CASE STUDY

Bluetooth Based Mobile to Raspberry Pi Communicator POC

Proof Of Concept

Integration POC

Integration POC

Overview

A proof of concept (POC) was developed to demonstrate secure and efficient Bluetooth communication between mobile devices and Raspberry Pi Zero for automated lighting control. The system implements a centralized decision-making architecture where the Raspberry Pi validates user proximity and authenticity before triggering LED activation. This POC successfully validates the feasibility of using Bluetooth Low Energy (BLE) for reliable device-to-device communication in IoT applications while maintaining security through centralized authentication.

The Challenge

The POC aimed to validate a Bluetooth-based communication system that could:

  • Accurately detect and authenticate authorized users
  • Activate lighting only for valid users within a specific proximity
  • Maintain security by preventing unauthorized access
  • Operate reliably in environments with multiple Bluetooth signals
  • Function continuously with minimal maintenance
  • Scale efficiently for multiple users and access points

Key technical challenges included:

  • Managing Bluetooth signal interference in busy environments
  • Ensuring real-time response despite processing limitations
  • Maintaining system security while allowing easy access for authorized users
  • Optimizing power consumption for continuous operation
  • Handling regular data synchronization without disrupting core functionality

Our Solution

The system follows a centralized decision-making architecture where the Raspberry Pi acts as the primary control unit. The process flow is as follows:

    • Mobile Broadcasting
    • Mobile device continuously broadcasts its unique ID via Bluetooth
    • Broadcasts occur at regular intervals in the background
    • Signal Reception & Distance Calculation
    • Raspberry Pi constantly scans for Bluetooth broadcasts
    • Upon receiving a signal, calculates distance using RSSI values
    • Implements distance threshold checking
    • User Validation
    • For nearby devices, system checks user validity against cached list
    • Valid user list is synchronized with cloud database periodically
    • Maintains local cache for offline operation
    • Action Execution
    • Valid users within range trigger LED activation
    • System maintains state for continuous operation
    • Implements debouncing to prevent rapid switching

Integrated System Components

Hardware Components

  • Raspberry Pi Zero (Central Control Unit)
  • LED lighting system
  • Mobile devices (User Interface)
  • WiFi router (2.4GHz connectivity)

Raspberry Pi Application

  • Python-based core application
  • Bluetooth signal processing module
  • Distance calculation algorithm
  • Local cache management system
  • Authentication validation module
  • LED control interface

Mobile Application (Flutter)

  • Cross-platform mobile app (iOS/Android)
  • Bluetooth broadcasting module
  • Background service management
  • User authentication interface
  • Configuration settings

Performance Optimizations

Signal Processing

  • Implementation of signal filtering algorithms
  • RSSI averaging for accurate distance calculation
  • Debouncing to prevent rapid on/off switching

Resource Management

  • Efficient cache management
  • Optimized Bluetooth scanning intervals
  • Background process prioritization
metro-collage

Technical Achievements

Performance Metrics:

  • Average response time: < 500ms
  • False positive rate: < 0.1%
  • System uptime: 99.9%
  • Synchronization success rate: 99.5%

Scalability Features:

  • Support for multiple concurrent users
  • Expandable to multiple access points
  • Flexible configuration options
  • Easy integration capabilities

Conclusion

The Smart Proximity Detection System successfully demonstrates the practical application of IoT technology in creating intelligent environments. By combining affordable hardware with sophisticated software solutions, the system delivers reliable, secure, and user-friendly automated lighting control.
The implementation overcame significant technical challenges while maintaining high performance and security standards. The solution's modular architecture and scalable design make it suitable for various applications beyond lighting control, establishing a foundation for future IoT implementations.

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Location

Ahmedabad, Mumbai

USA, Spain

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