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file_name
stringclasses
1 value
quality
stringclasses
1 value
transport_vehicle_type
stringclasses
1 value
product_type
stringclasses
1 value
product_quantity
stringclasses
1 value
weather_condition
stringclasses
1 value
time_of_day
stringclasses
1 value
obstacles_present
stringclasses
1 value
road_condition
stringclasses
1 value
e2ab296e43d66d2f9dfbe7dcf39d0d6b.jpg
2968*1975
Carriage
Hay
Moderate quantity
Sunny
Afternoon
No noticeable obstacles
Muddy but passable

Agricultural Product Transportation Scene Dataset

The current agricultural industry faces challenges such as low transportation efficiency and high loss rates. Especially during the transportation of agricultural products, the damage rate significantly affects farmers' income. Existing solutions primarily rely on manual inspection, which is inefficient and error-prone, hence the urgent need for an efficient automated detection method. This dataset aims to provide fundamental data for object detection in agricultural product transportation scenarios to help develop automated monitoring systems. Data collection is performed using high-resolution cameras capturing agricultural product transportation scenes under various lighting and weather conditions, ensuring data diversity and representativeness. In terms of quality control, the data undergoes multiple rounds of annotation, consistency checks, and expert reviews to ensure annotation accuracy and consistency. Data storage is in JPG format organized into a folder structure for quick access and processing.

Technical Specifications

Field Type Description
file_name string File name
quality string Resolution
transport_vehicle_type string The type of vehicle used during transportation, such as a truck or tractor.
product_type string The type of agricultural product being transported, such as fruit, vegetables, or wheat.
product_quantity integer The quantity of agricultural products being transported, which helps to understand the scale of transportation.
weather_condition string The weather condition when the image was captured during transportation.
time_of_day string The time period when the image was taken, such as morning, afternoon, or evening.
obstacles_present boolean Indicates whether there are obstacles present in the transportation process as depicted in the image.
road_condition string The condition of the road during transportation, such as smooth, rough, or slippery due to rain.

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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