Programme Parameters
Advanced Postgrad
3 Days (4.5 Hrs)
Online (e-LMS)
• Prior working knowledge of the field and comfort with core tools and quantitative reasoning.
• A laptop or desktop with a stable internet connection.
• Willingness to complete assignments and the capstone project.
About This Course
This course empowers participants with the expertise to deploy drone-based computer vision for critical infrastructure inspection and environmental risk assessment. Every participant receives a verified e-Certificate and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
This course empowers participants with the expertise to deploy drone-based computer vision for critical infrastructure inspection and environmental risk assessment.
📋 Course Objectives
1. Apply AI Enablement methods to authentic research and industry problems.
2. Build a defensible project you can showcase to supervisors, reviewers, or employers.
👥 Who Should Enroll?
• Master's and senior undergraduate students specializing in AI Enablement
• R&D engineers and working professionals applying AI Enablement in industry
• Academics and educators building research or teaching capacity in AI Enablement
🚀 Key Learning Outcomes
• A demonstrable AI Enablement project for your research or industry portfolio.
• A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
💎 What You'll Gain
Live & Recorded Sessions
Lifetime access to class recordingse-Certificate on Completion
Cryptographically verified credentialPost-Programme Support
Direct access to mentors & councilHands-On Experience
Notebooks, real-world code & datasetsCurriculum Outline
Drone Inspection Fundamentals & Data Capture
Define mission scope for defects, vegetation encroachment, and wildfire ignition cues. • Evaluate drone platforms and payloads (RGB, thermal, multispectral) for inspection tasks. • Plan safe and compliant flights, adhering to geofencing, BVLOS limits, and energized line safety. • Capture and manage imagery, video, orthomosaics, and point clouds.
Advanced Computer Vision Pipeline for Inspections
Preprocess drone data, including synchronization, geotagging, deblurring, and tiling for model readiness. • Develop and train computer vision models for defect detection (hardware, insulators). • Implement models for vegetation encroachment monitoring. • Integrate thermal hot-spot detection capabilities within the vision pipeline.
Wildfire Risk Assessment & Operational Integration
Identify and integrate various wildfire risk layers: fuel dryness, slope, weather, and historical ignitions. • Combine computer vision outputs with terrain and weather data for a holistic view. • Design efficient triage queues and human-in-the-loop validation processes. • Implement CMMS ticketing for identified defects and risks.
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | Drone platforms (multirotor |
| Covered Tool / Platform | fixed-wing) |
| Covered Tool / Platform | RGB Cameras |
| Covered Tool / Platform | Thermal Cameras |
| Covered Tool / Platform | Multispectral Sensors |
| Covered Tool / Platform | Flight Planning Software |
| Covered Tool / Platform | Image Annotation Tools |
| Covered Tool / Platform | Computer Vision Frameworks |
| Covered Tool / Platform | GIS Software |
Frequently Asked Questions
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