DECISION-THEORETIC CONTROL OF CENTRALIZED FIRE-ALARM SYSTEMS

RESEARCH IN FIRE-DETECTION METHODS CONTINUES TO MAKE INCREMENTAL PROGRESS IN INCREASING THE SENSITIVITY AND SPECIFICITY WITH WHICH SMOKE, FLAMES, AND OTHER COMBUSTION PRODUCTS ARE MEASURES. THERE EXISTS A DISTINCT POSSIBILITY FOR A SIGNIFICANT REDUCTION IN FALSE ALARM RATES THROUGH THE PRINCIPLED INTEGRATION OF SENSOR DATA FROM VARIOUS DETECTORS, INFORMATION ON THE CONFIGURATION OF ALARMS, AND A RICH SET OF CHARACTERISTICS OF BUILDING OCCUPANTS AND EQUIPMENT. RECENTLY, THERE HAVE BEEN SIGNIFICANT ADVANCEMENTS IN THE AREA OF PROBABILISTIC DIAGNOSTIC SYSTEMS. THESE ADVANCES HAVE LED TO THE DEVELOPMENT OF TOOLS FOR AUTOMATED DECISION-MAKING THAT EXHIBIT UNPRECEDENTED ACCURACY AND FLEXIBILITY. WE PROPOSE TO APPLY THESE METHODS TO REDUCTION OF FIRE-ALARM RATES IN LARGE BUILDINGS. WE WILL BUILD A PROBABILISTIC MODEL FOR THE ALARMING PROCESS IN MULTIPLE-FAMILY RESIDENTIAL STRUCTURES, INCORPORATING AN EXPLICIT MODEL OF THE COSTS AND BENEFITS OF ALARMING IN VARIOUS SCENARIOS. WE WILL INCORPORATE THIS MODEL INTO A PROTOTYPE RUNTIME SYSTEM FOR FIRE-ALARM DECISION MAKING. IN ADDITION, WE WILL INVESTIGATE PRINCIPLED METHODS FOR DEVELOPING A SYSTEM THAT RECOMMENDS OPTIMUM LEVELS OF SUPPRESSION RESPONSE FOR FIRES IN LARGE BUILDINGS.