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About Workshop

This workshop trains participants to use drone-based computer vision for inspecting transmission lines and assessing wildfire risks. It covers data capture, flight planning, model development for defect detection and vegetation encroachment, and risk mapping, enabling participants to generate actionable reports for improved safety and decision-making.

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Aim

The aim of this workshop is to teach participants how to use drone-based computer vision for inspecting transmission lines and assessing wildfire risks, covering data capture, model development, and integration of risk mapping for actionable insights.

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What Participants Will Learn

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Master drone operations for transmission line inspections and wildfire risk assessment.
Learn flight planning, safety compliance, and data capture techniques.
Develop computer vision models for defect detection and vegetation monitoring.
Integrate computer vision outputs with wildfire risk data for actionable maps.
Generate reports combining inspection findings and risk analysis.

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Structure

📅 Day 1 – Foundations & Data Capture

Mission scope: defects, vegetation encroachment, wildfire ignition cues
Platforms & payloads: multirotor vs fixed-wing; RGB/thermal/multispectral; radiometric & geo calibration
Flight planning & compliance: geofencing, BVLOS limits, safety near energized lines
Data & labels: imagery/video, orthos/point clouds; annotation schema & severity tags
Hands-on: Plan a corridor mission (flight lines, camera settings) and produce a data-collection checklist

📅 Day 2 – Computer Vision Pipeline

Preprocessing: sync/geotag, deblur/distortion, tiling, class balance
Models: detection/segmentation for hardware & insulators; vegetation encroachment; thermal hotspot flags
Robustness & evaluation: glare/motion/scale, active learning; precision/recall, per-class AP, uncertainty gates
Hands-on: Fine-tune a compact detector+segmenter and export inference (boxes/masks) with a defect/encroachment summary

📅 Day 3 – Wildfire Risk & Operations

Risk layers: fuel dryness, slope/aspect, weather/Red-Flag indices, proximity to lines, prior ignitions
Fusion & workflow: combine CV outputs with terrain/weather; triage queue, human-in-the-loop, CMMS ticketing
Deployment: edge vs cloud inference, bandwidth limits, encryption, model drift/rollback
Hands-on: Build a corridor risk map and generate a one-page report with geotagged findings, risk ranking, and actions

Important Dates

Workshop Dates

Coming Soon

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What You Will Gain

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Outcomes

Proficiency in drone-based data capture for transmission line inspections and wildfire risk assessment.
Hands-on experience in developing and fine-tuning computer vision models for defect detection and vegetation encroachment.
Ability to integrate computer vision outputs with environmental and wildfire risk layers.
Skills to generate actionable risk maps and operator-ready reports.
Enhanced understanding of flight planning, compliance, and safety protocols for drone operations.

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Who Should Attend

Professionals in electrical engineering and infrastructure maintenance
Researchers in wildfire management and environmental monitoring
Individuals working with drone technology, computer vision, or data analytics
Those involved in transmission line inspection and vegetation management
Professionals focused on wildfire risk assessment
Basic knowledge of drones and computer vision recommended but not required

Computer-Vision Drone Inspector for Transmission Lines & Wild-Fire Risk.