Junior Embedded System Engineer | Machine Learning Enthusiast

I am a passionate Junior Embedded System Engineer with a strong interest in Machine Learning and Deep Learning. My work often involves experimenting with the fusion of embedded systems and machine learning to create intelligent systems that can make a real-world impact.

• Embedded Systems Development: Designing, developing, and optimizing embedded systems for various applications.
• Machine Learning: Building and training models for predictive analytics, classification, and anomaly detection.
• Deep Learning: Exploring neural networks and their applications in image processing, natural language processing, and more.
• Integration: Combining the power of embedded systems with machine learning algorithms to create smart, autonomous solutions.

Here are a few highlights of my projects where I combined embedded systems with machine learning:

• Fire Monitoring System Using Quadcopter and Raspberry Pi: developing a quadcopter and equipping it with a Raspberry Pi and FLIR Lepton IR camera. This setup was created to detect and locate potential fires. To classify scenes where fire potentially occurred, I used a support vector classifier. The vehicle coordinates were then sent to the ground control station.
• Anomaly Detection in Power Meters: Created a system to detect anomalies in power meter readings using LSTM autoencoders, with real-time data processing and MQTT integration.

• Embedded Systems: C, C++, Microcontrollers (Arduino, STM32), RTOS
• Machine Learning: Python, TensorFlow, Keras, scikit-learn
• Deep Learning: Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks
• Integration: MQTT, IoT, Sensor Networks, Data Processing

• LinkedIn: Rumy's LinkedIn
• Email: [email protected]

Feel free to explore my repositories to see some of the cool projects I've worked on. I am always open to collaboration and discussions on innovative ideas!

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