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◈ Edge AI Systems
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◈ Edge AI Systems

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Parvaz-Jamei/README.md

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◈ Engineering Identity

I build Embedded, Industrial IoT, and Edge AI systems that connect real-world devices to reliable software platforms.

My work covers the full engineering path: firmware, sensor integration, telemetry, backend services, monitoring dashboards, and AI-assisted decision support.

I focus on practical systems that are measurable, maintainable, connected, and useful beyond the prototype stage.

identity:
  role     : Embedded Software Engineer
  domains  : [Industrial IoT, Edge AI, Firmware]
  approach : End-to-end system engineering
  focus    : Real-world connected products
  stack    : C/C++ · Python · MQTT · ARM/ESP32


⚙️ Core Engineering Areas

🔧 Domain 🎯 Focus
Embedded Systems C/C++, ARM, ESP32, firmware development, device bring-up, sensor integration
Industrial IoT MQTT telemetry, RS485, LoRaWAN, gateways, device-to-cloud data flow
Edge AI Computer vision, lightweight inference, AI-assisted monitoring, smart alert validation
Backend & APIs Python services, REST APIs, automation, data pipelines
Monitoring Systems Dashboards, logging, observability, device management, system reliability
Product Engineering End-to-end IoT products from electronics and firmware to cloud services and UI

🛠️ Technology Stack




C C++ Python ESP32 ARM

MQTT LoRaWAN RS485 REST API Linux

OpenCV TensorFlow Lite Docker Git


🧩 System Layers I Work With


◬ What I Build

I work on systems where hardware, firmware, connectivity, backend logic, monitoring, and intelligence are designed as one connected product.

Typical work areas include:

  • ⚙️ Embedded firmware for sensor-based systems
  • 📡 MQTT / RS485 / LoRaWAN telemetry pipelines
  • 🐍 Python backend services and automation tools
  • 📊 Device monitoring dashboards and operational interfaces
  • 🧠 Edge AI and computer-vision-based decision support
  • 🏭 Industrial and infrastructure-focused IoT systems


◈ Selected Engineering Work

🛣️ Smart Infrastructure & Road-Weather Intelligence

One of my applied engineering directions is smart infrastructure monitoring, including road-surface sensing, environmental telemetry, data collection, false-alarm reduction, and AI-assisted warning support.

This work represents a broader engineering pattern I focus on:

Sensors → Firmware → Communication → Backend → Dashboard → AI-assisted decisions

📊 GitHub Stats

 

🏆 Trophies


🌍 Current Direction

I am focused on building reliable, field-oriented systems in:

  • ⚙️ Embedded Software Engineering
  • 📡 Industrial IoT and telemetry systems
  • 🧠 Edge AI and computer vision
  • 🐍 Python backend services and automation
  • 📊 Monitoring dashboards and device-management platforms
  • 🏭 End-to-end smart infrastructure and industrial products

🔗 Connect

LinkedIn



🌐 Portfolio: https://proio.ir   ·   📩 Email: parvaz.nic@gmail.com


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  1. PulseWetProbe-Arduino PulseWetProbe-Arduino Public

    Arduino library for MCU-only pulsed electrode wetness, soil-moisture trend, conductivity-trend sensing with calibration, filtering, diagnostics, CSV/JSON output.

    C++ 2

  2. CrashHive32 CrashHive32 Public

    ESP32 crash blackbox and field diagnostics Arduino library with RTC/NOINIT logging, ESP-NOW heartbeat monitoring, neighbor watchdog, health scoring, boot storm detection, and metric alerts.

    C++ 3

  3. EcoSensePower-Arduino EcoSensePower-Arduino Public

    Energy-aware power management and battery-life estimation library for Arduino IoT projects.Arduino ESP32 AVR SAMD IoT battery-life power management BLE GPS LoRa energy harvesting

    C++ 3

  4. FDCxCapSense FDCxCapSense Public

    Arduino library for TI FDC1004, FDC1004-Q1 and FDC2x1x/FDC2214 capacitive sensing with calibration, CAPDAC, diagnostics, liquid level and proximity profiles.

    C++ 2

  5. codontrace codontrace Public

    A small white-box Python toolkit for executable codons, deterministic agent traces, causal replay, and mutation experiments.

    Python 1