Robotic Plant Monitoring With Sub-Plant Structure Mapping
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Solution Overview
Problem
Current plant monitoring in agriculture is labor-intensive, costly, and inefficient, often relying on manual methods or static sensors that provide limited data and require significant human intervention.
Innovation Solution
A plant management system that utilizes autonomous robotic monitoring devices to collect and manage vast amounts of plant data, including spatial and environmental characteristics, at the sub-plant level, enabling efficient data organization, retrieval, and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual monitoring methods are used, then monitoring can be performed with simple equipment, but labor costs increase and monitoring coverage is limited to a small percentage of plants
Solution Approach 1:
The system employs autonomous robotic devices that navigate greenhouse environments independently to collect plant data, eliminating the need for continuous human intervention and enabling comprehensive monitoring coverage without proportional increases in operational complexity
Solution Approach 2:
Manual monitoring activities are replaced with automated robotic systems equipped with sensors and navigation capabilities, substituting human labor with autonomous mechanical systems that can operate continuously and cover entire plant populations
2Quantity of substance
If static sensors are placed adjacent to a limited number of sample plants, then device complexity remains low, but the amount of plant data collected is insufficient for comprehensive analysis
Solution Approach 1:
The monitoring system is divided into multiple autonomous robotic units, each capable of independent operation and data collection, allowing the system to scale data collection capacity by deploying additional segments without proportionally increasing central system complexity
Solution Approach 2:
The system transitions from static sensor placements to dynamic robotic platforms that can move throughout the greenhouse environment, enabling comprehensive data collection from numerous plants while managing complexity through modular, autonomous operation
3Loss of time
If manual data entry and analysis is performed, then device complexity is minimized, but time consumption increases and decision-making is delayed
Solution Approach 1:
Manual data entry and analysis tasks are replaced with automated digital systems that continuously collect, store, and process plant data, eliminating time-consuming manual operations and enabling real-time decision-making through computational analysis
Solution Approach 2:
The system implements continuous feedback loops where collected plant data is automatically analyzed and used to generate real-time recommendations for plant care interventions, reducing decision-making delays through automated information processing and action generation
4Productivity
If monitoring is limited to a small percentage of plants, then resource consumption is reduced, but monitoring efficiency decreases and labor shortages cannot be addressed
Solution Approach 1:
Autonomous robotic systems perform monitoring tasks independently without requiring human labor, addressing workforce shortages while achieving comprehensive plant coverage; the systems manage their own navigation, data collection, and communication functions
Solution Approach 2:
The system optimizes resource consumption by adjusting operational parameters such as sensor activation thresholds, navigation paths, and data collection frequencies based on plant needs and environmental conditions, enabling high monitoring efficiency with controlled resource usage
Data Source
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AI summary
Systems and methods for managing operation of plant growth zone(s) are presented, the management system comprising: a storage device comprising a database that stores data indicative of plant characteristics for each plant in the plant growth zone, the plant characteristics comprising plant spatial and environmental characteristics and plant location in the plant growth zone; and a data processing unit comprising a database manager configured to create a new, or update an existing, database entry record corresponding to a plant in the plant growth zone, in response to sensing data being received from sensing system(s), the sensing data being part of visit data indicative of a visit by the sensing system(s) to the individual plant, and create a data retrieval record in response to data request input with respect to plant(s) in the plant growth zone, the database manager comprising: a sub-plant features extraction module configured to identify in the visit data spatial sub¬ plant features of each plant sensed during a visit, and a plant structure data generation module configured to generate plant structure data corresponding to the identified spatial sub-plant features, the database manager being configured to create the new, or update the existing, database entry record, to store said plant structure data in the database, and identify, in the data request input, each plant, and utilize the plant structure data stored in the database to create the respective data retrieval record; the plant structure data is configured such that contents of the database entry record and/or the data retrieval record comprise a virtual representation of the corresponding plant's structure in accordance with locations of the spatial sub-plant features and their dimensions matching a real structure of the plant.