Smartphone-Based, Field-Deployed AI Inspection System for Power Distribution Infrastructure

Key points

• Routine inspection of power distribution infrastructure remains challenging for utilities operating geographically dispersed networks, where conventional manual inspection can be difficult to perform consistently and at scale.1
• The proposed workflow integrates image-quality and viewing-perspective validation with AI-assisted assessment of pole lean, crossarm and top-cleat tilt, voltage level, vegetation-clearance risk, and distribution-transformer (DTR)-ground clearance.1
• The system integrates deep-learning models with monocular depth estimation, geometric analysis, and rule-based processing within a common multi-stage inspection workflow designed for practical field operation.1
• A curated multi-module field-captured dataset, PD-Defect, is also publicly released to support reproducible research in distribution-infrastructure inspection.1

Sources (1)

• [1]Smartphone-Based, Field-Deployed AI Inspection System for Power Distribution Infrastructure
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 13, 02:42 AM

  This work presents a smartphone-based AI inspection system for assessing targeted distribution-infrastructure conditions from images captured by field personnel.

  Routine inspection of power distribution infrastructure remains challenging for utilities operating geographically dispersed networks, where conventional manual inspection can be difficult to perform consistently and at scale.

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