| KEYWORD |
Indoor human localization and identification using low-power low-cost environmental and wearable sensors
keywords CAPACITIVE SENSORS, ENVIRONMENTAL SENSORS, IDENTIFICATION, INDOOR LOCALIZATION, RADAR, SLAM, WEARABLE AND IOT DEVICES, WEARABLE DEVICES
Reference persons LUCIANO LAVAGNO, MIHAI TEODOR LAZARESCU
Research Groups Microelectronics, Sensing and processing
Thesis type RESEARCH
Description The project, which currently involves several PhD and MS students, is aimed at finding the location of person and identifying the person among a small set, using a synergy between new capacitance-based sensors and traditional ones (e.g. infrared).
Previous research by our group has developed pilot nodes, based on an RC oscillator, that measure capacitance via frequency, transmit it to a PC, and use the data to locate the person with an error of about 30cm in a 3mx3m room.
Possible thesis topics, spanning analogue and digital electronics, embedded systems and machine learning:
- capacitance measuring techniques highly resilient to noise (e.g., filtering, balanced sensor structures, shielding of measurement field).
- analogue and digital front-end circuitry, aimed at measuring very small capacitance in the presence of noise from the environment.
- sensor power management, especially controlling sleep time of various components (analogue, digital, radio).
- low-power implementation on node of some processing functions (filters, some machine learning algorithms).
- machine learning algorithms on the base station, to fuse data from different capacitive and other kinds of sensors.
Deadline 17/11/2025
PROPONI LA TUA CANDIDATURA