@inproceedings{396b49aab2ea4177baaf4678828517ac,
title = "Early detection of fire hazard using fuzzy inference system",
abstract = "Fast detection of fire allows to protect human{\textquoteright}s health and life as well as avoid loss of property. Most fire sensors have simple construction, consisting of one or two sensing elements (usually detecting smoke and temperature) and an uncomplicated algorithm. This paper presents an idea of using fuzzy inference for early fire detection based on simultaneous analysis of data from multiple sensors. The measurement system includes a head with two accurate sensors: electrochemical carbon monoxide sensor and resistance temperature sensor. The implemented fuzzy inference algorithm accepts as inputs the values measured by the sensors, signal rise rate and signal variability. The main goal of the system is to early detect fire hazard or sensors malfunction. A series of experiments and detailed analysis of results were performed. It has been proved that fuzzy inference is suitable to the presented application.",
keywords = "Data fusion, Fire hazard detection, Fuzzy logic, Fuzzy sensors, Measurement head, Multisensory systems",
author = "Tomasz Grychowski and Karol Jab{\l}o{\'n}ski",
note = "Publisher Copyright: {\textcopyright} 2018, Springer International Publishing AG.; 5th International Conference on Man-Machine Interactions, ICMMI 2017 ; Conference date: 03-10-2017 Through 06-10-2017",
year = "2018",
doi = "10.1007/978-3-319-67792-7\_27",
language = "English",
isbn = "9783319677910",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "271--281",
editor = "Aleksandra Gruca and Tadeusz Czachorski and Katarzyna Harezlak and Stanislaw Kozielski and Agnieszka Piotrowska and Tadeusz Czachorski",
booktitle = "Man-Machine Interactions 5 - 5th International Conference on Man-Machine Interactions, ICMMI 2017",
address = "Germany",
}