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amirhossein-sadeghi2003/README.md

Intelligent Physical Systems animated banner

Amirhossein Sadeghi

Embedded Sensing · State Estimation · Planning · Control for Intelligent Physical Systems

Computer Engineering student building hands-on projects where software interacts with physical systems through sensors, models, estimation, planning, control, and applied machine learning.

About

I am a Computer Engineering student at Isfahan University of Technology, developing a project portfolio around intelligent physical systems.

My work focuses on systems that combine:

  • sensing and embedded software
  • dynamic-system modeling
  • state estimation and filtering
  • planning and search algorithms
  • feedback control and optimization
  • applied machine learning for monitoring, diagnosis, and inspection
  • secure IoT and cyber-physical anomaly detection

My long-term direction is close to robotics, autonomous systems, and cyber-physical systems: software that helps machines sense, estimate, decide, and act in the physical world.

Portfolio Direction

The main theme of my portfolio is:

Sensing → Estimation → Planning → Control → Embedded Intelligence → Secure Monitoring

I try to build projects that include more than source code: simulations, hardware tests, sensor data, plots, animations, model evaluation, engineering limitations, and reproducible results.

Featured Projects

Project Area What it demonstrates
IoT Digital Twin ML Pipeline IoT, embedded sensing, ML ESP32 sensor telemetry, Node-RED dashboard, MQTT pipeline, ML-based monitoring, digital-twin style system integration
Secure IoT Sensor Anomaly Detection IoT security, anomaly detection Real IoT telemetry data, simulated spoofing attacks, rule-based detection, ML detection, temporal features, metrics, visual results
Ball and Beam Hardware Control Embedded control ESP32, HC-SR04 distance sensing, MG946R servo actuation, open-loop tests, P-control Prototype V1, hardware debugging, demo video
Embedded IMU Attitude Estimation Embedded estimation ESP32 + MPU6050 roll/pitch estimation, complementary filter, OLED display, LED feedback, attitude animation
Sensor Fusion State Estimation State estimation 2D trajectory estimation with noisy GPS-like measurements, IMU-like acceleration, dropout handling, tracking animation
TinyML Embedded Condition Monitor Embedded AI ESP32-based monitoring, real sensor data, TinyML-style inference, OLED/NeoPixel/buzzer feedback, live monitor dashboard

Supporting Projects

Dynamics, Control, and Estimation Foundations

Applied Machine Learning for Physical Systems

IoT and System Integration

Security for IoT and Cyber-Physical Systems

Additional CS / ML Coursework

Project Map

Sensing and Embedded Estimation
├── Embedded IMU Attitude Estimation
├── TinyML Embedded Condition Monitor
└── IoT Digital Twin ML Pipeline

Planning and Decision-Making
└── Robot Path Planning Visualizer

Dynamics, Control, and Optimization
├── Ball and Beam Hardware Control
├── Evolutionary Control Tuning
├── DC Motor Simulation
└── Mass-Spring-Damper Simulation

State Estimation and Filtering
├── Sensor Fusion State Estimation
└── Kalman Filter DC Motor

Applied ML for Physical Systems
├── Time-Series Motor Fault Detection
├── Industrial Surface Defect Classification
└── Dynamic System Classification

Security for IoT and Cyber-Physical Systems
└── Secure IoT Sensor Anomaly Detection

Technical Areas

  • Python, C/C++, Arduino, ESP32
  • NumPy, pandas, matplotlib
  • scikit-learn, PyTorch
  • embedded sensing and hardware bring-up
  • Kalman filtering and sensor fusion
  • dynamic-system simulation and response analysis
  • path planning and search algorithms
  • feedback control and optimization
  • signal processing and feature extraction
  • IoT communication and MQTT
  • IoT security and anomaly detection
  • computer vision for visual inspection

Current Focus

I am currently strengthening my portfolio toward graduate studies in:

  • robotics and autonomous systems
  • control systems
  • cyber-physical systems
  • embedded intelligence
  • sensing and state estimation
  • applied machine learning for physical systems
  • secure IoT and cyber-physical systems

Engineering software for systems that sense, estimate, plan, and act.

Pinned Loading

  1. tinyml-flight-condition-monitor tinyml-flight-condition-monitor Public

    ESP32-based TinyML condition monitoring prototype using real sensor data, embedded inference, OLED, NeoPixel, and buzzer feedback.

    Python 1

  2. ball-and-beam-hardware-control ball-and-beam-hardware-control Public

    C++

  3. embedded-imu-attitude-estimation embedded-imu-attitude-estimation Public

    ESP32 and MPU6050 attitude estimation project with raw IMU sensing, roll/pitch estimation, and filtering for intelligent physical systems.

    C++

  4. IoT-DigitalTwin-ML-Pipeline IoT-DigitalTwin-ML-Pipeline Public

    IoT digital twin pipeline using ESP32 sensing, MQTT communication, ML inference, and a Node-RED dashboard.

    Python

  5. secure-iot-sensor-anomaly-detection secure-iot-sensor-anomaly-detection Public

    Python

  6. sensor-fusion-state-estimation sensor-fusion-state-estimation Public

    Aerospace- and robotics-inspired sensor fusion project for 2D state estimation using simulated GPS/IMU data and Kalman filtering.

    Python