Fix #635: Implement Smart Location Intelligence and Geospatial Analytics

[SatyamPandey-07]

✅ Key Features Implemented:

Geospatial Transaction Model: Updated
models/Transaction.js
to support GeoJSON storage. Every transaction now has a location (Point) and formattedAddress field, along with a 2dsphere index for high-speed spatial queries.
Location Intelligence Cache: Created
models/Place.js
to store and reuse geocoded location data. This prevents redundant API calls and ensures that spending at the same merchant is consistently grouped.
Proximity Search Engine: Implemented
findNear
in
services/locationService.js
, allowing users to query expenses based on their physical location (e.g., "expenses within 5km of my current position").
Spending Hotspot Clustering: Developed a custom clustering algorithm in
services/locationService.js
that groups nearby transactions into "Hotspots." This identifies physically dense spending zones (e.g., shopping malls or specific neighborhoods).
Automated Geocoding Job: Built
jobs/geocodingJob.js
for background processing. It scans historical transactions and uses the geocoding engine to backfill missing location data.
New API Suite:
GET /api/maps/nearby: Proximity searching.
GET /api/maps/hotspots: Spending density analysis.
POST /api/maps/backfill: Manual trigger for location backfilling.

closes #635

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[github-actions]

🎉 Thanks for the PR, @SatyamPandey-07!

We really appreciate you taking the time to contribute to ExpenseFlow! 💙

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