Nalazite se na CroRIS probnoj okolini. Ovdje evidentirani podaci neće biti pohranjeni u Informacijskom sustavu znanosti RH. Ako je ovo greška, CroRIS produkcijskoj okolini moguće je pristupi putem poveznice www.croris.hr
izvor podataka: crosbi !

FireBot - An Autonomous Surveillance Robot for Fire Prevention, Early Detection and Extinguishing (CROSBI ID 736105)

Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija

Balen, Josip ; Damjanovic, Davor ; Maric, Petar ; Vdovjak, Kresimir ; Arlovic, Matej ; Martinovic, Goran FireBot - An Autonomous Surveillance Robot for Fire Prevention, Early Detection and Extinguishing // 2023 15th International Conference on Computer and Automation Engineering (ICCAE). Institute of Electrical and Electronics Engineers (IEEE), 2023. str. 400-405 doi: 10.1109/iccae56788.2023.10111251

Podaci o odgovornosti

Balen, Josip ; Damjanovic, Davor ; Maric, Petar ; Vdovjak, Kresimir ; Arlovic, Matej ; Martinovic, Goran

engleski

FireBot - An Autonomous Surveillance Robot for Fire Prevention, Early Detection and Extinguishing

Every year, fire is responsible for numerous deaths, as well as huge material losses. Therefore, prevention and early detection of fire have become a priority for society, as well as the main research and development issue for many scientists and various industries. This paper describes our work in the development of FireBot, an autonomous surveillance robot. The Firebot is equipped with modern technologies and state-of- the-art navigational and computer vision methods that enable autonomous navigation, obstacle avoidance, video surveillance, fire prevention and detection, and fire extinguishing. It utilizes both infrared thermal (IRT) and RGB cameras paired with a modern convolutional neural network (CNN) for fault and fire detection, as well as various other sensors for analyzing air composition, processing of surrounding sounds, and detecting irregularities in its environment in general. The best performing CNN was implemented and tested in real-world environments for fire detection purposes, the results of which are presented in this paper. A state-of-the-art SLAM algorithm paired with LiDAR and a depth camera is used for mapping and navigation. The architecture presented in this paper, along with all functionalities planned for future work, represents an innovative autonomous surveillance system that will make a great contribution in the field of fire prevention and detection.

convolutional neural network , fire detection , fire prevention , infrared thermography , SLAM

nije evidentirano

nije evidentirano

nije evidentirano

nije evidentirano

nije evidentirano

nije evidentirano

Podaci o prilogu

400-405.

2023.

objavljeno

10.1109/iccae56788.2023.10111251

Podaci o matičnoj publikaciji

Institute of Electrical and Electronics Engineers (IEEE)

979-8-3503-9622-5

Podaci o skupu

2023 15th International Conference on Computer and Automation Engineering (ICCAE)

predavanje

03.03.2023-05.03.2023

Sydney, Australija

Povezanost rada

Interdisciplinarne tehničke znanosti, Računarstvo

Poveznice