International Business Machines Corporation

Edward Tyrone Childress

Rhonda L Childress

Michael Bender

Gregory J Boss

Donald L Muchmore

David B Kumhyr

Neil Raymond Pennell

Michael P Shute

Charles D Wriska

A method, computer program product, and a system where a processor(s) obtains data related to physical activities performed by an individual from a sensor(s) proximate to the individual. The processor(s) cognitively analyzes the data to identify baseline behavioral patterns of the individual, when the individual is engaged in each of the physical activities. The processor(s) obtains data indicating consumption of a substance by the individual at a first time. The processor(s) determines impacts of the consumption on the baseline behavioral patterns of the individual and generates a data structure (a predictive model) that includes expected deviations from the baseline behavioral patterns of the individual, when the individual has consumed the substance.

Predictive model for substance monitoring and impact prediction

A method and system analyzes the productivity of a person engaged in a task. A computing device receives configuration data from sensors including environmental parameters related to a corresponding productivity score of the person engaged in the task. The environmental parameter data is analyzed to determine any impact on the person's productivity during the task. Changes in the productivity score and corresponding environmental parameters are stored in the computing device, and optimum values are determined.

System and method to measure optimal productivity of a person engaged in a task

A method, computer program product, and system includes a processor(s) configuring a sensor(s) (first sensor(s)), to capture data related to an emotional state of an individual and a sensor(s) (second sensor(s)), to capture data related to an environment of the individual. The processor(s) obtains, over a pre-defined period of time, data from the sensors and utilizes data from the second sensor(s) to identify activities in which the individual participated. The processor(s) obtains, from a scheduling resource, a schedule of activities scheduled for the individual. The processor(s) generates a record for each activity. The processor(s) determines, based on data from the first sensor(s) and the record for each activity, emotional states of the individual throughout each activity of the identified activities. The processor(s) generates a rule representing relationships between events during each activity and emotional state of the participant and recommends a schedule of future activities.

Enforcement of services agreement and management of emotional state

A computer-implemented method is provided for facilitating an interaction between a first and second entity. The method includes instructing, by a cognitive recommendation engine, a communication aspect of the interaction between the first entity and the second entity. The instructing includes obtaining, by the cognitive recommendation engine, interaction preference data of the first entity related to the communication aspect of the interaction, and based on the interaction preference data, determining by the cognitive recommendation engine, an instruction recommendation. The instruction recommendation facilitates, from the first entity's view, the interaction between the first and second entities. Further, the instructing includes providing by the cognitive recommendation engine the instruction recommendation to the second entity for use by the second entity during the interaction with the first entity.

Cognitive recommendation engine facilitating interaction between entities

An unexpressed liking and an unexpressed dislike of a user, which are not specified in the user's preference are determined by cognitive analytics. The unexpressed liking and dislike correspond to a first and second characteristic of items, respectively. In a list, a first item having the first characteristic and available in an inventory is included, which is, and a second item having the second characteristic and also available in the inventory is excluded. Items included in the list are arranged according to the user's degrees of liking or the items. An item having the first characteristic is determined to be absent from the inventory. Using completed sales information received from a set of retailer systems, an estimated value of a lost sales opportunity produced when the absent item is purchased is computed. The prioritized list and an accommodation offer responsive to the cost of the lost opportunity are presented.

Cognitive expansion of user acceptance criteria

A method, system, and computer program product are disclosed for customized ratings for specified media items. In embodiments, the method comprises a user giving input about multiple segments of a first specified media item, analyzing the input from the user, and correlating the analyzed input with multiple segments of a second specified media item to provide to the user a customized content rating of the second media item. In embodiments, the system comprises a first processing device for receiving input from a user about multiple segments of a first specified media item; and a computing system for receiving the user input from the first processing device, for analyzing the user input, and for correlating the analyzed input with multiple segments of a second specified media item to provide to the user a customized content rating of the second media item.

Recording ratings of media segments and providing individualized ratings

A driver action system for monitoring traffic and capturing specific information about the car and the driver from a GPS device and other IoT sensors. Driver history and tendencies can provide insight into a driver's intention while on the road. The system will analyze the collected information and broadcast an alert to other drivers in the same area. A broadcast to the other devices or users in the area would include the probability or percentage of the driver taking a particular action or a lack of familiarity with the area.

Warning driver of intent of others

Transactions with respect to database operations are fingerprinted by associating transaction identifiers with logged information about those database operations. An SQL query is obtained prior to its evaluation by a database engine. A transaction identifier to be associated with the SQL query is also obtained. The SQL query is then modified to generate a modified SQL query, wherein the modified SQL query includes a WHERE clause that contains an expression that always evaluates to a logical true value, and wherein the expression contains the transaction identifier. The modified SQL query is then sent to the database engine for evaluation within the data processing system. When the processing of the modified SQL query is logged with a copy of the modified SQL query, the logged information contains a copy of the transaction identifier.

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Austin, TX, United States of America

Edward Tyrone Childress