Ground patrol analytics and inspection priorities

Preparing inspection records, assigning consistent priorities, and reviewing work orders and defects in GIS and Power BI.

What I did

I developed inspection-data preparation and priority-assignment workflows, alongside GIS and Power BI views for examining inspection progress, defects, and work orders.

Result: The work provided structured inspection records, consistent rule-based assignments, and reporting views for reviewing progress and maintenance needs.

Tools

  • Python
  • pandas
  • SQL
  • ArcPy
  • ArcGIS
  • Power BI

This case study presents related historical processing and reporting components. It does not establish a single automated Power BI refresh chain or a measured cost-savings result. Client records and infrastructure details remain private.

Preparation, rules, and reporting

The project combined data preparation, inspection-priority logic, and analytical views. The diagram separates these components so that the reporting work and the underlying processing are clear.

Ground patrol data preparation, priority rules, and reporting components
An explanatory diagram of related project components. Connections within each row describe the method; the diagram does not assert an automated connection between the rows. Scroll horizontally to explore the diagram.

Prepare records for comparison

Historical inspections arrived in spreadsheets and year-specific exports. Python preparation converted workbook data to CSV, retained relevant inspection and asset attributes, added the reporting year, and combined selected yearly files.

A related SQL workflow joined work orders to asset locations, parent locations, and structure attributes. Python normalized dates and coordinates, while ArcPy created point features and added hazard-area context through a spatial overlay.

Make priority assignments explicit

Condition codes mapped to a priority, work type, and job plan. When a record contained several findings, the calculation selected the lowest numerical priority. If equally urgent findings called for repair and replacement, replacement took precedence.

These were deterministic business rules. The examples below illustrate the selection logic using hypothetical findings.

Illustrative priority selection
Findings on one recordSelected actionReason
Priority 1: repair; priority 2: replacePriority 1: repairThe lower numerical priority takes precedence.
Priority 1: repair; priority 1: replacePriority 1: replaceReplacement takes precedence at equal priority.

Review the operational questions

The GIS dashboard organized inspection progress, status, priorities, and geography. Power BI views expanded the analysis to work-order status, recurring defects, job plans, and cost summaries, with filters for reporting year, material, and location.

Questions addressed by the reporting views
QuestionView
Where does inspection work remain?Inspection status and progress with a map.
Which defects and priorities recur?Comparisons by reporting year, damage category, and asset material.
What maintenance work is represented?Work-order status, job-plan, and geographic summaries.
How are recorded costs distributed?Yearly and circuit-level cost summaries.
Technical details

Independent consulting · Utility inspection analytics

Inspection findings, asset attributes, and work orders needed a consistent basis for comparison across locations and reporting years.

  • Prepare spreadsheet and CSV exports with relevant inspection attributes and reporting years.
  • Join work orders to asset records and add geographic context for GIS use.
  • Apply explicit condition rules to assign priority, work type, and job plan.
  • Present inspection status, defect patterns, priorities, and cost summaries in reporting views.

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