International Business Machines Corporation

Brent P Gross

Charles Daniel Wolfson

Sushain Pandit

David Alec Selby

Otis Smart

Harikumar Venkatesan

Guenter Anton Sauter

Michael R Self

Frederick L White

Florian Pinel

Curt Lee Cotner

Paul Arnold Ostler

Timothy Jon Vincent

James Warden Marlin

Robert Alan Begg

Corey A Stubbs

Gerald B Anderson

Von D Tucker

Historical device positioning data captured from one or more devices over a period of time is received. The historical device positioning data includes historical latitude, longitude, and elevation data of the one or more devices. Building boundaries for a give building are identified based upon the historical latitude and longitude data. The historical device positioning data corresponding to locations within the building boundaries of the building is clustered using a machine learning-based clustering algorithm, resulting in clusters with corresponding cluster centroids. The cluster centroids are associated with respective floors within the building. A current floor of the building on which a specific device is located is determined by mapping current device positioning data of the specific device to the closest cluster centroid.

Spatial device clustering-based emergency response floor identification

Computer-implemented event detection includes obtaining, at one or more processors, multimedia data including multiple frames of video data and corresponding audio data. The processor(s) process the multiple frames to detect at least one object and to track the object(s) between two or more of the frames. The processor(s) generate sonification audio data representing a position of the object(s) in the two or more frames, movement of the object(s), or both the position and the movement of object(s). The processor(s) generate combined audio data including the audio data and the sonification audio data. The processor(s) generate one or more feature vectors representing the combined audio data and provide the feature vector(s) as input to a trained event classifier to detect an event represented in the multimedia data.

Computer-implemented event detection using sonification

Known geospatial device coordinates are clustered using a clustering algorithm into device clusters with cluster centroids. Each device cluster corresponds to a geographical location. Each cluster centroid is annotated with a regional floor-height value of the respective geographical location. Current device data of a device, including geographic location and elevation, are received. An approximate current floor upon which the first device is located is determined using the elevation of the first device and the annotated regional floor-height value of a closest cluster centroid, the closest cluster centroid determined based, at least in part, on the geographic location of the first device. An individual is directed to the device's geographic location and approximate current floor. The device clusters are re-computed based upon feedback from the individual regarding the device's actual floor.

First responder feedback-based emergency response floor identification

Using a location sensor, a location including a latitude and a longitude of a device is determined. Using an air pressure sensor, a first elevation of a device is determined. Using the location, a corresponding street address is determined. Using the street address and the first elevation, a floor number is determined. The street address and the floor number are reported to an emergency response system.

Enhanced elevation detection for emergency response systems

At an emergency response system, a first location including a latitude and a longitude at which a first device is located is received. At an emergency response system, an air pressure reading measured by the first device is received. Using the air pressure reading and a mean sea-level barometric measurement, a first elevation of a device is computed. Using the first location, a corresponding street address is computed. Using the street address and the first elevation, a floor number is computed. The street address and the floor number are transmitted to a second device.

Known geospatial device coordinates are clustered using a machine learning-based clustering algorithm into device clusters with cluster centroids. Each device cluster corresponds to a geographical location. Each cluster centroid is annotated with a regional floor-height value of the respective geographical location. Current device data of a device, including latitude, longitude, and elevation, are received, and a geographic location of the device is determined using the latitude and longitude. An approximate current floor upon which the first device is located is determined by mapping the current device data of the first device to a closest cluster centroid, and calculating the approximate current floor using the elevation of the first device and the annotated regional floor-height value of the closest cluster centroid. An individual is directed to the device's geographic location and approximate current floor. The device clusters are re-computed based upon feedback from the individual regarding the device's actual floor.

An initiation of an emergency communication with an emergency service associated with an emergency telephone number is detected by a mobile communications device. A completion of the emergency communication using a first communication path associated with a mobile communications service provider is attempted. The mobile communication device determines that the emergency communication using the first communication path has failed. An identity of a destination of the failed emergency communication is determined using location and telemetry data from the mobile communication device. A connection of the mobile communications device to the identified destination is facilitated using a second communication path. The mobile communications device is identified to the determined destination as an originator of the connection.

Emergency call service backup using device user plane communications

A database server helps to streamline the retrieval of LOB values by deciding to send a locator in replacement of the LOB value, or the LOB value itself, depending upon the specific LOB value being retrieved. A threshold value is determined in a fetch query, and the LOB sizes below that threshold are sent as values in a corresponding fetch response, and the lengths above are sent as locators in the fetch response. Indicators are inserted in a fetch parameter of the response to inform the receiving client the form of retrieval that was used for each requested LOB value being returned.

System and method for executing a large object fetch query against a database

This invention is a method for annotating and redacting a final-form document archived in a computerized system where it is important that the fidelity of the final form document is preserved. More particularly, this method allows final-form documents containing objects such as texts, graphics and images to be annotated or redacted by other objects carried in the same data stream without compromising the integrity of the original document.

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Scarborough, Canada

Brent P Gross