ESP32 IoT Sensor Node with Edge Filtering

Overview

This project simulates the core logic of an IoT sensor node designed for ESP32-based edge monitoring applications.

The node is intended to:

• acquire sensor data
• apply lightweight edge filtering
• detect events locally

ESP32 IoT Sensor Node with Edge Filtering, MQTT-Ready Telemetry, and Azure-Ready Integration

📌 Overview

This project demonstrates the architecture of an ESP32-style IoT sensor node designed for edge monitoring and cloud-ready telemetry applications.

The project includes:

• simulated sensor data acquisition
• edge-side filtering
• threshold-based event detection
• firmware-style sample-by-sample node logic
• telemetry packet generation
• heartbeat/status messaging
• MQTT-ready topic routing
• Azure-ready telemetry schema design

This project highlights skills in:

• IoT system architecture
• Embedded-oriented firmware logic
• Edge filtering and event detection
• Telemetry design
• MQTT-style communication flow
• Azure-ready cloud integration thinking

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🎯 Objective

• simulate a real-time sensor stream
• apply lightweight edge filtering
• detect threshold-based events locally
• generate telemetry, heartbeat, and event packets
• organize a mock MQTT telemetry flow
• build Azure-ready packet structures for future cloud integration

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⚙️ Methodology

1. Sensor Stream Simulation

A time-series sensor signal is simulated with:

• baseline dynamics
• Gaussian noise
• injected event spikes

This represents the behavior of a real embedded sensing system under noisy operating conditions.

2. Edge Filtering

A lightweight moving-average filter is applied to the raw signal to mimic edge-side preprocessing on a constrained embedded device.

3. Local Event Detection

Threshold-based logic is used to detect relevant signal events locally on the node.

This reflects a common IoT pattern:

• collect raw signal
• preprocess locally
• trigger event-driven communication when needed

4. Firmware-Style Node Design

A firmware-style node class was developed to simulate ESP32-like sample-by-sample execution.

The node performs:

• filtering
• event detection
• telemetry packet generation
• heartbeat generation

5. MQTT-Ready Pipeline

A mock MQTT broker and publisher were implemented to test:

• telemetry publishing
• heartbeat topic flow
• event topic flow
• topic-based routing structure

6. Azure-Ready Packet Design

A cloud-ready telemetry schema was added with:

• device metadata
• firmware version
• message type
• signal quality
• heartbeat status
• event severity

This makes the project closer to real Azure IoT integration patterns.

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📊 Example Results

🔹 Raw vs Filtered Signal

🔹 Event Detection

🔹 ESP32-Style Filtered Signal

🔹 ESP32-Style Event Detection

🔹 MQTT-Ready Event Summary

🔹 MQTT-Ready Heartbeat Summary

🔹 Azure-Ready Event Summary

🔹 Azure-Ready Heartbeat Summary

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✅ Baseline Sensor Processing

The initial stage of the project established:

• raw sensor signal simulation
• edge-side filtering
• local event detection

This created the core sensing and signal-processing logic for the rest of the system.

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✅ Firmware-Style IoT Node

A step-based ESP32-style node implementation was built to support:

• one-sample-at-a-time processing
• telemetry packet creation
• heartbeat logic
• local event flagging

Generated packet counts:

• Telemetry packets: 601
• Heartbeat packets: 31

This confirms the node behaves as a periodic telemetry source with background health monitoring.

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✅ MQTT-Ready Pipeline

A mock MQTT pipeline was created to simulate:

• telemetry publishing
• heartbeat publishing
• event-based publishing
• topic routing

Generated packet counts:

• Telemetry packets: 601
• Heartbeat packets: 31
• Event packets: 48

This stage demonstrates an IoT-ready message flow architecture without requiring a live broker.

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✅ Azure-Ready Telemetry Architecture

The telemetry system was extended with Azure-style packet structures that include:

• device ID
• device type
• firmware version
• location
• cloud timestamp
• message type
• signal quality
• heartbeat status
• event severity

Generated packet counts:

• Telemetry packets: 601
• Heartbeat packets: 31
• Event packets: 48

This confirms that the node and telemetry architecture are ready for future Azure IoT Hub integration.

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📁 Project Structure

esp32-iot-sensor-node/
│
├── src/
│   ├── main.py
│   ├── esp32_node.py
│   ├── test_esp32_node.py
│   ├── mqtt_client_mock.py
│   ├── test_mqtt_pipeline.py
│   ├── azure_packet_builder.py
│   └── test_azure_ready_pipeline.py
│
├── data/
├── results/
├── figures/
│
├── README.md
└── requirements.txt

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▶️ How to Run

Install dependencies:

pip install numpy matplotlib pandas

Run the baseline sensor processing stage:

python src/main.py

Run the firmware-style ESP32 node simulation:

python src/test_esp32_node.py

Run the MQTT-ready telemetry pipeline:

python src/test_mqtt_pipeline.py

Run the Azure-ready telemetry pipeline:

python src/test_azure_ready_pipeline.py

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📈 Output

The project generates:

• filtered signal plots
• event detection plots
• firmware-style packet flow outputs
• MQTT-ready telemetry logs
• Azure-ready telemetry logs
• packet summaries
• sample packet JSON files

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🚀 Features

• simulated sensor acquisition
• lightweight edge filtering
• local threshold-based event detection
• firmware-style node execution
• telemetry packet generation
• heartbeat packet generation
• MQTT-ready topic routing
• Azure-ready message structure
• cloud-oriented metadata and status fields

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🔧 Future Work

• connect the pipeline to a real MQTT broker
• connect the node to Azure IoT Hub
• add reconnect logic and buffering
• add configuration updates / remote parameter control
• deploy the logic on real ESP32 hardware
• support multiple sensor channels
• add anomaly detection beyond simple threshold logic

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🧠 Key Takeaway

This project demonstrates how an IoT sensor node can be designed from the edge to the cloud:

• sensing
• filtering
• event detection
• telemetry generation
• heartbeat monitoring
• MQTT-style transport
• Azure-ready telemetry schema

It provides a strong system-level example of embedded IoT architecture and cloud-ready telemetry design.

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👤 Author

Hossein Electronics Engineer