Image Annotation and Data Processing for Industry and Logistics

Image Annotation

and Data Processing

for Industry and Logistics

We deliver ready-to-use datasets to train your AI models at every stage of the industrial and logistics value chain

What We Do

Data and computer vision expertise for industry and logistics

Multi-sensor image annotation, defect segmentation, object tracking, flow analysis, and document indexing.

Our pipelines ensure precision, consistency, and traceability within ISO 27001–certified environments.

Rigorous and Controlled Process

Technical scoping, definition of annotation guidelines, pilot projects, multi-level validation, inter-annotator QA, quality audits, and performance dashboards (IoU, F1, mAP, temporal drift).

Security & Compliance (ISO 27001 / GDPR)

Secure pipelines including encryption, access control, logging, visual and textual anonymization. Full compliance with European regulations and internal industrial policies.

Multi-Sensor Annotation

Industrial cameras (RGB/IR), LiDAR, thermal vision, IoT sensors, MES data, and maintenance reports. Seamless integration with your supervision and enterprise systems (SCADA, ERP, PLM, WMS).

EXpertise

Industrial AI: Data Annotation for Quality, Maintenance, and Traceability

Industrial data annotation enables AI to monitor, control, and optimize production and distribution chains. It powers embedded vision models, predictive maintenance, quality inspection, and logistics traceability.

At Infoscribe, we combine methodological rigor, domain expertise, and advanced annotation technologies to deliver reliable, consistent, and training-ready AI datasets.

2D & 3D Annotation – Industrial and Logistics Vision

Multi-Camera Automated Visual Inspection

Annotation of images from multiple high-speed cameras installed on production lines to detect defects, misalignments, cracks, and dimensional anomalies on parts or packaging..

Camera + LiDAR Fusion for Volumetric Inspection

Combination of 2D images and 3D point clouds to measure dimensions, volumes, and alignments of industrial components, ensuring high-precision geometric control.

Pork Carcass Categorization in Slaughterhouses

Visual analysis of carcasses on slaughter lines to annotate key anatomical landmarks, measure fat thickness, and automate quality grading.

Monitoring Resin Spreading in Industrial Moldst

Visual inspection of industrial molds to verify resin uniformity, annotate correct or defective areas, detect anomalies, improve quality, and reduce scrap.

Baggage Tracking and Identification

Detection and tracking of luggage on airport sorting systems to identify labels, ensure flow traceability, and reduce routing errors.

Object Segmentation in Bins for Robotic Picking

Fine-grained segmentation of objects in logistics bins, enabling robots to localize, identify, and accurately grasp items during order fulfillment.

Thermal and Infrared Vision for Predictive Maintenance

Annotation of thermal data to detect overheating, leaks, wear, or electrical overloads. AI predicts failures before they cause production downtime.

Multi-Sensor Object Tracking in Warehouses

Fusion of camera feeds, RFID, and positioning sensors to annotate trajectories of parcels, carts, or robots, optimizing logistics flows and productivity..

Image and IoT Process Sensor Correlation

Simultaneous annotation of images and sensor data (temperature, vibration, pressure) to identify visual causes of production drift and refine machine calibration.

3D Inspection of Complex Surfaces

Annotation of 3D models from laser scanners or LiDAR to identify micro-defects, scratches, or deformations invisible to the naked eye on metal or composite structures.

Embedded Vision for Industrial Robotics

Annotation of 2D/3D images from cameras embedded on robotic arms to train AI models for guidance, precise positioning, and dynamic obstacle detection.

Assembly Compliance Control

Annotation of images synchronized with torque, force, or vibration sensor signals to verify correct assembly, tightening, and alignment of components on assembly lines.

X-Ray or Hyperspectral Package Inspection

Annotation of multi-spectral images to detect internal anomalies, missing products, foreign objects, or hidden damage inside sealed packages.

Operator Safety Monitoring

Annotation of RGB and infrared images to detect PPE usage (helmets, gloves, vests), risky postures, and dangerous movements near machinery.

Stereo Vision Quality Inspection

Annotation of stereo image pairs to compute depth and surface relief, detecting part misalignments or structural defects in assemblies.

Video and Acoustic Data Fusion

Joint annotation of audio signals (vibrations, mechanical noise) and video streams to correlate abnormal sounds with visual events on production lines.

Multi-Source Energy Monitoring

Annotation of thermal camera feeds, IoT, and SCADA data to identify overconsumption zones, heat losses, leaks, or anomalies in fluid networks and installations.

Real-Time Production Monitoring

Sequential annotation of multi-sensor data streams to link process stages, identify bottlenecks, and automate performance indicator generation

Multi-Sensor Calibration (Camera, LiDAR, IMU)

Annotation of image datasets and inertial measurements to synchronize sensors and improve the accuracy of perception systems on robots or industrial vehicles.

Internal Transport Flow Analysis

Combined annotation of overhead cameras and positioning sensors to track forklifts, pallets, and AGVs, detecting congestion or inefficient routes..

Augmented Vision for Remote Maintenance

Annotation of visual streams captured by AR glasses and mobile cameras to remotely guide operators, recognize tools, and identify components in real time.

Packaging Line Control

Annotation of multi-sensor images (optical and infrared) to verify presence, orientation, sealing, and labeling of products, preventing packaging errors or non-compliant batches.

Simulation and Validation of Industrial AI Models

Annotation of synthetic data from digital twins and simulated environments to train detection models and validate systems before real-world deployment.

Text Annotation – Industrial and Logistics NLP

Maintenance Report Analysis

Annotation of failures, root causes, equipment, and recommendations in maintenance reports to automate the detection of recurring issues and prioritize maintenance actions.

Incident Classification

Automatic categorization of anomalies, emergencies, and corrective actions from production logs or maintenance tickets, enabling real-time prioritization and reporting.

Technical Document Indexing

Annotation of manuals, product datasheets, and procedures to structure industrial documentation, improve technical search, and accelerate knowledge transfer across teams.

Key Information Extraction (NER)

Identification of entities such as equipment, part numbers, materials, suppliers, and locations to automatically link documents, incidents, and components within an industrial knowledge graph.

Automated Summarization

Generation of automatic summaries of reports, audits, and production records, giving decision-makers quick access to a consolidated view of performance and anomalies.

Internal Ticket and Email Analysis

Annotation of internal messages to automatically classify, prioritize, and route requests to the appropriate departments (maintenance, quality, logistics, safety).

Supplier Quality Monitoring

Annotation of audit reports, quality records, and contracts to detect compliance gaps, track supplier KPIs, and proactively trigger corrective actions.

Regulatory Documentation

Annotation of compliance-related documents (ISO, REACH, safety, traceability) to automate regulatory checks and ensure documentation compliance during audits and certifications.

Other Industries

FAQ

Frequently Asked Questions

Infoscribe handles a wide range of industrial media, covering most formats used today in production, quality control, automated inspection, and robotics environments. This versatility allows us to support manufacturing, automotive, energy, logistics, aerospace, and electronics industries, meeting growing needs in computer vision, automation, and industrial AI.

One key category is industrial photographs, including images of parts, equipment, surfaces, or components. These can be annotated to detect defects, measure tolerances, monitor wear, or identify visual anomalies. We also process images from production lines, assembly stages, or snapshots from industrial supervision systems.

Industrial videos form another important category. They enable analysis of gestures, tracking of logistics flows, assessment of production rates, or detection of unexpected behaviors in dynamic environments. Videos from surveillance cameras, industrial robots, or embedded systems can also be processed.

Infoscribe can handle data from machine vision systems used for automated quality control or rapid defect detection on high-speed production lines. Sources may include raw formats, calibrated images, or continuous streams requiring preprocessing.

We also process 3D data, including point clouds from industrial scanners, LiDAR systems, or depth sensors (stereo, ToF). These are essential for 3D modeling, volumetric inspection, surface reconstruction, or deformation detection.

Specialized media include thermal images, useful for detecting overheating, monitoring electrical networks, predictive maintenance, or insulation assessment. We also process industrial X-rays (radiography) for non-destructive testing (NDT), such as inspecting welds, metal parts, or composite materials.

Finally, our teams can work with LiDAR scans, multispectral or hyperspectral images, or any other format produced by industrial machines.

Thanks to this ability to handle diverse and complex media, Infoscribe meets the demanding requirements of data analysis, annotation, processing, and structuring in modern industrial contexts.

Infoscribe ensures annotation consistency and quality in industrial settings through a combination of proven methodologies, strict quality control, and management adapted to operational constraints. Industrial environments present numerous challenges—low tolerance for errors, lighting variations, occlusions, dust, rapid movements, or complex perspectives—requiring higher annotation standards than in other sectors.

1. Precise, Use-Case-Specific Guidelines

Before project launch, detailed, tailor-made guidelines are prepared, defining:

  • object classes and subclasses,
  • segmentation or detection rules,
  • tolerances,
  • special cases and exceptions,
  • annotation conditions in degraded situations (shadows, reflections, blur).

These documents are developed in collaboration with the client to faithfully reflect industrial requirements.

2. Targeted Team Training

Annotators receive domain-specific industrial training, including:

  • understanding parts and equipment,
  • identifying defects,
  • maintaining annotation consistency,
  • mastering 2D/3D tools.

Evaluation tests ensure annotators reach the required level before joining the project.

3. Multi-Level Quality Control Workflow

Infoscribe applies a multi-layer QA process, including:

  • systematic review by senior annotators,
  • double annotation on critical samples,
  • regular audits according to ISO 2859–equivalent standards,
  • variance analysis to quickly correct deviations.

This ensures high consistency even with massive volumes.

4. Specialized 2D/3D Tools

Annotation tools enable:

  • zooming in on micro-defects,
  • 3D calibration,
  • multi-view visualization,
  • precise polygon and mask manipulation.

This minimizes errors due to visual variations.

5. Continuous Monitoring and Adjustments

Regular check-ins with the client allow guideline adjustments, clarification of ambiguities, and ongoing alignment with industrial objectives.

Thanks to this strict framework, Infoscribe delivers reliable, consistent, and compliant annotations that meet the most demanding industrial requirements.

Infoscribe applies a particularly rigorous quality control and internal audit process for industrial projects, especially those involving critical applications related to safety, compliance, or traceability. The goal is to ensure maximum accuracy, perfect consistency, and reliability that meets the high standards of industrial environments.

1. Implementation of Strict, Standardized Guidelines

Before any annotation, detailed guidelines are developed in collaboration with the client. They define:

  • object classes,
  • quality criteria,
  • acceptable tolerances,
  • exceptions,
  • edge cases.

These documents serve as a normative reference for the entire team.

2. Specialized Annotator Training

Annotators receive dedicated industrial training, including:

  • understanding parts, machines, or components,
  • identifying defects or anomalies,
  • mastering 2D/3D annotation tools,
  • practicing according to the guidelines.

Evaluation tests validate their capability before joining the project.

3. Systematic Double Quality Control

Each batch of annotations undergoes multiple verification levels:

  • review by a senior annotator,
  • quality supervisor check,
  • double annotation on critical samples,
  • inter-annotator comparison to detect discrepancies.

Detected deviations are automatically flagged and corrected.

4. Regular Internal Audits

Infoscribe conducts weekly or monthly audits depending on project criticality. These include:

  • checking overall consistency,
  • statistical error analysis,
  • assessing compliance with guidelines,
  • adjusting processes as needed.

Audits follow industrial sampling methods such as ISO 2859.

5. Full Traceability

Each annotation is linked to:

  • annotator ID,
  • timestamp,
  • version of guidelines used,
  • history of corrections.

This traceability ensures full compliance for sensitive applications (safety, certification, client audits).

6. Continuous Communication with the Client

Regular check-ins allow adjustment of requirements, anticipation of deviations, and maintenance of stable quality levels.

This comprehensive process ensures a level of quality that meets the strict requirements of industries demanding precision, safety, and traceability.

Infoscribe adapts its annotation workflows to varying parts, materials, or production conditions across industrial sites by implementing a flexible and progressive methodology. The company begins with a detailed analysis of each industrial environment, considering differences in lighting, dust presence, color or texture variations of parts, and the specific characteristics of machines and assembly lines. This step ensures a precise understanding of the visual constraints and the challenges related to detection, classification, or inspection of the components.

Next, site- or part-specific guidelines are developed, taking into account industrial tolerances, expected defects, dimensional variations, and special cases. These evolving documents ensure annotation consistency while respecting operational differences between sites.

Annotators then receive dedicated training, including an introduction to the site-specific characteristics, parts, or materials. This training can include examples, exercises, or calibration sessions to ensure perfect consistency within the team despite diverse environments.

During production, Infoscribe uses a dynamic quality control system that allows rapid adjustments to guidelines or practices if significant variations are observed in the data. Client feedback, regular audits, and variance analysis help maintain a high level of accuracy.

Thanks to this adaptable approach, Infoscribe can guarantee reliable and consistent annotations, even when industrial conditions vary significantly from site to site.