Tipo di tesi
Tesi di laurea magistrale
Titolo
Analysis and Design of a DNN for Smoke/Fire Video Feature Extraction and its Integration in Low-cost and Low-power Embedded Systems
Dipartimento
INGEGNERIA DELL'INFORMAZIONE
Corso di studi
INGEGNERIA ROBOTICA E DELL'AUTOMAZIONE
Riassunto (Italiano)
Design and analysis of a DNN architecture for smart fire and smoke detection in indoor/outdoor environment. The algorithm uses a two-subnetwork architecture joined with an alarm-triggering code, it was trained on custom dataset and tested versus most recent state of the art solutions and traditional AI-based methods through the computation of performance indices such as Accuracy, Precison, Recal and F1-score. The algorithm deployment on low-end embedded systmes, like Raspberry Pi 3 and Nvidia Jetson Nano, is then discussed in detail confronting the resulting performance against both deep-Learning-based and non-DL-based solutions from the State of the Art and traditionally employed techniques such as fine-tuned VGG DNN. Results show that the proposed solution outperform benchmarks in term of performance indices while achieving computational cost comparable to non-DL-based solutions.
