CASE STUDY / 03

Industrial IoT Fuel Monitoring Platform

An end-to-end industrial monitoring platform that connects on-site fuel instrumentation, IoT gateways, cloud services, data storage, and web-based monitoring into a unified system.

ROLE Embedded Developer

PLATFORM Industrial IoT / Cloud

STACK C++ · Java · Embedded Linux · MQTT · Azure · PostgreSQL

In field fuel dispensing system with ESP32 controller

Mobile fuel dispensing system with ESP32 controller

In field fuel dispensing system with ESP32 controller

Tank monitoring system

Overview

This project is an Industrial IoT platform designed to collect, process, store, and visualize fuel monitoring data from multiple field devices. The system connects flow meters, fuel tank instrumentation, RFID readers, ATG consoles, and fuel dispensing systems to an on-site IoT Gateway. The gateway acts as the bridge between industrial equipment and the cloud platform, providing local data acquisition, temporary storage, and telemetry forwarding. Cloud services then process and distribute the data for storage, application services, and browser-based monitoring.

The Problem

Industrial fuel operations often involve multiple independent systems and field instruments. Flow measurement, tank levels, user identification, and existing fuel management systems may use different communication interfaces and protocols. Without a unified data pipeline, operational data can become fragmented across local controllers and systems.

01 Multi-device integration

Connect flow meters, tank level meters, RFID readers and existing fuel systems through different field interfaces.

02 Real-time telemetry

Collect operational data from on-site equipment and transmit telemetry to the cloud through the IoT gateway.

03 Unified data pipeline

Route field data through cloud services for event processing, messaging, storage and backend application services.

04 Operational traceability

Store measurement and transaction data in centralized databases and data storage for monitoring and historical analysis.

SYSTEM DESIGN

Architecture

An end-to-end industrial IoT architecture connecting field instrumentation, edge data acquisition, cloud processing, and web-based monitoring.

Technology

LANGUAGEC++, Java

FRAMEWORKQt / Qt Widgets

HARDWAREESP32, ATG, LC M10

OSEmbedded Linux

PROTOCOLModbus RTU / RS485

CONTROLGPIO

DATABASESQLite

DEPLOYMENTMicrosoft Azure

Key Features

Multi-Protocol Device Integration

Integrates industrial equipment using Digital I/O,RS232, RS485, and WiFi.

Edge Data Logging

Local SQLite storage provides buffering and historical data logging at the site.

Cloud Telemetry

Field data is forwarded from the gateway to Azure IoT Hub for centralized processing.

Event-Driven Processing

Azure Functions process incoming telemetry without requiring a continuously running processing server.

Scalable Data Pipeline

Data Lake, PostgreSQL, and Service Bus separate telemetry storage, structured operational data, and application messaging.

Web-Based Monitoring

Operational data can be accessed through a browser-based monitoring application.

ENGINEERING NOTE

Designed around
the machine, not just the screen.

The application architecture separates the operator interface, process data and machine-control responsibilities. This makes the system easier to test, maintain and extend as additional field devices are introduced.