telecommunication networks and sends control commands back, allowing the operator to monitor and control the machine from a remote location without needing to be physically close by
Solution Approach 2:
The direct visual monitoring and manual control mechanism is replaced with an automated monitoring system that uses sensors, data processing units, and telecommunication networks to detect irregularities and transmit control commands, eliminating the need for continuous human presence near the machine
2Reliability
If continuous monitoring with remote operator control is implemented, then operational safety is maintained, but the complexity of the monitoring and control system increases
Solution Approach 1:
The monitoring system is segmented into distinct functional modules: sensor devices for data acquisition, control units for processing, telecommunication interfaces for communication, and a remote monitoring center for oversight. This modular segmentation reduces overall system complexity by allowing each component to be developed and maintained independently
Solution Approach 2:
The system performs preliminary detection and analysis of irregularities through automated sensors and processing units before human intervention is needed. This preliminary automated action reduces the complexity of human-operated control systems by handling routine monitoring tasks automatically
3Ease of operation
If an operator must be in close proximity to control the autonomous machine, then real-time control is possible, but personnel resources are inefficiently utilized
Solution Approach 1:
The remote monitoring center can oversee multiple autonomous agricultural machines simultaneously through a single interface, allowing one operator to perform the control function for several machines at once. This multi-functionality increases personnel resource efficiency while maintaining real-time control capability
Data Source
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AI summary
The present invention relates to a method for monitoring the operation of at least one autonomous agricultural machine (1). The method comprises determining data representing operating parameters and environmental parameters of the autonomous agricultural machine (1), and detecting irregularities based on these data. The method is characterized in that, as soon as an irregularity is detected, the determined data is transmitted to and stored in a database (6), and the irregularity is identified by means of a processing device (7) by processing the determined data in an analysis routine. An instruction for transitioning the autonomous agricultural machine (1) from a safe operating state to a normal operating state is generated based on the identified irregularity, and the instruction is executed.