Parcel Videos Data Collection

Project Overview:

Objective

To compile a diverse dataset of parcel and package handling videos. This collection aims to enhance AI systems responsible for automating logistics, ensuring proper handling of packages, and developing intelligent surveillance for warehouses and shipping centers.

Scope

Collate videos showcasing various parcel types, packaging materials, handling techniques, environments, and delivery scenarios to cover the broad spectrum of the parcel lifecycle.

Sources

Warehouses and Sorting Centers: Collaborate with logistics companies to capture videos of parcels as they move through conveyor systems, get sorted, and loaded onto vehicles.
Delivery Process: Record videos of delivery personnel handling and delivering parcels to various locations: homes, businesses, drop-off points, etc.
Return and Damaged Goods: Document the process of dealing with returned goods and assessing parcel damages.
User-generated Content: Encourage customers or receivers to share videos of unboxing or any observed mishandling.

Data Collection Metrics

Total Data Points: 40,000 videos
Warehouse Footage: 20,000
Delivery Footage: 10,000
Return/Damage Assessment: 5,000
User-generated Videos: 5,000

Annotation Process

Stages

Parcel Type: Label the parcel’s contents if identifiable (e.g., electronics, perishables, fragile items).
Handling Annotation: Document the handling method observed (e.g., manual, automated, with/without care).
Environment & Context Tagging: Indicate the primary setting (warehouse, outdoor, residential area) and any specific context (raining, crowded, conveyor belt)

Annotation Metrics

Parcel Type Annotations: 40,000
Handling Annotations: 40,000
Environment Tags: 40,000

Quality Assurance

Video Quality Review: Check that each video meets a defined standard of clarity, stability, and resolution.
Privacy Assurance: Ensure no sensitive information or identifiable personal data is visible in the videos, especially in user-generated content.
Metadata Verification: Regular audits to guarantee the accuracy and consistency of annotations.

QA Metrics:

Videos Needing Quality Adjustments: 4,000 (10% of total)
Privacy Review on All Videos: 40,000 (100% due to potential sensitivity)
Metadata Audit Samples: 8,000 (20% random sampling)

Conclusion

The Parcel Videos Data Collection Initiative is poised to revolutionize the logistics and e-commerce industries. With a holistic view of the parcel lifecycle and detailed annotations, AI systems can be better trained for automation, surveillance, and quality assurance, ensuring that each package reaches its destination safely and efficiently.(Parcel Videos Data Collection)