file_name stringclasses 1 value | quality stringclasses 1 value | person_count stringclasses 1 value | activity_type stringclasses 1 value | equipment_presence stringclasses 1 value | tool_type stringclasses 1 value | weather_condition stringclasses 1 value | experiment_location stringclasses 1 value | plant_type stringclasses 1 value | experiment_phase stringclasses 1 value |
|---|---|---|---|---|---|---|---|---|---|
ce68d580d39c3a7993cf8f25dfd5d66c.jpg | 7603*5071 | 1 | Observation and Recording | Present | Tablet or Laptop | Indoor Environment | Indoor Laboratory | Unspecified | Execution Phase |
Agricultural Experiment Personnel Operation Behavior Dataset
The current agricultural industry is facing issues of low production efficiency and resource waste, especially in crop monitoring and management. Existing monitoring methods often rely on manual inspection, which is inefficient and prone to error. This dataset aims to solve problems in automated monitoring by providing high-quality operational behavior data of agricultural experiment personnel for object detection and behavior recognition. Data collection was carried out using high-resolution cameras under various lighting and environmental conditions to ensure coverage of different agricultural operation scenarios. In terms of quality control, we implemented multiple rounds of annotation and consistency checking, with final review by agricultural experts to ensure data accuracy. The data is stored in JPG format and organized such that each image corresponds to related annotation files. As for the core advantages of the dataset, we ensured high annotation accuracy (95%), with consistency improvement of 20% compared to traditional methods. Additionally, we introduced new data augmentation techniques to enhance model generalization capability, with expected performance metric improvements of up to 30%.
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| person_count | int | The number of agricultural experiment personnel appearing in the image. |
| activity_type | string | The type of activity being performed by agricultural experiment personnel in the image, such as planting, fertilizing, harvesting, etc. |
| equipment_presence | boolean | Indicates whether agricultural equipment is present in the image. |
| tool_type | string | The type of tools used by agricultural experiment personnel in the image. |
| weather_condition | string | The weather conditions depicted in the image, such as sunny, cloudy, rainy, etc. |
| experiment_location | string | The location of the agricultural experiment activity depicted in the image. |
| plant_type | string | The type of plants involved in the image. |
| experiment_phase | string | The current stage of the agricultural experiment, such as preparation phase, execution phase, results recording phase, etc. |
Compliance Statement
| Authorization Type | CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike) |
| Commercial Use | Requires exclusive subscription or authorization contract (monthly or per-invocation charging) |
| Privacy and Anonymization | No PII, no real company names, simulated scenarios follow industry standards |
| Compliance System | Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs |
Source & Contact
If you need more dataset details, please visit Mobiusi. or contact us via contact@mobiusi.com
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