1. Project Overview

The Telemetry Data Processing System was developed as a web-based platform for collecting, validating, processing, storing, and visualizing telemetry data received from remote devices. The system was designed to automate incoming data handling from external sources and convert raw telemetry/SMS payloads into structured operational records for monitoring and reporting.

The project focused on backend reliability, clean architecture, maintainability, and secure data handling.

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2. Business Problem

Organizations receiving telemetry feeds often struggle with:

• Manual processing of raw device messages n- Inconsistent data formats
• Difficulty validating corrupted or incomplete payloads
• Lack of centralized dashboards
• Poor audit logging and traceability
• Delays in converting incoming data into actionable insights

The objective was to build a centralized system that automatically ingests telemetry data, validates it, stores it in a database, and presents usable outputs to operators.

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3. Solution Delivered

A custom web application was built using PHP with the Slim Framework following MVC-inspired modular practices.

Core Features

• SOAP-based communication with remote telemetry sources
• SMS / raw message parsing engine
• Validation of telemetry payloads
• Structured storage in MySQL database
• Secure authentication and session handling
• Web dashboard for processed records
• Search and filtering tools
• Error and event logging using Monolog
• Templated UI using Twig
• Version controlled delivery using GitHub

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4. Technology Stack

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5. System Architecture

Remote Devices / Providers
        |
        v
   SOAP Interface
        |
        v
 Slim PHP Application
 ├── Authentication Module
 ├── Telemetry Parser
 ├── Validation Engine
 ├── Business Logic Layer
 ├── Dashboard Controllers
 └── Logging Layer
        |
        v
     MySQL Database
        |
        v
   Twig Frontend Views

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6. Key Responsibilities & Contributions

Backend Development

• Designed API endpoints and request routing using Slim Framework.
• Implemented telemetry ingestion workflows.
• Built parsing logic for raw SMS/device payloads.
• Developed validation rules for malformed or missing values.

Database Engineering

• Designed relational schema for incoming records, users, logs, and processed telemetry.
• Optimized inserts and retrieval queries.

Security & Sessions

• User login flow.
• Session protection.
• Controlled dashboard access.

Monitoring & Reliability

• Added Monolog logging for:

  • Request failures
  • Parsing issues
  • SOAP communication errors
  • Authentication events

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7. Functional Modules

7.1 Authentication Module

• Login / Logout
• Session management
• Role-based access control

7.2 Telemetry Intake Module

• Receive messages from external source
• SOAP requests/responses
• Queue and process incoming data

7.3 Parsing Engine

• Decode raw payload structure
• Extract metrics, timestamps, IDs, statuses

7.4 Validation Module

• Mandatory field checks
• Numeric ranges
• Timestamp integrity
• Duplicate detection

7.5 Dashboard Module

• View processed telemetry records
• Search by device/date/status
• Review failed records

7.6 Logging Module

• System events
• Exceptions
• Audit trails

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8. Database Design (High-Level)

Tables Included

• users
• telemetry_records
• raw_messages
• device_registry
• error_logs
• sessions

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9. Data Flow Diagrams (DFD)

Level 0 – Context Diagram

+------------------+          Telemetry Data          +------------------------------+
| External Devices | -------------------------------> | Telemetry Processing System |
+------------------+                                  +------------------------------+
         ^                                                         |
         |                                                         v
         |                                                 Processed Reports
         |                                                         |
         |                                                         v
                                           +-------------------------------+
                                           | Admin / Operations Users      |
                                           +-------------------------------+

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Level 1 – Major Process Flow

                 +------------------+
                 | External Source  |
                 +------------------+
                          |
                          v
                 (1) Receive Data
                          |
                          v
                 (2) Parse Payload
                          |
                          v
                 (3) Validate Data
                    /          \
                   /            \
                  v              v
        Store Valid Data     Store Error Logs
               |                  |
               v                  v
         MySQL Database      Logging System
               |
               v
        (4) Generate Dashboard
               |
               v
          Admin Users

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Level 2 – Validation Subsystem

Incoming Payload
      |
      v
+-------------------+
| Check Required    |
| Fields            |
+-------------------+
      |
      v
+-------------------+
| Verify Format /   |
| Data Types        |
+-------------------+
      |
      v
+-------------------+
| Duplicate Check   |
+-------------------+
      |
      v
+-------------------+
| Accept / Reject   |
+-------------------+

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10. Challenges Solved

Multiple Input Formats

Different telemetry sources produced inconsistent payloads. Flexible parsing logic was implemented.

Reliability

Communication failures were logged and isolated without crashing the application.

Data Quality

Validation reduced corrupt records entering the reporting system.

Maintainability

Slim Framework routing and modular components improved readability and future enhancements.

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11. Results & Impact

• Reduced manual telemetry handling effort
• Faster operational visibility
• Cleaner and validated records
• Centralized monitoring dashboard
• Easier troubleshooting through logs
• Scalable foundation for future integrations

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12. What This Project Demonstrates

This project demonstrates capability in:

• Backend engineering
• Systems integration
• API communication (SOAP)
• PHP application architecture
• Database design
• Data validation pipelines
• Logging & observability
• Secure admin systems

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13. Future Enhancements

• REST API expansion
• Real-time dashboards
• WebSocket live telemetry updates
• Alert engine for threshold breaches
• Device analytics reports
• Role-based advanced permissions
• Cloud deployment with Docker

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14. Conclusion

The Telemetry Data Processing System successfully transformed raw incoming telemetry data into structured business information through automated ingestion, parsing, validation, storage, and visualization. It provided a dependable backend platform with strong maintainability and operational value.