Modeling uncertainty in estimating the information quality acquired from the fire alarm systems

The article discusses issues associated with modelling the uncertainty of estimating the quality of information acquired during the monitoring and alarming process within fire alarm systems (FAS) operated in buildings. The FAS in question guarantees fire safety for a selected building and the accumulated animate (humans, animals, etc.) and inanimate (collected property) matter, as well as oversees the surrounding natural environment through monitoring and protection, e.g., fuel, grease, and chemical compound storage. Therefore, a FAS must exhibit a reliable structure of the operating process, as well as alarm and fault signal transmission (AFST) to remote monitoring centers (fire alarm receiving center and fault signal receiving station). The further section of the paper includes a critical source literature review, which led to the conclusion that FAS functionality assessment requires determining information quality (IQ) and monitoring the IQ level that will enable estimating the FAS state. Because the information quality is determined, in addition to system reliability, many other aspects that contribute to information quality are also considered. IQ determination is presented based on an example of a representative FAS that monitors a given building. The selected FAS was subjected to a review of fire detection methods, and a statistical study of the errors occurring within AFST was conducted on this basis. Uncertainty modelling was employed to determine IQ. It enables the estimation of information quality for both dependent and independent elements. The next section of the article presents an estimation of the IQ process in an FAS employing uncertainty modelling based on fuzzy rough sets and a hypothesis certainty factor. Created an uncertainty hybrid method for IQ calculation. Ultimately, an information quality model was developed, and an example of IQ calculation was presented. The authors also conducted a computer simulation that enables the development of conclusions. The methods presented can be applied to the design, ongoing maintenance operation, and improvement of an FAS