GeoMonitor Optimization Engine — GIS analysis for maintenance decisions
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2) Intro (helder wat je wilt)
"I'm looking for a GIS / geospatial developer to build a working version of an Optimization Engine that analyzes historical maintenance, visit and incident data per asset and generates EMVI-relevant insights and recommendations. The goal is to provide measurable decision support for maintenance adjustments."
Geen vaag "optimization", maar "data-gedreven beslissingsondersteuning".
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3) Scope (MVP deliverable)
A) Data Inputs
•Connect to ArcGIS Feature Services / GeoJSON layers
•Read:
•Asset layer (points/polygons)
•Maintenance history (visits/actions)
•Incident/melding layer
B) Core Functions
Provide EMVI-relevant metrics:
•Visit frequency per asset
•Incident frequency per asset
•Visit-to-incident ratio
•Hotspot detection on incidents
•Cost proxy estimate per asset based on visit count
Generate Recommendation Layer:
•Suggested frequency change (up/neutral/down)
•Hotspot flag
•Reason (explicit metrics)
•Confidence score (based on data volume)
C) Output
•Write results to a GIS table / layer named "OptimizationRecommendations"
•Each record:
•assetID
•suggestedAction
•reason
•confidenceScore
•relevantMetrics
D) Simple UI
A lightweight interface:
•Map with recommendation layer
•List of assets with filter
•Click to view decision metrics
Keep UI minimal — focus on useful info, not UX polish.
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4) Technical Requirements
•ArcGIS Experience Builder widget OR lightweight web app
•Configurable field mapping (important for reuse)
•Clean, documented code
•No advanced ML in MVP
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5) Out of Scope
•Full AI/ML models
•Workflow enforcement / execution tracking
•Mobile app
•Complex dashboards
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6) Budget & Terms (unchanged)
•Fixed budget: $3,500
•Deliver working build + install instructions + documentation
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7) Timeline
•4–6 weeks max
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8) Experience required
Applicants must show:
•ArcGIS development
•Geospatial analysis
•Understanding of metrics generation
•Examples of similar analysis layers
Contract duration of less than 1 month.
Mandatory skills: Python, Data Science, GIS, Data Analysis, ArcGIS