International Business Machines Corporation

John David Costantini

Sarbajit Kumar Rakshit

Shubhadip Ray

Avik Sanyal

An autonomous computing system managed through an internet of things (IoT) protocol is provided. A computing device determines a clustering of autonomous vehicles based on expression sentiment data of each passenger of a respective autonomous vehicle. A computing device determines a node within an IoT network and monitors a plurality of autonomous vehicles traveling though the node. A computing device identifies a time frame in which each respective vehicle in the cluster is predicted to pass through an intersection. A computing device identifies a current traffic pattern of a vehicle that is external to the cluster of autonomous vehicles. The one or more processors adjust the traffic flow to allow the clustering of autonomous vehicles to pass through an intersection at a rate that maintains a threshold level of comfort for each passenger in the determined cluster of autonomous vehicles.

Autonomous vehicle safety system

Detecting trends is provided. The method comprises receiving, from a number of data sources, data regarding choices of people at a number of specified events and public places and determining, according to a number of clustering algorithms, trend clusters according to data received from the data sources cross-referenced to defined event types and place types. Customer profile data and preferences are received from a number of registered customers through user interfaces, and a number of customer clusters according to the customer profile data and preferences are determined according to clustering algorithms. Correlation rules are calculated between the trend clusters and the customer clusters. A number of trend predictions and recommendations are then sent to a user regarding a number of specified events or time frames according to the correlation rules.

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Jersey City, NJ, United States of America

John David Costantini