Active theses topics for possible student theses.


  1. Home electricity monitoring with current sensors (taken by student at 31.01.2020)
    1. Use 2-3 SCT013 type of current sensors to measure power consumption
    2. Send measured power to the SQL database using for example ESP32 module with integrated WIFI
    3. Fetch power mesurements from the server database and display it using STM32 with integrated LCD
  2. Develop human presence detector using cheap termal sensor (1 student)
    1. Use Omron D6T type thermal sensor to detect human presence in the area of interest
    2. Continuous sensor calibration to set baseline for floor temperature changes
    3. Send object detection data over WIFI network to the server SQL server
    4. Optimize power consumption to maximize battery powered sensor lifetime
  3. Develop face recognition based home alarm system that sends alarm in case there is unknown person behind the door (taken by student group)
    1. Use Jetson Nano development kit and CSI-2 or IP camera that is behind the door
    2. Develop visitor management interface to manage, verify visitors and collect their visiting statistics
    3. Develop automatic alarm management functionality (where, which time and when to send alarms)
  4.  Build PCB milling printer based on the existing 3D printer (taken by studnt group)
    1. (hardware exists and is in working condition)
    2. Demonstration video: 
    3. Forum topic:
  5. Develop testing system that has 31 sensors that send messages over CAN interface to the controller
    1. System must be installed on to one compact stand 
    2. All sensors should be able to program quickly and at the same time if possible, using one binary file.
    3. It must be able to check in real-time how many CAN messages  have been lost and on which servers.


  1. Develop a model to optimize vehicle detection sensor placement and amount for ship deck (2-4 students)
    1. – Testida erineva arvu sensoritega mõju laadimiskiirusele ja auto koguste hindamisele
      – Testida sensorite erinevate asukohtadega nende mõju laadimiskiirusele ja auto koguste hindamisele
      – Arvesse tuleb võtta konkreetse teki mõõtmeid, parkimise asukohtasid ja parkimiskoha iseärasusi (ajaline)
      – Simuleerida ultrahelianduriga sensorit (tuvastab ainult sensori all teatud raadiuses sõiduki olemasolu ja selle kõrguse)
      – Simuleerida kaameraga töötavat sensorit (tuvastab teatud alas sõiduki tüübi, kiiruse ja asukoha kaamera suhtes)
    2. Outputs:
      – Erinevate sensorite koguste puhul sensorit nö vahele mahtuvate sõidukite arv ning kui palju kulub aega kuni probleem tuvastatakse, leidmaks optimaalseim sensorite arv tekil
      – Sensorite asukohtadest sõltuv nö sõiduki vahele mahtuvate sõidukite probleemide tuvastamise kiirus leidmaks optimaalset sensori asukohta tekil
      – Erinevat tüüpi sensorite kasutamisega ettetulevate probleemide tuvastamise kiirus
      – Ülalloetletud seadistuste mõju laadimiskiirusele ja milliste sõidukite koguste puhul see mõjutab laeva reaalset mahutavust
  2. Use machine learning model to classify different types of signals
    1. TBD