Case Study: BLE Proximity Tracking for Real-Time Supervisor Monitoring at Shankar Masala

The Core Problem

Factory environments often lack the infrastructure or conditions for traditional GPS-based tracking systems to function effectively. At Shankar Masala, management had no reliable way to monitor supervisor movements across critical zones. Manual systems were being used but lacked accuracy and transparency.

Limitations of Previous System:

• Manual logbooks were time-consuming, often inaccurate, and prone to tampering
• GPS-based staff tracking failed inside the factory, due to thick walls, metal obstructions, and signal drop
• Supervisors frequently skipped zones unnoticed, leading to reduced quality control oversight
• Wearable GPS or RFID systems were either too expensive, not scalable, or required frequent maintenance

Solution Overview: BLE-Based Proximity Tracking System

Amar Infotech designed and deployed a BLE Beacon–powered Proximity Node system integrated with a Node.js backend, offering automated zone-level staff tracking.

Key Deliverables:

• Uses Bluetooth Low Energy (BLE) beacons with 8–10 ft detection range.
• Requires no manual check-in or RFID swipe.
• Runs via mobile app in the supervisor’s smartphone
• Automatically logs entry, exit, and time spent in each production zone
• Sends data in real-time to a centralized Node.js + NextJS dashboard.

How Amar InfoTech Implement Technical Architecture

The system is designed using scalable, modern technologies that ensure reliability and ease of use for non-technical factory staff. Here's a breakdown of how each component works together to deliver real-time indoor location tracking.

BLE Beacons (Installed Hardware)

• Battery-powered, 3–4 years lifespan
• Mounted in key locations
• Short-range (8–10 ft) accurate detection
• Dust & humidity resistant (IP65)

Mobile App (For Supervisors)

• Lightweight, runs in background
• Bluetooth enabled, detects nearby beacons
• Automatically logs entry/exit without manual action
• Android and iOS support

Backend (Node.js + Express)

Built using Node.js and Express, the backend handles real-time detection events, stores secure time-series logs, and enables data queries for reports, analytics, and AI applications.

• Real-time data logging and sync
• Secure storage of logs
• Time-series structure for analytics
• Time-series structure for analytics

Dashboard (AngularJS 5)

An easy-to-use dashboard for plant managers provides visual insights into daily activity, enabling faster decisions, better shift auditing, and reduced administrative load.

• Live zone tracking
• Performance summaries per supervisor
• Alerts for skipped zones
• Downloadable reports (CSV/PDF)

Why BLE Works Where GPS Fails

Manufacturing plants are typically GPS dead zones due to their construction materials and layout. BLE, on the other hand, is designed for short-range indoor tracking and excels in environments where GPS cannot operate effectively.

• GPS fails indoors due to walls, machinery, and signal blocks
• BLE uses short-range wireless, ideal for factory environments
• BLE beacons are battery-operated, requiring no wiring or power
• BLE offers precise room-level tracking (unlike GPS's 10m+ error margin)

Why BLE Works Where GPS Fails

This BLE-based proximity system is ideal for several industrial applications beyond just supervisor monitoring. It opens up possibilities for automating audits, enforcing compliance, optimizing worker allocation, and enabling AI-ready indoor location analytics in factories where GPS tracking fails.

• Supervisor zone-wise presence logging using BLE beacons – Automatically track supervisor movements in real-time for each production area, improving accountability and traceability
• BLE-powered time & attendance automation for factory staff – Eliminate punch cards and manual logbooks with automatic proximity detection and attendance logs
• Operator-machine presence validation system – Ensure the right operator is present at the right machine during operation hours using proximity-based confirmation
• Real-time contractor and visitor movement tracking system – Monitor short-term visitors, maintenance staff, or third-party contractors without needing ID badges or escorts
• Assembly line productivity analysis using BLE tracking – Measure time spent at each station, detect workflow bottlenecks, and optimize line efficiency
• Restricted zone access compliance with beacon-based detection – Automate safety compliance in hazardous or sterile zones by logging only authorized personnel presence
• BLE-based emergency response and evacuation audit – Track real-time presence and last-known location of staff in the event of a fire or evacuation
• Indoor logistics tracking in packaging and dispatch areas – Monitor staff presence in logistics-sensitive areas where timing affects shipping and inventory
• Cleanroom entry monitoring in food and pharmaceutical factories – Automatically detect and log staff presence in temperature- or contamination-sensitive areas
• Shift changeover monitoring in industrial environments – Log presence during shift overlaps to ensure proper handoffs and safety briefings
• AI-powered factory workforce heatmaps and zone utilization – Visualize which areas are most visited and detect anomalies using AI-integrated BLE data
• Workforce audit trail without GPS or RFID infrastructure – Use low-power BLE tracking for accurate indoor history logging in GPS-denied environments

Generative AI for Indoor Workforce Tracking and Factory Analytics

The data captured through BLE proximity tracking is highly structured, making it perfect for integration with Generative AI systems. AI and ML tools can use this data to generate shift summaries, detect patterns, and predict inefficiencies. With natural language processing and predictive analytics, factory operations can be monitored and queried in real time using simple human language.

Our system is AI-ready and supports:

• Natural language queries (e.g., "Who missed QC zone yesterday?")
• Auto-generated shift reports for daily or weekly reviews
• Time-spent anomaly detection using AI pattern recognition
• Integration with HRMS and ERP systems to correlate proximity data with payroll, attendance, and performance
• Predictive analytics on zone visits and movement patterns to identify inefficiencies or risks in workforce deployment

Common use cases for Generative AI in factory dashboards include automated answers to everyday operational queries, real-time alerts, and shift report generation. These can be triggered through simple voice commands or typed queries such as:

• "Show supervisor time logs for packaging zone last week"
• "Alert me if no one visits quality control for 30 minutes"
• "Download visit report for Shift A on June 15th"
• "Who skipped the dispatch zone today?""Who skipped the dispatch zone today?"