Fire alarm systems construction on artificial intelligence principles

Abstract

Coverage of modern views on security trends and directions for developing security systems in the context of global automation and integration into unified automated control systems. An overview of the prospects for using artificial intelligence in security systems to identify difficult to classify situations using signs obtained from monitoring data. Assessment of the prospects for the use of fire alarm systems based on the principles of artificial intelligence based on neural networks (building on the principles of combinatorics of methods of neural networks and odd logic systems). Construction of a mathematical model that describes the process of generating a reliable formation of a signal about the transition of the system to the "fire" state and a description of the problem of correctly setting the system response threshold for signal generation, solving the problem of minimizing the number of false positives by introducing an additional channel that receives initial information about the state of the object in the optical range. Investigation of the reliability of the characteristics of gas fire detectors declared by the manufacturer to determine the possibility of using them as initial elements of fire alarm systems built on the principles of neural networks.

Analysis of optimization of labor protection measures aimed at improving workplace conditions

“…When the system is operating in control mode, it is supplemented with identification blocks (5), optimization (6-8) and forecasting (9)(10)(11). The parameters of working conditions and morbidity indicators after their statistical processing and grouping, which allows for comparative analysis, serve as the initial basis for the identification model.…”

“…Information on the state of the control object contains data on compliance with the rules and norms of labor protection, on the implementation of planned activities, current values of working conditions factors, indicators of the health status of workers and economic data [11].…”

Analysis of the optimization of labor protection measures in engineering work

“…When the system is operating in the control mode, it is supplemented with blocks of identification and prediction optimization [9][10][11]. The parameters of working conditions and morbidity indicators after their statistical processing and grouping, which allows for comparative analysis, serve as the initial basis for the identification model.…”

“…Assuming that after carrying out a set of optimal measures, the minimum possible levels of morbidity will be reached after some time, we take this time for the forecasting period [11]. Having estimated by expert means the values that the parameters of working conditions will have over time (without carrying out optimal measures), using the identification model [1] we will determine the real forecast of morbidity indicators [14]:…”

“…Summing up this decrease in all the forms of diseases identified for the object under study, we obtain a general decrease in morbidity as a result of optimizing preventive measures. The social effect of health-improving measures should be determined by the number of workers removed from the influence of harmful and harsh working conditions, which directly affects the reduction of morbidity rates [11]. Thus, the calculated decrease in the number of sick people, the number of cases of diseases can be considered the equivalent of one of the types of social effect obtained by optimization [19].…”