The Toronto-dominion Bank

Salvatore Aspro

Masashi Kobayashi

Jinoj Titus

Thomas M Kerigan

Mok Choe

George Wright

Evgenia Syromyatnikova

A processor-implemented method is disclosed. The method includes: obtaining sensor readings from a plurality of sensors associated with a plurality of homes; receiving, from a computing device associated with a first one of the plurality of homes, a request for a live home score; determining, based on first sensor readings for at least one sensor associated with the first one of the plurality of homes and second sensor readings from corresponding sensors associated with at least a second one of the plurality of homes, a live home score for the first one of the plurality of homes; and sending the live home score to the computing device associated with the first one of the plurality of homes.

Integrated home scoring system

A processor-implemented method is disclosed. The method includes: obtaining sensor readings from sensors associated with a first home and a plurality of second homes; determining a set of prioritized maintenance items for the first home based on comparing sensor readings from sensors associated with the plurality of second homes to identify and rank maintenance items; detecting one or more maintenance events associated with one or more of the set of the prioritized maintenance items for the first home; and outputting a live home score for the first home based on detecting the one or more maintenance events.

An API generation system can be used to generate complete (or almost complete) APIs in response to received requests for new or modified APIs. Received API generation requests can include API descriptive data which is augmented to generate a set of data requirements defining one or more inputs and outputs for the API. The API functions can be mapped to one of a set of reference data models defining data types as used by the backend system, and the mappings used to automatically generate an API design defining input and output parameters for each API function of the requested API. The API generation system then assembles a code foundation for the requested API based on a set of software components implementing a portion of the API function and generates API source code based on the code foundation to complete the requested API.

Automated API code generation

To automatically generate a project document, a server in a computing environment receives input documents associated with a project, and extracts a set of features from each input document. The server determines a frequency of the words in each input document and stores the frequencies in relation to the words in the sets of words. The server than applies a document type machine-learned model to a set of words for each input document to infer a document type. The document machine-learned model may be trained using a bag-of-words representation. The server then applies a architecture pattern machine-learned model the set of input documents to determine a target architecture pattern. The server automatically generates a project document for the project based on the document types and inferred architecture pattern.

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Vaughan, Canada

Salvatore Aspro