Utc Fire and Security Corporation

United Technologies Corporation

Chubb Protection Corporation

Robert N Tomastik

Alan Matthew Finn

Sergei F Burlatsky

Ziyou Xiong

Pengju Kang

Ravi Rajamani

Pei-Yuan Peng

Vadim V Atrazhev

Satish Narayanan

Andrzej Banaszuk

Lin Lin

Jihua Wang

Sergey Shishkin

Thomas M Gillis

Thomas Gannon

Robert E LaBarre

Nathan S Hariharan

Philippe Detriche

Oleg A Vasilyev

Nikolay S Erikhman

A model-based egress support system () employs models to generate an optimal egress route for occupants in a region. The system includes an egress controller () that is connected to receive detection data. The egress controller () executes an optimization algorithm () to select an egress route based on model-based egress estimates generated by an egress prediction model () in response to the detection data.

Model-based egress support system

A system generates occupancy estimates based on a Kinetic-Motion (KM)-based model that predicts the movements of occupants through a region divided into a plurality of segments. The system includes a controller for executing an algorithm representing the KM-based model. The KM-based model includes state equations that define each of the plurality of segments as containing congested portions and uncongested portions. The state equations define the movement of occupants based, in part, on the distinctions made between congested and uncongested portions of each segment.

System and method for occupancy estimation

An alarm filter () for use in a security system () to reduce the occurrence of nuisance alarms receives sensor signals (S-S, S) from a plurality of sensors () included in the security system (). The alarm filter () produces an opinion output as a function of the sensor signals and selectively modifies the sensor signals as a function of the opinion output to produce verified sensor signals (S'-S&#x2032;).

Nuisance alarm filter

A method for conducting a repairable inventory analysis calculates the minimum number of repairable parts to be held in inventory while still being able to satisfy the demand for spare parts even in view of uncertain repair lead times. The method uses a set of equations that relates a customer service level to arbitrary probability distribution functions of a repair lead-time and a part arrival process. The distributions are then searched to locate the optimal inventory level in the distribution.

Rotable inventory calculation method

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Rocky Hill, CT, United States of America

Robert N Tomastik