Abstract: A remote monitoring system and a method of operating a system having a pump is provided. The remote monitoring system includes a vacuum/pressure sensor coupled to measure a vacuum or a pressure in the system. A temperature sensor is positioned to measure an ambient temperature. A fluid level sensor is positioned to measure fluid in a collection tank. A controller is operably coupled to the vacuum/pressure sensor, the temperature sensor and the fluid level sensor, the controller having a communications circuit that is operable to transmit and receive signals via a cellular SMS text message communications medium, the controller having one or more processors that are responsive to nontransitory executable computer instructions, the one or more processors being responsive to change the operation of the pump in response to an operating signal from the communications circuit, the temperature sensor or the vacuum/pressure sensor or the fluid level sensor.

Abstract: A remote monitoring system and a method of operating a system having a pump is provided. The remote monitoring system includes a vacuum/pressure sensor coupled to measure a vacuum or a pressure in the system. A temperature sensor is positioned to measure an ambient temperature. A fluid level sensor is positioned to measure fluid in a collection tank. A controller is operably coupled to the vacuum/pressure sensor, the temperature sensor and the fluid level sensor, the controller having a communications circuit that is operable to transmit and receive signals via a cellular SMS text message communications medium, the controller having one or more processors that are responsive to nontransitory executable computer instructions, the one or more processors being responsive to change the operation of the pump in response to an operating signal from the communications circuit, the temperature sensor or the vacuum/pressure sensor or the fluid level sensor.

Abstract: A traffic sensor system for detecting and tracking vehicles is describede. A video camera is employed to obtain a video image of a section of a roadway. Motion is detected through changes in luminance and edges in frames of the video image. Predetermined sets of pixels (“tiles”) in the frames are designated to be in either an “active” state or an “inactive” state. A tile becomes active when the luminance or edge values of the pixels of the tile differ from the respective luminance or edge values of a corresponding tile in a reference frame in accordance with predetermined criteria. The tile becomes inactive when the luminance or edge values of the pixels of the tile do not differ from the corresponding reference frame tile in accordance with the is predetermined criteria. Shape and motion of groups of active tiles (“quanta”) are analyzed with software and a neural network to detect and track vehicles.

Abstract: A recognition system is disclosed, including a representation of an object in terms of its constituent parts that is translationally invariant, and which provides scale invariant recognition. The system further provides effective recognition of patterns that are partially present in the input signal, or that are partially occluded, and also provides an effective representation for sequences within the input signal. The system utilizes dynamically determined, context based expectations, for identifying individual features/parts of an object to be recognized. The system is computationally efficient, and capable of highly parallel implementation, and further includes a mechanism for improving the preprocessing of individual sections of an input pattern, either by applying one or more preprocessors selected from a set of several preprocessors, or by changing the parameters within a single preprocessor.

Abstract: A traffic sensor system for detecting and tracking vehicles is described. The disclosed system may be employed as a traffic light violation prediction system for a traffic signal, and as a collision avoidance system. A video camera is employed to obtain a video image of a section of a roadway. Motion is detected through changes in luminance and edges in frames of the video image. Predetermined sets of pixels (“tiles”) in the frames are designated to be in either an “active” state or an “inactive” state. A tile becomes active when the luminance or edge values of the pixels of the tile differ from the respective luminance or edge values of a corresponding tile in a reference frame in accordance with predetermined criteria. The tile becomes inactive when the luminance or edge values of the pixels of the tile do not differ from the corresponding reference frame tile in accordance with the predetermined criteria.

Abstract: A collision avoidance system and method for a traffic intersection having a traffic light, which selectively extends the duration of a red light cycle to prevent traffic from entering the intersection during a red light violation. Output from one or more violation prediction image capturing devices is used to provide images showing one or more vehicles approaching the intersection. A violation prediction unit, which is also coupled to a signal reflecting a current light phase of the first traffic signal, receives and processes vehicle location information derived from the images to generate violation predictions for the vehicles approaching the intersection. The violation prediction indicates a likelihood that an associated vehicle will violate an upcoming red light phase of the traffic signal. In response to the violation prediction, a violation predicted signal is provided to a traffic signal controlling traffic intersecting with the predicted violator.

Abstract: A system for separating and identifying classes of patterns or events which are not necessarily linearly separable. During a training process of the system, new prototypes are created when prior stored prototypes fail to properly classify an input pattern, and previously stored prototypes are modified when an input pattern falls within the sphere of influence of a prototype associated with a different class than the input pattern.

Abstract: A system is disclosed for separating and identifying classes of patterns or events which are not necessarily linearly separable. The patterns are represented by an input signal S. The system comprises (1) a plurality of classification units, connected in parallel to receive the input signal S and (2) a class selection device, responsive to the output signals produced by the classification units, for producing a single output response R representing the class of each respective pattern. At least some of the pattern classification units include generalizer units having a memory for storing a number of generalizer "prototypes" and a comparator for comparing the vector location of an input pattern with each of the generalizer prototypes.

Abstract: A system is disclosed for separating and identifying classes of patterns or events which are not necessarily linearly separable. The patterns are represented by an input signal S. The system comprises (1) a plurality of classification units, connected in parallel to receive the input signal S, and (2) a class selection device, responsive to the output signals produced by the classification units, for producing a single output response R representing the class of each respective pattern. In a preferred embodiment each classification unit includes a pattern feature encoding device, responsive to the input signal S, for producing an intermediate signal F.sub.i representative of the features contained in the pattern, and a pattern classifier, responsive to the signal F.sub.i, for producing an output signal R.sub.i representative of the respective class of the pattern, as identified by the features encoded by the feature encoding device.

Abstract: A system is provided for the separation into and the indentification of classes of events wherein each of the events is represented by a signal vector comprising the signals s, s.sub.z . . . , s.sub.j . . . , s.sub.N. The system comprises a plurality of assemblies, each of the assemblies including a matrix of junction elements for respectively receiving as inputs the different respective signals of a vector. The junction elements provide a transfer of information A.sub.ij s,; i.e., the product of the transfer function of the element and the signal input applied thereto. The information transferred by the junction elements is summed in each assembly. In the training mode of operation information summed in each assembly is applied to a scalar multiplier and the resulting information is in turn applied to a threshold stage which is actuated to produce an output if the input applied thereto attains a prescribed value.