B.Sc. Projects

My philosophy for project management.

Integration projects (Sensors, IoT, and Cloud)

• Running ML/DL algorithms on low-cost, low-power and low-resource hardware, e.g. Raspberry Pi and STM32, TensorFlow Lite for Microcontrollers and Edge Impulse.
  • Open to suggestions for specific projects.
• Running IoT sensors with cloud analytics, e.g. using a physical device that sends data to AWS IoT, Azure IoT or Google IoT.
  • Open to suggestions for specific projects.
• Build a smart home appliance with connectivity for either Home Assistant, OpenHAB, or Google Home.
  • Open to suggestions for specific projects.

Research projects (Signal processing, machine learning and sensors)

The following projects are mostly recommended for students who are interested in continuing toward an M.Sc. studies (thesis track).

• Galvanic skin response (GSR) analysis (co-supervised with Dr. Nir Trabelsi from Mechanical Engineering Department).
  • An example of a GSR equipment is Shimmer3 GSR
  • GSR equipment is commonly used to measure the electrical conductance of the skin, which changes with sweat gland activity, often used in stress detection, emotional response research, and more.
• Water flow analysis in pipes, co-supervised with Dr. Lev Nelik from Civil Engineering Department.
  • Dr. Nelik is known for his expertise in pump systems and fluid mechanics
  • The goal of the project is to develop a system that can analyze water flow in pipes using sensors and machine learning algorithms.
• Droplet analysis - the follow-up project of the ML course competition, co-supervised with Dr. Merav Arogeti from Mechanical Engineering Department.
  • The goal of the project is to develop a system that can analyze droplets using acoustic microphone, underwater microphone and ultrafast camera.

You are welcome to contact me for more details.

Past projects

Only project that were published are listed here.

• D. Bykhovsky, R. Manto and M. S. Azimov, “Real-Time Face Detection and Recognition using Deep Learning and Nvidia Optimised Models,” 2024 32nd Telecommunications Forum (TELFOR), Belgrade, Serbia, 2024, pp. 1-4, link
• YOLO8/11-Based DeepStream Pipeline on Jetson Nano Platform, 2024, link
• S. H. Kobi, M. David, I. August and D. Bykhovsky, “Hyperspectral Image Prediction Using a Linear Model in Different Illumination Conditions,” 2023 13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), Athens, Greece, 2023, pp. 1-4, link
• D. Bykhovsky, N. Tochilovsky and A. Rudyak, “Python-Based Simulation of Non-Gaussian Stationary Random Process with Arbitrary Auto-Correlation Function,” 2023 International Conference on Electrical, Computer and Energy Technologies (ICECET), Cape Town, South Africa, 2023, pp. 1-6, link
• L. Kapah, N. Weizman, D. Bykhovsky and I. Y. August, “Hyper-Spectral Image Compression By Joint Spatial Spectral Dimension Reduction Using Thresholded Principal Component Analysis,” 2022 12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), Rome, Italy, 2022, pp. 1-5, link
• D. Bykhovsky, D. Cohen and D. Benafsha, “Coding performance of non-interleaved non-memoryless optical wireless channels,” 2016 IEEE International Conference on the Science of Electrical Engineering (ICSEE), Eilat, Israel, 2016, pp. 1-4, link