Accenture Global Solutions Limited

Dominique Verdejo

Freddy Lecue

Md Faisal Zaman

A device may receive data associated with an event. The device may identify a context of the event based on receiving the data. The device may identify a similar event based on performing a comparison of the context of the event and a context of the similar event. The device may determine a set of pre-events associated with the event based on identifying a pre-event that occurred before the similar event. The set of pre-events may include at least one pre-event similar to the pre-event that occurred before the similar event. The device may determine a set of post-events associated with the event based on determining the set of pre-events and identifying a post-event that occurred after the similar event. The set of post-events may include at least one post-event similar to the post-event. The device may perform an action based on the set of post-events.

Automatic prediction of an event using data

A device may receive, from one or more other devices, one or more images that depict one or more events occurring at a location. The device may detect an event of the one or more events depicted in the one or more images. The device may determine a first score that indicates a first likelihood that the event is an anomalous event. The device may determine a second score that indicates a similarity between the event and another event. The second score may be based on second data received from the one or more other devices. The device may determine a third score based on the first score and the second score. The third score may indicate a second likelihood that the event is the anomalous event. The device may perform an action based on the third score.

Automatically detecting an event and determining whether the event is a particular type of event

A device may receive, from another device, an image that depicts one or more events occurring at a location. The device may detect an event of the one or more events depicted in the image. The device may determine a first score that indicates a likelihood that the event is an anomalous event. The first score may be based on first data received from the other device. The device may determine a second score that indicates a similarity between the event and another event. The second score may be based on second data received from the other device. The second data may comprise data from a sensor, a wearable device, a mobile device, and/or a handheld device. The device may perform an action based on the first score or the second score.

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Dominique Verdejo