Thesis Description & Objectives
This thesis will concentrate on defining, analyzing, and validating
figures of merit for advanced sensor fusion architectures within smart
environments. The student will review performance and reliability
metrics combining contactless spatial data (millimeter-wave radar
sensors) with biometric and motion streams from low-power wearable
devices (BLE/Zigbee). The work will propose a coherent framework of
metrics tailored to real-time edge computing workflows, optimizing
event detection while minimizing false alarm rates. Several composite
objectives will be designed, for instance balancing system latency, data
consistency, and user privacy constraints. Using simplified sensor
simulators, data fusion models, or hardware testbeds, the thesis will
explore trade-offs between different filtering policies and how edge
computing architectures influence detection accuracy. The expected
contribution is a clear metric and algorithmic framework to evaluate
multi-sensor fusion strategies in home automation.
Notes: The thesis will be carried out in a hybrid mode (Smart Working
for software and code development) with periodic in-person testing
sessions and laboratory activities at the Alessandria campus.
Contact Patrik Resta resta.patrik83@gmail.com
