Abstract: The present invention extends to methods, systems, and computer program products for ingesting streaming signals. Signal ingestion modules sample a frame from a raw streaming signal. A preliminary severity or possible event type is computed from the sampled frame. A deeper inspection request is triggered of the raw streaming signal or of another raw streaming signal. Segments of content from the raw streaming signal or the other raw streaming signal are inspected. An actual severity or actual event type is computed from the inspected content. The actual severity or actual event type can be included in a normalized signal.

Abstract: The present invention extends to systems and methods for notifying entities of relevant events. A boundary geometry, a user event truthfulness preference, a first event type, a second event type, and an area are combined into a rule formula. The first event type and a first event truthfulness associated with a detected event are accessed. The second event type and a second event truthfulness associated with another detected event are accessed. It is determined that the first event type and the second event type occurred in combination in the area within a boundary defined by the boundary geometry and that the first event truthfulness and the second event truthfulness both satisfy the user event truthfulness preference. An entity is automatically electronically notified in accordance with notification preferences that the rule formula was satisfied.

Abstract: The present invention extends to methods, systems, and computer program products for normalizing insufficient signals based on additional information. A probability of an event occurring is detected from a raw signal. It is determined signal characteristics of the raw signal are insufficient to normalize the raw signal along at least one of: a time, location, or context dimension. In one aspect, an additional signal relevant to the signal is ingested. In another aspect, a previously detected event relevant to the signal is accessed from a geo cell database. The raw signal is normalized, including deriving at least one of: the time dimension, the location dimension, or the context dimension from a combination of the signal characteristics and characteristics of the other signal and/or characteristics of the previously detected event.

Abstract: The present invention extends to systems and methods for notifying entities of relevant events. A boundary geometry, a user event truthfulness preference, a first event type, a second event type, and an area are combined into a rule formula. The first event type and a first event truthfulness associated with a detected event are accessed. The second event type and a second event truthfulness associated with another detected event are accessed. It is determined that the first event type and the second event type occurred in combination in the area within a boundary defined by the boundary geometry and that the first event truthfulness and the second event truthfulness both satisfy the user event truthfulness preference. An entity is automatically electronically notified in accordance with notification preferences that the rule formula was satisfied.

Abstract: The present invention extends to systems and methods for notifying entities of relevant events. An entity defines a rule formula that is triggered when one or more detected events match the rule formula including defining one or more event types and one or more locations types. A boundary associated with a selected location type is also received along with a monitoring area. The received elements are combined into the rule formula notification preferences are associated with the defined rule. One or more events are detected and then compared to the rule formula to determine if the combination of one or more event types occurred within the boundary of the one or more location types within the area.

Abstract: The present invention extends to methods, systems, and computer program products for ingesting streaming signals. Signal ingestion modules sample a frame from a raw streaming signal. A preliminary severity or possible event type is computed from the sampled frame. A deeper inspection request is triggered of the raw streaming signal or of another raw streaming signal. Segments of content from the raw streaming signal or the other raw streaming signal are inspected. An actual severity or actual event type is computed from the inspected content. The actual severity or actual event type can be included in a normalized signal.

Abstract: The present invention extends to systems and methods for notifying entities of relevant events. An entity defines a rule formula that is triggered when one or more detected events match the rule formula including defining one or more event types and one or more locations types. A boundary associated with a selected location type is also received along with a monitoring area. The received elements are combined into the rule formula notification preferences are associated with the defined rule. One or more events are detected and then compared to the rule formula to determine if the combination of one or more event types occurred within the boundary of the one or more location types within the area.

Abstract: The present invention extends to systems and methods for notifying entities of relevant events. An entity defines a rule formula that is triggered when one or more detected events match the rule formula including defining one or more event types and one or more locations types. A boundary associated with a selected location type is also received along with a monitoring area. The received elements are combined into the rule formula notification preferences are associated with the defined rule. One or more events are detected and then compared to the rule formula to determine if the combination of one or more event types occurred within the boundary of the one or more location types within the area.

Abstract: The present invention extends to systems and methods for notifying entities of relevant events. An entity defines a rule formula that is triggered when one or more detected events match the rule formula including defining one or more event types and one or more locations types. A boundary associated with a selected location type is also received along with a monitoring area. The received elements are combined into the rule formula notification preferences are associated with the defined rule. One or more events are detected and then compared to the rule formula to determine if the combination of one or more event types occurred within the boundary of the one or more location types within the area.

Abstract: The present invention extends to methods, systems, and computer program products for ingesting streaming signals. Signal ingestion modules sample a frame from a raw streaming signal. A preliminary severity or possible event type is computed from the sampled frame. A deeper inspection request is triggered of the raw streaming signal or of another raw streaming signal. Segments of content from the raw streaming signal or the other raw streaming signal are inspected. An actual severity or actual event type is computed from the inspected content. The actual severity or actual event type can be included in a normalized signal.

Abstract: The present invention extends to methods, systems, and computer program products for normalizing insufficient signals based on additional information. A probability of an event occurring is detected from a raw signal. It is determined signal characteristics of the raw signal are insufficient to normalize the raw signal along at least one of: a time, location, or context dimension. In one aspect, an additional signal relevant to the signal is ingested. In another aspect, a previously detected event relevant to the signal is accessed from a geo cell database. The raw signal is normalized, including deriving at least one of: the time dimension, the location dimension, or the context dimension from a combination of the signal characteristics and characteristics of the other signal and/or characteristics of the previously detected event.

Abstract: The present invention extends to systems and methods for notifying entities of relevant events. An entity defines a rule formula that is triggered when one or more detected events match the rule formula including defining one or more event types and one or more locations types. A boundary associated with a selected location type is also received along with a monitoring area. The received elements are combined into the rule formula notification preferences are associated with the defined rule. One or more events are detected and then compared to the rule formula to determine if the combination of one or more event types occurred within the boundary of the one or more location types within the area.

Abstract: The present invention extends to methods, systems, and computer program products for normalizing insufficient signals based on additional information. A probability of an event occurring is detected from a raw signal. It is determined signal characteristics of the raw signal are insufficient to normalize the raw signal along at least one of: a time, location, or context dimension. In one aspect, an additional signal relevant to the signal is ingested. In another aspect, a previously detected event relevant to the signal is accessed from a geo cell database. The raw signal is normalized, including deriving at least one of: the time dimension, the location dimension, or the context dimension from a combination of the signal characteristics and characteristics of the other signal and/or characteristics of the previously detected event.

Abstract: The present invention extends to methods, systems, and computer program products for ingesting streaming signals. Signal ingestion modules sample a frame from a raw streaming signal. A preliminary severity or possible event type is computed from the sampled frame. A deeper inspection request is triggered of the raw streaming signal or of another raw streaming signal. Segments of content from the raw streaming signal or the other raw streaming signal are inspected. An actual severity or actual event type is computed from the inspected content. The actual severity or actual event type can be included in a normalized signal.

Abstract: The present invention extends to methods, systems, and computer program products for normalizing ingested signals. In general, different types of raw signals including source data in different pluralities of data dimensions and including other characteristics are ingested. Per raw signal, a transdimensionality transform is applied to recode and normalize the source data into a normalized signal that includes normalized data in a common reduced plurality of dimensions including a time dimension, a location dimension, and a context dimension. Normalization can include inferring signal annotations from the source data and using the annotations and/or the other characteristics to derive time, location, and context dimensions. Derivation can include computing a probability of a real-world event and including the probability in the context dimension. An real-world event is detection from the normalized data in the time, location, and context dimensions and an entity is notified of the real-world event.

Abstract: The present invention extends to methods, systems, and computer program products for normalizing insufficient signals based on additional information. A probability of an event occurring is detected from a raw signal. It is determined signal characteristics of the raw signal are insufficient to normalize the raw signal along at least one of: a time, location, or context dimension. In one aspect, an additional signal relevant to the signal is ingested. In another aspect, a previously detected event relevant to the signal is accessed from a geo cell database. The raw signal is normalized, including deriving at least one of: the time dimension, the location dimension, or the context dimension from a combination of the signal characteristics and characteristics of the other signal and/or characteristics of the previously detected event.

Abstract: The present invention extends to methods, systems, and computer program products for ingesting streaming signals. Signal ingestion modules sample a frame from a raw streaming signal. A preliminary severity or possible event type is computed from the sampled frame. A deeper inspection request is triggered of the raw streaming signal or of another raw streaming signal. Segments of content from the raw streaming signal or the other raw streaming signal are inspected. An actual severity or actual event type is computed from the inspected content. The actual severity or actual event type can be included in a normalized signal.

Abstract: The present invention extends to methods, systems, and computer program products for normalizing ingested signals. In general, signal ingestion modules ingest different types of raw structured and/or raw unstructured signals on an ongoing basis. The signal ingestion modules normalize raw signals into normalized signals having a Time, Location, Context (or “TLC”) dimensions. A Time (T) dimension can be a time of origin or alternatively “event time” of a signal. A Location (L) dimension can be anywhere across a geographic area, such as, a country (e.g., the United States), a State, a defined area, an impacted area, an area defined by a geo cell, an address, etc. A Context (C) dimension indicates circumstances surrounding formation/origination of a raw signal in terms that facilitate understanding and assessment of the raw signal. The Context (C) dimension of a raw signal can be derived from express as well as inferred signal features of the raw signal.

Abstract: The present invention extends to methods, systems, and computer program products for normalizing insufficient signals based on additional information. Evidence of an event is detected from a raw signal. It is determined signal characteristics of the raw signal are insufficient to normalize the raw signal along at least one of: a time, location, or context dimension into a Time, Location, Context (TLC) format. In one aspect, an additional raw signal related to the detected evidence is accessed from another signal source. In another aspect, a previously detected event related to the detected evidence is received from a geo cell database. The raw signal is normalized into the Time, Location, Context (TLC) format, including deriving at least one of: the time dimension, the location dimension, or the context dimension from a combination of the signal characteristics and characteristics of the other signal and/or characteristics of the previously detected event.

Abstract: The present invention extends to methods, systems, and computer program products for normalizing insufficient signals based on additional information. Evidence of an event is detected from a raw signal. It is determined signal characteristics of the raw signal are insufficient to normalize the raw signal along at least one of: a time, location, or context dimension into a Time, Location, Context (TLC) format. In one aspect, an additional raw signal related to the detected evidence is accessed from another signal source. In another aspect, a previously detected event related to the detected evidence is received from a geo cell database. The raw signal is normalized into the Time, Location, Context (TLC) format, including deriving at least one of: the time dimension, the location dimension, or the context dimension from a combination of the signal characteristics and characteristics of the other signal and/or characteristics of the previously detected event.