The members of the SAL group offer the following topics for students to do their final degree or master's dissertation (TFG/TFM):
Software development for the alternative operating system Haiku (Supported by Dr. Nicolás Calvo Cruz)
Fall detection system using a low-cost microcontroller (Supported by Marcos Lupión Lorente)
In this work, we propose the design and deployment of a fall detection system using a low-cost device, consisting of an acceleration sensor and a gyroscope. The fall detection is performed in the same device using a machine learning algorithm. In addition, when a fall is detected, the device sends a message to the Smart Home, enabling an Alexa skill to ask the user how they are doing.
Topics: Arduino, Machine Learning, Bluetooth, Alexa
Gesture recognition in thermal images (Supported by Marcos Lupión Lorente)
This work proposes the creation of an artificial vision system that can recognise a user's gestures in thermal images. In addition, it will be integrated with an Alexa skill, which will give commands to the user to perform gestures, and the user will have to carry out these gestures. Thanks to the gesture recognition model, Alexa will know if the user is doing the gestures accordingly.
Topics: Images, Deep Learning, Alexa
Deployment of indoor location services using Bluetooth and Ultra-Wide-Band (Supported by Marcos Lupión Lorente)
In this work we propose the implementation of an indoor location system using Bluetooth devices with Direction Finding functionality, which allows locating the user in a very accurate way. Furthermore, in this work, Bluetooth will be compared with the Ultra-Wide-Band location system currently deployed in the Smart Home.
Topics: Bluetooth, Ultra-Wide-Band, MQTT, Machine Learning
If you are interested in any of them, do not hesitate to contact the referred professor!