Warehouse Monitoring & Geofencing

GPS-based geofenced clock-in/out and warehouse presence monitoring to help identify unmanned godown situations.

Role: Backend / Full Stack Developer

Location context: India

Overview

Functionality for monitoring warehouse presence and identifying potentially unmanned warehouses through employee geolocation and geofenced attendance tied to warehouse boundaries.

Challenge

Operations teams needed visibility into whether required staff were physically present at mapped warehouse locations.

Approach

Built location-based validation against warehouse boundaries with Rails backend APIs supporting clock-in, clock-out, and presence monitoring logic.

Key contributions

Contributed to business logic for warehouse presence monitoring
Worked on geofenced employee check-in and check-out
Implemented location-based validation against warehouse boundaries
Worked on employee-to-godown mapping and geolocation-related functionality
Contributed to logic for identifying warehouses without required personnel presence
Built and supported Rails backend APIs for location and attendance workflows

Key features

Geofenced clock-in and clock-out
GPS coordinate capture
Warehouse boundary validation
Employee and godown mapping
Warehouse presence monitoring
Unmanned warehouse detection logic

Technology stack

Frontend: React
Backend: Ruby on Rails
Database: MySQL
Infrastructure: Linux, Nginx, Puma
Integrations: GPS / Geolocation services

Technical challenges

Location accuracy vs business rules

Problem: GPS data can be inconsistent while attendance rules still need to be enforceable.

Solution: Geofence validation against defined warehouse boundaries with backend rule checks.

Timeline

Feature development within warehouse operations platform

Part of the broader NCML Storeman warehouse platform.