Abstract: Certain example embodiments of the disclosed technology may include systems and methods for telematics monitoring. An example method is provided that includes receiving, at a mobile computing device, and from a Vehicle Identification Unit (VIU), identification (ID) data representing a first vehicle. The method further includes receiving, by the mobile computing device, sensor data from one or more sensors associated with the mobile computing device. Certain embodiments may further include receiving, at an Operational Measurement Unit (OMU), an operation indication associated with the first vehicle. The OMU may include an operational measurement component configured to advance an operational count in response to receiving the operation indication. Certain example embodiments may include transmitting telematics data by the mobile computing device. In certain embodiments, the telematics data may include least a portion of one or more of the ID data, the sensor data, and/or the operational count data.

Abstract: Certain example embodiments of the disclosed technology may include systems and methods for telematics monitoring. An example method is provided that includes receiving, at a mobile computing device, and from a Vehicle Identification Unit (VIU), identification (ID) data representing a first vehicle. The method further includes receiving, by the mobile computing device, sensor data from one or more sensors associated with the mobile computing device. Certain embodiments may further include receiving, at an Operational Measurement Unit (OMU), an operation indication associated with the first vehicle. The OMU may include an operational measurement component configured to advance an operational count in response to receiving the operation indication. Certain example embodiments may include transmitting telematics data by the mobile computing device. In certain embodiments, the telematics data may include least a portion of one or more of the ID data, the sensor data, and/or the operational count data.

Abstract: Certain example embodiments of the disclosed technology may include systems and methods for telematics monitoring. An example method is provided that includes receiving, at a mobile computing device, and from a Vehicle Identification Unit (VIU), identification (ID) data representing a first vehicle. The method further includes receiving, by the mobile computing device, sensor data from one or more sensors associated with the mobile computing device. Certain embodiments may further include receiving, at an Operational Measurement Unit (OMU), an operation indication associated with the first vehicle. The OMU may include an operational measurement component configured to advance an operational count in response to receiving the operation indication. Certain example embodiments may include transmitting telematics data by the mobile computing device. In certain embodiments, the telematics data may include least a portion of one or more of the ID data, the sensor data, and/or the operational count data.

Abstract: Certain example embodiments of the disclosed technology may include systems and methods for telematics monitoring. An example method is provided that includes receiving, at a mobile computing device, and from a Vehicle Identification Unit (VIU), identification (ID) data representing a first vehicle. The method further includes receiving, by the mobile computing device, sensor data from one or more sensors associated with the mobile computing device. Certain embodiments may further include receiving, at an Operational Measurement Unit (OMU), an operation indication associated with the first vehicle. The OMU may include an operational measurement component configured to advance an operational count in response to receiving the operation indication. Certain example embodiments may include transmitting telematics data by the mobile computing device. In certain embodiments, the telematics data may include least a portion of one or more of the ID data, the sensor data, and/or the operational count data.

Abstract: Monitoring systems and methods are configured to determine a pattern of vehicle usage or to verify personal data about a vehicle insurance applicant, without unreasonable expense to an insurance provider or the applicant. A monitoring system can track movements of a handheld mobile communication device, and can include a personal data unit, a communication unit, and an analysis unit. The personal data unit can receive personal data about the insurance applicant, including an identifier of a mobile communication device used by the insurance applicant. The communication unit can receive location data describing various locations of the mobile communication device.

Abstract: Certain example embodiments of the disclosed technology may include systems and methods for telematics monitoring. An example method is provided that includes receiving, at a mobile computing device, and from a Vehicle Identification Unit (VIU), identification (ID) data representing a first vehicle. The method further includes receiving, by the mobile computing device, sensor data from one or more sensors associated with the mobile computing device. Certain embodiments may further include receiving, at an Operational Measurement Unit (OMU), an operation indication associated with the first vehicle. The OMU may include an operational measurement component configured to advance an operational count in response to receiving the operation indication. Certain example embodiments may include transmitting telematics data by the mobile computing device. In certain embodiments, the telematics data may include least a portion of one or more of the ID data, the sensor data, and/or the operational count data.

Abstract: Surrogate heuristic identification is described, including a memory configured to store data associated with content, and a processor configured to select a portion of the content and the portion is standardized, to identify a characteristic associated with the portion, to use the characteristic to generate a data representation, the data representation being used to provide heuristic data, and to process the heuristic data to generate a fingerprint configured to compare against one or more stored fingerprints.

Abstract: Surrogate heuristic identification is described, including an interface configured to present data associated with content and a fingerprint, wherein the content and the fingerprint are compared to another fingerprint using heuristic data, and a plurality of panels presented within the interface, wherein each of the plurality of panels is configured to present other data generated from one or more functions performed by a logic module, wherein the one or more functions are associated with comparing the content and the fingerprint to the another fingerprint.

Abstract: Monitoring systems and methods are configured to determine a pattern of vehicle usage or to verify personal data about a vehicle insurance applicant, without unreasonable expense to an insurance provider or the applicant. A monitoring system can track movements of a handheld mobile communication device or rely on an application installed on said device, and can include a personal data unit, a communication unit, and an analysis unit. The personal data unit can receive personal data about the insurance applicant, including an identifier of a mobile communication device used by the insurance applicant.

Abstract: Monitoring systems and methods are configured to determine a pattern of vehicle usage or to verify personal data about a vehicle insurance applicant, without unreasonable expense to an insurance provider or the applicant. A monitoring system can track movements of a handheld mobile communication device, and can include a personal data unit, a communication unit, and an analysis unit. The personal data unit can receive personal data about the insurance applicant, including an identifier of a mobile communication device used by the insurance applicant. The communication unit can receive location data describing various locations of the mobile communication device. The analysis unit can analyze the location data to determine a level of risk for insuring the entity, based at least partially on movements of the mobile communication device indicated by the location data.

Abstract: Surrogate hashing is described, including a database configured to store data associated with a first file and a second file, and a processor configured to run a first hashing algorithm against a first portion of a first file to generate a first hash value, and running a second hashing algorithm against the first portion of the first file to generate a second hash value, to determine whether the first hash value and the second hash value are substantially similar to one or more stored hash values associated with a second portion of a second file, wherein the second portion is identified by one or more attributes that are substantially similar to one or more corresponding attributes associated with the first portion, and to identify a location of the second file if the first hash value and the second hash value are substantially similar to the one or more stored hash values associated with the second portion of the second file.

Abstract: Surrogate hashing is described, including initializing one or more variables in a collection, evaluating an address associated with a host, comparing the address to the collection to determine if the address is stored in the collection, and processing the address to hash a file identified by the address if the address is not stored in the collection or determining if another address is indicated by the address if the address is stored in the collection.

Abstract: Surrogate heuristic identification is described, including a memory configured to store data associated with an image, and a processor configured to select a portion of an image, and the portion is standardized, to identify a characteristic associated with the image, to use the characteristic to generate a data representation, the data representation being used to provide heuristic data, and to process the heuristic data to generate a fingerprint configured to compare against one or more stored fingerprints associated with other images.

Abstract: Methods, apparati, and products are provided, including running a hashing algorithm against a portion of a file to generate a hash value, determining whether the hash value is substantially similar to a stored hash value associated with another portion of another file, the portion and the another portion being standardized, and identifying a location of the another file if the hash value is substantially similar to the stored hash value associated with the another portion of the another file.

Abstract: Surrogate hashing is described, including running a hashing algorithm against a portion of a file to generate a hash value, determining whether the hash value is substantially similar to a stored hash value associated with another portion of another file, the portion and the another portion being standardized, wherein at least one of the portion and the another portion is an extremely small dataset, and identifying a location of the another file if the hash value is substantially similar to the stored hash value associated with the another portion of the another file.

Abstract: Surrogate hashing is described, including a memory configured to store data a hash value and data associated with a portion of a file, and a processor configured to run a hashing algorithm against a portion of a file to generate a hash value, to determine whether the hash value is substantially similar to a stored hash value associated with another portion of another file, the portion and the another portion being standardized, wherein at least one of the portion and the another portion is an extremely small dataset, and to identify a location of the another file if the hash value is substantially similar to the stored hash value associated with the another portion of the another file.

Abstract: Surrogate hashing is described, including a repository configured to store a standardized address and data associated with the standardized address, and a processor configured to parse an address associated with a host to generate a standardized address in a format used to compare the standardized address to one or more addresses stored in a collection, to determine if the standardized address is listed in the collection, and to process the standardized address.

Abstract: Surrogate heuristic identification is described, including a memory configured to store audio data associated with audio content, and a processor configured to select a portion of audio content, and the portion is standardized, to identify a characteristic associated with the portion, to use the characteristic to generate a data representation, the data representation being used to provide heuristic data associated with the audio content, and to process the heuristic data to generate a fingerprint associated with the audio content, and the fingerprint is configured to compare to one or more stored fingerprints to detect substantially similar audio content.

Abstract: Surrogate hashing is described, including running a first hashing algorithm against a first portion of a first file to generate a first hash value, and running a second hashing algorithm against the first portion of the first file to generate a second hash value, determining whether the first hash value and the second hash value are substantially similar to one or more stored hash values associated with a second portion of a second file, wherein the second portion is identified by one or more attributes that are substantially similar to one or more corresponding attributes associated with the first portion, and identifying a location of the second file if the first hash value and the second hash value are substantially similar to the one or more stored hash values associated with the second portion of the second file.

Abstract: Surrogate hashing is described, including running a hashing algorithm against a portion of a file to generate a hash value, determining whether the hash value is substantially similar to a stored hash value associated with another portion of another file, the portion and the another portion being standardized, and identifying a location of the another file if the hash value is substantially similar to the stored hash value associated with the another portion of the another file.