Abstract:
A generation technique and an analysis technique of a large number of explanatory variables to derive effective measures by using various data are provided. Specifically, a factor which lurks in a large amount of data and affects business performance is identified by automatically generating a large number of explanatory variables and performing correlation analysis between the explanatory variables and an objective variable. Three operators representing condition, target, and arithmetic which are variable generation conditions are defined in advance for data inputted into an analysis system and a large number of explanatory variables are automatically generated by these operators.
Abstract:
An analysis sever capable of performing analysis among a large amount of sensor data in order to obtain an analysis result that a reader desires and outputting the result instantaneously. The analysis server rearranges the sensor data acquired from a sensor node into time series data. The analysis is performed separately for time trigger analysis (D) and for event trigger analysis (F) depending on analysis contents. In the time trigger analysis (D), analysis processing that is basically needed when visualizing a state of an organization is performed. In the event trigger analysis (F), an analysis result obtained by the time trigger analysis (D) is processed using the reader's desired information and is outputted.
Abstract:
On-site getting in and out data including the number of people who got in the elevator in the past is created, virtual getting in and out data including the number of people who get in the elevator is created by making people who arrive at a landing of the elevator virtually appear and simulating operation of the elevator on the basis of the number of people who appear, a first conversion model for converting the virtual getting in and out data before a certain time point into the number of people who appear after the certain time point and a second conversion model for converting the virtual getting in and out data after a certain time point into the number of people who appear before the certain time point are created on the basis of the number of people who appear and the virtual getting in and out data, a prediction model for predicting the number of people who appear after a certain time point from the number of people who appear before the certain time point is learned on the basis of the number of people who appear converted by the second conversion model, and the number of people who appear after a certain time point is predicted from the on-site getting in and out data before the certain time point by using the first conversion model and the prediction model.
Abstract:
A sensor-net system for digitizing a relationship between persons in an organization includes plural terminals and a processor for processing data received from those terminals. Each of the terminals includes a sensor for sensing a physical amount and a data sender for sending data denoting the physical amount sensed by the sensor. The processor calculates a value denoting a relationship between a first terminal wearing person and a second terminal wearing person according to the data received from the first and second terminals.
Abstract:
For providing an information processing system which enables easier automatic extraction of a more suitable object for which a measure is to be taken, the information processing system for extracting the object for which the measure is taken is configured to include: a reception. unit (GSO5) which receives first data (GSC11) related to business of an enterprise and second data (GSC12) that is related to the business of the enterprise and has granularity equal to or finer than the granularity of the first data; an index generation unit (GSO2) which generates, from the first data, a plurality of descriptive indices matching the granularity of the second data; and an extraction unit (GSO1) which extracts from the descriptive indices, the object for which the measure is to be taken.
Abstract:
A generation technique and an analysis technique of a large number of explanatory variables to derive effective measures by using various data are provided. Specifically, a factor which lurks in a large amount of data and affects business performance is identified by automatically generating a large number of explanatory variables and performing correlation analysis between the explanatory variables and an objective variable. Three operators representing condition, target, and arithmetic which are variable generation conditions are defined in advance for data inputted into an analysis system and a large number of explanatory variables are automatically generated by these operators.
Abstract:
Provided is a sensor data analysis system, comprising terminals, a control unit, an analysis unit, and a storage unit, wherein the terminals worn on persons belonging to an organization, the terminals each comprising a sensor to measure a physical quantity, the storage unit holds an activity index of the organization, and holds, for a first condition relating to a behavior of each of the persons, advice corresponding to a statistical relation between an amount of the behavior satisfying the first condition and the activity index, the control unit generates a behavior index for indicating a behavior of a first person based on the physical quantity, the analysis unit calculates, for the first condition, the statistical relation between the amount of the behavior satisfying the first condition and the activity index based on the behavior index, and the control unit outputs advice corresponding to the statistical relation satisfying a second condition.
Abstract:
An analysis system analyzes a state of a person and includes a terminal configured to be worn on the person's body. The terminal includes an acceleration sensor, a storage unit, and a processing unit. The processing unit determines whether each value contained in the time series data is in a first state in which the value is equal to or greater than the threshold or in a second state in which the value is less than the threshold. The processing unit also determines a duration which is a period of time during which the first state continues. The processing unit quantifies a brain state of the person on the basis of the duration.
Abstract:
A data analysis support systems according to the present invention assumes any of multiple indices to be an objective variable, implements clustering and collectively outputs indices belonging to the identical cluster.