International Business Machines Corporation

Nageswara Sastry Renduchintala

Su Liu

Jonathan D Dunne

Zachary A Silverstein

Hernan A Cunico

Yang Liang

Hamid Majdabadi

A computer implemented method processes log events. A computer system determines dependence and independence of training log events. The computer system clusters the training log events with determined dependence and independence to form clustered training log events. The computer system generates an event association model using the clustered training log events. The computer system clusters the log events using the event association model.

Artificial intelligence driven log event association

An embodiment for detecting the danger of an object in close proximity of a subject is provided. The embodiment may include receiving real-time data from one or more IoT devices in a surrounding environment. The embodiment may also include detecting and classifying one or more subjects and one or more objects in an image from the one or more IoT devices. The embodiment may further include identifying one or more risk factors associated with each object. The embodiment may also include correlating the one or more risk factors associated with each object with the one or more subjects in the image. The embodiment may further include identifying relative positions of the one or more subjects and the one or more objects in the image. The embodiment may also include in response to determining a current position of at least one subject is dangerous, notifying a user of the danger.

Proximity danger detection based on subject and object distance analysis

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Kolkata, India

Nageswara Sastry Renduchintala