International Business Machines Corporation

Olivier Verscheure

Lisa Amini

Deepak Srinivas Turaga

Pascal Frossard

Peter Hans Westerink

Michael Wurst

Pascal Pompey

Chitra Venkatramani

Anika Schumann

Eric P Bouillet

Jeremy Silber

Niall Brady

Anshul Sehgal

Aris Gkoulalas-Divanis

Stefano Braghin

Adi Ionel Botea

Upendra V Chaudhari

Joern Ploennigs

Spyridon Antonatos

Michele Berlingerio

Francesco Calabrese

Mark C Johnson

Ching-Yung Lin

Freddy Lecue

Srinivasan Parthasarathy

Francesco Fusco

Christoph Lingenfelder

Martin G Kienzle

Amadou Ba

Lea A Deleris

Raymond Lloyd

Justin Wai-chow Wong

Donna Leigh Gresh

Bernard Gorman

Hsin I Tseng

Pierre Vandergheynst

Zhen Liu

Joel Leonard Wolf

Wei Fan

Bei Chen

Ganesh Nachiappa Ramaswamy

Nagui Halim

Daby Mousse Sow

Michail Vlachos

Alice-Maria Marascu

Juan Manuel Huerta

Alain E Biem

Perry G Hartswick

Brian Christopher Barker

Themis Palpanas

Brian Douglas Pfeifer

Edward Sumner Begle

Pascal Frossad

Brian K Foo

Gerett Raybourn Yocum

Lars Kristen Selberg Daldorff

Raymond E Rose, Jr

Ray E Rose

Lisa D Amini

Chitra Venka-Tramani

Energy usage can be monitored within at least one building having a plurality of energy consuming components. A database can be generated that contains values for a set of data points corresponding to data received from the plurality of energy consuming components. A change in a configuration can be detected for the plurality of energy consuming components based upon a change in values received from plurality of energy consuming components relative to the database. Based upon the change, an additional data point can be added to the set of data points in the database. Based upon the values for the set of data points, a probability can be determined that a rule for the additional data point is valid. A message can then be generated that includes the determined probability.

Management of building energy systems through quantification of reliability

A method, system and computer program product for providing privacy protection to data streams in a distributed computing environment. The method includes concurrently processing, by a plurality of computer machines, data streams of attributes containing data values received by each of the plurality of local computer machines; indexing the data values for each attribute of the plurality of data streams received by each of the plurality of local computer machines; providing the indexed data values to a main computer machine; integrating, by the main computer machine, the local computer machine indexed data values into a global index data structure for the plurality of data streams; and identifying privacy vulnerabilities of the attributes that are direct identifiers and quasi-identifiers based on the global index.

Method/system for the online identification and blocking of privacy vulnerabilities in data streams

In one aspect, a method for reducing uncertainty in a hydraulic model of a water distribution network due to uncertain parameters and faults in the water distribution network is provided which includes the steps of: (i) calculating an optimized placement of sensors throughout a given uncertain section of the water distribution network; (ii) collecting data from the sensors; (iii) partitioning the given uncertain section of the water distribution network into observable and unobservable sub-sections based on the hydraulic model and a) a position, b) a number, and/or c) a type of the sensors that are available; (iv) correcting uncertain parameters and identifying faults for each of the observable sub-sections; (v) calculating a global uncertainty value for each of the unobservable sub-sections; and (vi) repeating the steps (i)-(vi) iteratively, at each iteration selecting an uncertain sub-section of the water distribution network, until no uncertain sub-sections of the water distribution network remain.

Techniques for iterative reduction of uncertainty in water distribution networks

An embodiment of the invention includes a processor can identify one or more simple patterns in at least one data stream of the data streams. The simple pattern can include repetition of a data object of the data objects. The processor can also identify one or more multi-patterns in at least one data stream of the data streams, wherein the multi-pattern can include repetition of a data block. The data block can include at least two contiguous data objects that are in the same order in the data block. The processor can identify one or more composite patterns in at least two data streams of the data streams, wherein the composite pattern can include data objects on each of the at least two data streams that repeat together in the same pattern.

Mining of composite patterns across multiple multidimensional data sources

Distributed, consistent utility-preserving data masking is provided by retrieving an original value from a data table; initiating a communication with a mapping service to ascertain whether or not a masking table of the mapping service includes a fictionalized value associated with the original value; when the masking table does not include a fictionalized value associated with the original value, producing a fictionalized value for the original value wherein the fictionalized value preserves at least one utility function of the original value, updating the mapping service to include the fictionalized value in the masking table, and applying a first masking operation by replacing the retrieved original value with the fictionalized value.

Consistent utility-preserving masking of a dataset in a distributed environment

A method and system for automatically identifying and protecting privacy vulnerabilities in data streams includes indexing data values for each attribute of the data stream received by local virtual machines based on a schema of each data stream, classifying the data attributes of the plurality of data streams into known data types, integrating the local virtual machine indexes into a global index data structure for the data streams including single attribute data values, identifying privacy vulnerabilities in the data as attributes that are direct identifiers based on the attribute data values stored in the global index and combinations of attributes that are quasi-identifiers based on the low frequency of certain combinations of attribute data value pairs by computing the frequency based on the single attribute data values stored in the global index and providing privacy protection to the data streams by applying data transformations on the discovered direct identifiers and the quasi-identifiers.

Software that uses actual, historic building management system (BMS) data and/or machine logic to estimate an amount of energy that would have been consumed (and saved) had the BMS been operated under the control of an energy management system (EMS). The software performs the following steps: (i) receiving first actual BMS information relating to operation of a first set of appliance(s) located in a first building during a first time interval; (ii) selecting a first proposed EMS rule set; and (iii) determining a first contrafactual energy resource use value based, at least in part, on the first actual BMS information, with the first contrafactual use value corresponding to an amount of energy resources that would have been consumed by the first set of appliance(s) if the BMS had operated the first set of appliance(s) under control of the first proposed EMS rule set.

Estimating energy savings from building management system point lists

Embodiments of the disclosure include a method for journey planning including receiving a journey planning request, the journey planning request having an origin and a destination in a transportation network. The method also includes calculating an optimized journey plan by identifying a plurality of routes through the transportation network from the origin to the destination and determining an uncertainty associated with each of the plurality of routes. Calculating an optimized journey plan also includes evaluating a robustness of each of the plurality of routes to the uncertainty associated with each of the plurality of routes and selecting the optimized journey plan based on the journey planning request and the robustness of each of the plurality of routes.

Hedging risk in journey planning

Techniques for configuring a Building Energy Management System (BEMS) using knowledge encoded in BMS point lists are provided. In one aspect, a method for configuring a BEMS of a site is provided. The method includes the following steps. A knowledge base is derived from subject matter expertise. The knowledge base is used to extract one or more building characteristics from a point list of a building management system (BMS) that are not directly available from the BMS point list. The BEMS is configured using the one or more building characteristics extracted from the BMS point list.

Configuring building energy management systems using knowledge encoded in building management system points lists

Embodiments of the disclosure include a computer system for journey planning, the computer system includes a journey planning server configured to perform a method. The method includes receiving a journey planning request, the journey planning request having an origin and a destination in a transportation network. The method also includes calculating an optimized journey plan by identifying a plurality of routes through the transportation network from the origin to the destination and determining an uncertainty associated with each of the plurality of routes. Calculating an optimized journey plan also includes evaluating a robustness of each of the plurality of routes to the uncertainty associated with each of the plurality of routes and selecting the optimized journey plan based on the journey planning request and the robustness of each of the plurality of routes.

Techniques for iterative feature extraction using domain knowledge are provided. In one aspect, a method for feature extraction is provided. The method includes the following steps. At least one query to predict at least one future value of a given value series based on a statistical model is received. At least two predictions of the future value are produced fulfilling at least the properties of 1) each being as probable as possible given the statistical model and 2) being mutually divert (in terms of numerical distance measure). A user is queried to select one of the predictions. The user may be queried for textual annotations for the predictions. The annotations may be used to identify additional covariates to create an extended set of covariates. The extended set of covariates may be used to improve the accuracy of the statistical model.

Iterative active feature extraction

A method for selecting an analysis procedure for a value series, including displaying a value series on a computer display monitor, receiving one or more sequences of user provided annotations, where the annotations overlay at least a sub-interval of the value series on the computer display monitor, using the sequences of user provided annotations to select an optimal value series analysis method from a set of value series analysis methods, where selecting an optimal value series analysis method includes determining parameter values for the optimal value series analysis method, and presenting the selected optimal value series analysis method and parameters, and the optimal reconstruction of the annotation sequences to the user.

Automatic tuning of value-series analysis tasks based on visual feedback

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Hopewell Junction, NY, United States of America

Olivier Verscheure