Abstract: GPS satellite (4) ranging signals (6) received (32) on comm1, and DGPS auxiliary range correction signals and pseudolite carrier phase ambiguity resolution signals (8) from a fixed known earth base station (10) received (34) on comm2, at one of a plurality of vehicles/aircraft/automobiles (2) are computer processed (36) to continuously determine the one's kinematic tracking position on a pathway (14) with centimeter accuracy. That GPS-based position is communicated with selected other status information to each other one of the plurality of vehicles (2), to the one station (10), and/or to one of a plurality of control centers (16), and the one vehicle receives therefrom each of the others' status information and kinematic tracking position. Objects (22) are detected from all directions (300) by multiple supplemental mechanisms, e.g., video (54), radar/lidar (56), laser and optical scanners. Data and information are computer processed and analyzed (50,52,200,452) in neural networks (132, FIGS.

Abstract: Systems and methods are disclosed that optimize the combustion process in various reactors, furnaces, and internal combustion engines. Video cameras are used to evaluate the combustion flame grade. Depending on the desired form, standard or special video devices, or beam scanning devices, are used to image the combustion flame and by-products. The video device generates and outputs image signals during various phases of, and at various locations in, the combustion process. Other forms of sensors monitor and generate data signals defining selected parameters of the combustion process, such as air flow, fuel flow, turbulence, exhaust and inlet valve openings, etc. In a preferred form, a neural networks initially processes the image data and characterizes the combustion flame. A fuzzy logic controller and associated fuzzy logic rule base analyzes the image data from the neural network, along with other sensor information.

Abstract: A friend or foe detection system and method is disclosed. Friend or foe warning unit 20 has a geographic locating system, a communication system for communicating with each of the warning units, and a military force detection system for detecting military forces in a combat area and has a signal routing and control circuitry 50 for controlling operations. A number of components, devices, or sub-systems, such as a transmitter/receiver radio 28, an antenna 26, a microphone 30, a speaker 32, a battery 34, a display 36, a microprocessor 38, a memory 40, a camera 56, a radar/lidar input 54, on/off switch 52, a GPS location system 45 that includes a GPS processor 46, a GPS receiver 42, a GPS antenna 44, are coupled to the circuitry 50. Display 36 provides a display to the user of the unit 20 and shows the location of friendly forces as well as unfriendly or unidentified forces in the area. Display 36 displays text messages for the user of the warning unit 20.

Abstract: The present invention discloses a general overall system 30 and a general overall method 10 for tracking, monitoring, and learning prisoner or parolee behavior. The system 30 and method 10 involve obtaining prisoner or parolee data and monitoring data for at least one individual prisoner or parolee 38, storing the prisoner or parolee data and monitoring data into a database, learning prisoner or parolee behavior from the prisoner or parolee data and the monitoring data in the database, and updating the prisoner or parolee data and the monitoring data in the database. The present invention involves learning both individual and aggregate prisoner or parolee behavior from the prisoner or parolee data and the monitoring data in the database. The present invention executes expert system (i.e. including but not limited to fuzzy logic, reinforcement learning, neural networks, artificial intelligence, etc.) algorithms for determining and analyzing deviated behavior by the prisoner or parolee 38.

Abstract: The present invention discloses a general overall system 30 and a general overall method 10 for tracking, monitoring, and learning prisoner or parolee behavior. The system 30 and method 10 involve obtaining prisoner or parolee data and monitoring data for at least one individual prisoner or parolee 38, storing the prisoner or parolee data and monitoring data into a database, learning prisoner or parolee behavior from the prisoner or parolee data and the monitoring data in the database, and updating the prisoner or parolee data and the monitoring data in the database. The present invention involves learning both individual and aggregate prisoner or parolee behavior from the prisoner or parolee data and the monitoring data in the database. The present invention executes expert system (i.e. including but not limited to fuzzy logic, reinforcement learning, neural networks, artificial intelligence, etc.) algorithms for determining and analyzing deviated behavior by the prisoner or parolee 38.

Abstract: A method for detecting fires and reacting thereto. A stationary, earth orbit satellite, drone aircrafts or piloted aircraft contains infrared detectors and optical means for detecting fires. A computer in the satellite, drone or piloted aircraft and/or on the ground analyzes image signals of the areas being monitored and, upon detecting infrared radiation of varying intensity and shape, indicative that a fire has started, generates signals which are indicative of the coordinate locations of the fire, the extent of the fire, the shape of the area(s) burning, the direction of movement of the fires, the speed(s) of the flame fronts, smoke condition, intensity of the fire, fire ball location(s), etc. In one form, a camera generates image signals which are digitized and recorded. Expert system logic is used to prioritize dangerous areas to assist in directing fire fighting.

Abstract: GPS satellite (4) ranging signals (6) received (32) on comm1, and DGPS auxiliary range correction signals and pseudolite carrier phase ambiguity resolution signals (8) from a fixed known earth base station (10) received (34) on comm2, at one of a plurality of vehicles/aircraft/automobiles (2) are computer processed (36) to continuously determine the one's kinematic tracking position on a pathway (14) with centimeter accuracy. That GPS-based position is communicated with selected other status information to each other one of the plurality of vehicles (2), to the one station (10), and/or to one of a plurality of control centers (16), and the one vehicle receives therefrom each of the others' status information and kinematic tracking position. Objects (22) are detected from all directions (300) by multiple supplemental mechanisms, e.g., video (54), radar/lidar (56), laser and optical scanners. Data and information are computer processed and analyzed (50, 52, 200, 452) in neural networks (132, FIGS.

Abstract: A system and method for controlling traffic and traffic lights and selectively distributing warning messages to motorists includes a controller to determine appropriate action based on traffic congestion parameters. Fuzzy logic is used to determine optimum traffic light phase split based on the traffic information from the traffic information units. Global Positioning System technology is used by the system and method in order to track moving vehicles and signs and be able to communicate with them.

Abstract: A fuzzy logic based emergency flight control system for an aircraft. The system has a thrust vectoring flight control system, an aerodynamic flight control system, and a fuzzy logic controller. The thrust vectoring flight control system provides thrust to the aircraft in an emergency situation alone or in combination with aerodynamic flight controls. The fuzzy logic controller executes fuzzy logic algorithms for assessing the emergency situation and controlling the aircraft thrust vectoring and aerodynamic flight control systems in the emergency situation. An adjustable nozzle is coupled to an exhaust thrust end of an engine of the aircraft and is angularly adjusted to direct thrust of the aircraft in a determined direction after fuzzy logic controller assessment of the emergency situation.

Abstract: A system and method for controlling traffic and traffic lights and selectively distributing warning messages to motorists is described. Traffic information is obtained from various traffic information units. The traffic information units have intelligent controllers. The traffic information is transmitted to at least one central controller. The central controller is used to determine congestion parameters and warning information. The congestion parameters and the warning information are transmitted from the central controller to the intelligent controllers. The intelligent controllers are used to determine appropriate action based on the congestion parameters and the warning information. Fuzzy logic is used to determine optimum traffic light phase split based on the traffic information from the traffic information units. The optimum traffic light phase split is determined for each of the intelligent controllers.

Abstract: A system for automatically detecting fires in select areas, and reacting thereto to put out the fires. A stationary, earth orbit satellite, pilotless drone aircrafts or piloted aircraft contains one or more infrared detectors and optical means for detecting small fires when they first occur in fields and wooded areas, preferably where man made campfires and trash dumping are prohibited. A computer in the satellite, drone or piloted aircraft and/or on the ground receives and analyzes image signals of the earth area or areas being monitored and, upon detecting infrared radiation of varying intensity and variable shape, indicative that a fire has started, generates coded signals which are (a) indicative of the coordinate locations of the fire, (b) the extent of the fire, (c) the shape of the area(s) burning, (d) the direction of movement of the fires (e) the speed(s) of the flame fronts, (f) smoke condition, (g) intensity of the fire, (h) fire ball location(s), etc.

Abstract: Systems and methods are disclosed that optimize the combustion process in various reactors, furnaces, and internal combustion engines. Video cameras are used to evaluate the combustion flame grade. Depending on the desired form, standard or special video devices, or beam scanning devices, are used to image the combustion flame and by-products. The video device generates and outputs image signals during various phases of, and at various locations in, the combustion process. Other forms of sensors monitor and generate data signals defining selected parameters of the combustion process, such as air flow, fuel flow, turbulence, exhaust and inlet valve openings, etc. In a preferred form, a neural networks initially processes the image data and characterizes the combustion flame. A fuzzy logic controller and associated fuzzy logic rule base analyzes the image data from the neural network, along with other sensor information.

Abstract: GPS satellite (4) ranging signals (6) received (32) on comm1, and DGPS auxiliary range correction signals and pseudolite carrier phase ambiguity resolution signals (8) from a fixed known earth base station (10) received (34) on comm2, at one of a plurality of vehicles/aircraft/automobiles (2) are computer processed (36) to continuously determine the one's kinematic tracking position on a pathway (14) with centimeter accuracy. That GPS-based position is communicated with selected other status information to each other one of the plurality of vehicles (2), to the one station (10), and/or to one of a plurality of control centers (16), and the one vehicle receives therefrom each of the others' status information and kinematic tracking position. Objects (22) are detected from all directions (300) by multiple supplemental mechanisms, e.g., video (54), radar/lidar (56), laser and optical scanners. Data and information are computer processed and analyzed (50,52,200,452) in neural networks (132, FIGS.

Abstract: A fuzzy logic based emergency flight control system for an aircraft. The system has a thrust vectoring flight control system, an aerodynamic flight control system, and a fuzzy logic controller. The thrust vectoring flight control system provides thrust to the aircraft in an emergency situation alone or in combination with aerodynamic flight controls. The fuzzy logic controller executes fuzzy logic algorithms for assessing the emergency situation and controlling the aircraft thrust vectoring and aerodynamic flight control systems in the emergency situation. An adjustable nozzle is coupled to an exhaust thrust end of an engine of the aircraft and is angularly adjusted to direct thrust of the aircraft in a determined direction after fuzzy logic controller assessment of the emergency situation.

Abstract: A friend or foe detection system and method is disclosed. Friend or foe warning unit 20 has a geographic locating system, a communication system for communicating with each of the warning units, and a military force detection system for detecting military forces in a combat area and has a signal routing and control circuitry 50 for controlling operations. A number of components, devices, or sub-systems, such as a transmitter/receiver radio 28, an antenna 26, a microphone 30, a speaker 32, a battery 34, a display 36, a microprocessor 38, a memory 40, a camera 56, a radar/lidar input 54, on/off switch 52, a GPS location system 45 that includes a GPS processor 46, a GPS receiver 42, a GPS antenna 44, are coupled to the circuitry 50. Display 36 provides a display to the user of the unit 20 and shows the location of friendly forces as well as unfriendly or unidentified forces in the area. Display 36 displays text messages for the user of the warning unit 20.

Abstract: Systems and methods are disclosed that optimize the combustion process in various reactors, furnaces, and internal combustion engines. Video cameras are used to evaluate the combustion flame grade. Depending on the desired form, standard or special video devices, or beam scanning devices, are used to image the combustion flame and by-products. The video device generates and outputs image signals during various phases of, and at various locations in, the combustion process. Other forms of sensors monitor and generate data signals defining selected parameters of the combustion process, such as air flow, fuel flow, turbulence, exhaust and inlet valve openings, etc. In a preferred form, a neural networks initially processes the image data and characterizes the combustion flame. A fuzzy logic controller and associated fuzzy logic rule base analyzes the image data from the neural network, along with other sensor information.

Abstract: A friend or foe detection system and method is disclosed. Friend or foe warning unit 20 has a geographic locating system, a communication system for communicating with each of the warning units, and a military force detection system for detecting military forces in a combat area and has a signal routing and control circuitry 50 for controlling operations. A number of components, devices, or sub-systems, such as a transmitter/receiver radio 28, an antenna 26, a microphone 30, a speaker 32, a battery 34, a display 36, a microprocessor 38, a memory 40, a camera 56, a radarilidar input 54, on/off switch 52, a GPS location system 45 that includes a GPS processor 46, a GPS receiver 42, a GPS antenna 44, are coupled to the circuitry 50. Display 36 provides a display to the user of the unit 20 and shows the location of friendly forces as well as unfriendly or unidentified forces in the area. Display 36 displays text messages for the user of the warning unit 20.

Abstract: A friend or foe detection system and method is disclosed. Friend or foe warning unit 20 has a geographic locating system, a communication system for communicating with each of the warning units, and a military force detection system for detecting military forces in a combat area and has a signal routing and control circuitry 50 for controlling operations. A number of components, devices, or sub-systems, such as a transmitter/receiver radio 28, an antenna 26, a microphone 30, a speaker 32, a battery 34, a display 36, a microprocessor 38, a memory 40, a camera 56, a radar/lidar input 54, on/off switch 52, a GPS location system 45 that includes a GPS processor 46, a GPS receiver 42, a GPS antenna 44, are coupled to the circuitry 50. Display 36 provides a display to the user of the unit 20 and shows the location of friendly forces as well as unfriendly or unidentified forces in the area. Display 36 displays text messages for the user of the warning unit 20.

Abstract: Surveillance platforms in airborne craft (8,10), land based vehicles (12), vessels at sea or fixed structures (14) detect dangers using conventional scanners and transmit information signals describing the dangers to a control center (2) which analyzes the data and determines the degree of danger and its geographic extent. The center generates a danger warning and emergency response including a danger index. The warning/response message identifies the degree of danger (danger index 144) and the GPS coordinates (142) of the impacted geographic area for a wide region or regions of the earth (FIGS. 2-6). A vulnerability index (FIG. 16) determined using neural networks (FIGS. 13-14) and fuzzy logic (FIGS. 15-20) enables a prioritized warning/response. The center broadcasts (18) the danger warning and emergency response (FIG. 9) to a large population of remotely located warning devices (11), such as a network of pagers each of which has a GPS receiver (6,28).

Abstract: A system and method for tracking, monitoring and learning prisoner or parolee behavior involves obtaining prisoner or parolee data and monitoring data for at least one individual prisoner or parolee, storing the prisoner or parolee data and monitored data into a database, learning prisoner or parolee behavior from the prisoner or parolee data and the monitored data in the database, and updating the prisoner or parolee data and the monitored data in the database. Expert system (i.e. including but not limited to fuzzy logic, reinforcement learning, neural networks, artificial intelligence, etc.) algorithms are executed for determining and analyzing deviated behavior by the prisoner or parolee. A parole level is assigned to the prisoner or parolee and it is determined whether the prisoner or parolee is to be moved up or down a parole level depending on whether the prisoner or parolee behavior does not constitute or does constitute prisoner or parolee violations.