Institute of Computer Science, University of Tartu
Note: Your valuable work can contributed to one of these projects.Reach us at huber DOT flores AT UT DOT ee
Edge intelligence: The goal of this project is to explore different strategies to achieve federated learning on smartphones and smart devices.
Food quality estimation: The goal of this project is to develop innovate techniques with green light sensing and thermal imaging to estimate the quality of different produce, e.g., fruits and vegetables.
Waste management with thermal imaging: The idea is to exploit the human-emitted thermal radiation to classify object materials before its actual disposal in the trash bins. This projects builds on the fact that people need to touch objects when they are throwing them away and that these interactions result in thermal footprints on the object's surface. By examining the dissipation of these thermal footprints, it is possible to identify the material of the waste.
Transform old smartphones into micro-clouds: The idea is to extract the CPU from old smartphones to create a portable rack of processing power. This computing infrastructure can be used to create portable micro-clouds that can be carry by different means.
Underwater communications: This project consists in running a benchmark to compare the transfer data rate of acoustic and light communications for enable the Internet of Underwater Things.
User studies: This project involves conducting user studies to test the perception of multiple users towards mobile and pervasive applications. For instance, the perception of people about sharing sensor data in public and with strangers, the perception of people about drones in public spaces, etc.
Unmanned autonomous vehicles (drones): This project focuses on creating drone systems that collect data in the wild with sensors. For instance, a ground drone that collects information about road conditions, such that it can warn drivers around about dangers. Another example is an aerial drone that is designed to spot littering areas in a city.
Defended theses have contributed to these projects:
[Master] Mayowa Olapade, Autonomous Monitoring of Litter using Sunlight. [Contributed to a publication in IEEE Pervasive Computing 2022]
[Master] Hilary Emenike, Exploiting Human-emitted Thermal Radiations. [Contributed to a publication in IEEE PerCom 2021]