Abstract: Provided is a process including: writing classes using object-oriented modelling of modeling topics; scanning the classes to determine class definition information; receiving from a subscribing modeling object a request for a subscription to a given modeling topic in a given modeling topic class, the subscription request including a modeling topic filter to select the given modeling topic from a plurality of modeling topics described by the given modeling topic class; registering a modeling topic accessor associated with the subscribing modeling object and a modeling topic mutator associated with the subscribing modeling object; processing, through the modeling topic filter a modeling topic that is accessed through an accessor and is described by the modeling topic class, the modeling topic being received from a modeling publisher object; notifying the subscribing object of the received modeling topic through a registered modeling topic listener; and mutating the received modeling topic.

Abstract: The present application is at least directed to a method of dynamically managing content delivery of sensor data to a third party. A step of the method may include receiving, via plural smart devices each including a trained machine learning algorithm, data of an object detected in an environment and filtered to remove an attribute of the detected object. Another step of the method may include aggregating the filtered data with the removed attribute received from the plural devices. Yet another step of the method may include obtaining a credential of a third party requesting the aggregated data of the object. Yet even another step of the method may include determining, via another trained machine learning algorithm, an additional filter of the aggregated data is required in view of the credential of the third party. A further step of the method may include transmitting, to the third party, the additionally filtered data in view of the credential.

Abstract: Provided is a process including: searching code of a machine-learning pipeline to find a first and a second object code sequences performing similar tasks; modifying the code of the machine learning pipeline by inserting a third object code sequence into the code of the machine learning pipeline, the third code sequence being operable to pass control to the first object code sequence; inserting a branch at the end of the first code sequence, the branch being operable to: pass control, upon detection of a first predefined condition, to an instruction following the first object code sequence, and to pass control, upon detection of a second predefined condition, to an instruction following the third object code sequence; and wherein the third code sequence is executed in place of the second object sequence without affecting completion of the tasks.

Abstract: Provided is a process including: obtaining, for a plurality of entities, datasets; and orchestrating an object-orientated application or service by: forming a plurality of objects, forming object-oriented labeled datasets based on an event and the attributes of each of the datasets; forming a library or framework of classes with a plurality of object-orientation modelors; and forming a plurality of object-manipulation functions, each function being configured to leverage a respective class among the library or framework of classes.

Abstract: Provided is a process including: writing classes using object-oriented modelling of modeling topics; scanning the classes to determine class definition information; receiving from a subscribing modeling object a request for a subscription to a given modeling topic in a given modeling topic class, the subscription request including a modeling topic filter to select the given modeling topic from a plurality of modeling topics described by the given modeling topic class; registering a modeling topic accessor associated with the subscribing modeling object and a modeling topic mutator associated with the subscribing modeling object; processing, through the modeling topic filter a modeling topic that is accessed through an accessor and is described by the modeling topic class, the modeling topic being received from a modeling publisher object; notifying the subscribing object of the received modeling topic through a registered modeling topic listener; and mutating the received modeling topic.