Abstract: A method and device for generating data services from heterogeneous systems is disclosed. The method includes generating an asset data model for a parent asset based on at least one data attribute associated with the parent asset. The method further includes populating the asset data model with at least one sub-asset associated with each of the at least one data attribute and at least one event associated with the at least one sub-asset and the at least one data attribute. The method includes creating a plurality of role hierarchies across multiple organizations associated with the parent asset. The method further includes associating a plurality of stakeholders with each of the plurality of role hierarchies. The method includes associating data contracts with each of the plurality of stakeholders and each of the at least one sub-asset based on the plurality of role hierarchies and the asset data model.

Abstract: A method and device for generating data services from heterogeneous systems is disclosed. The method includes generating an asset data model for a parent asset based on at least one data attribute associated with the parent asset. The method further includes populating the asset data model with at least one sub-asset associated with each of the at least one data attribute and at least one event associated with the at least one sub-asset and the at least one data attribute. The method includes creating a plurality of role hierarchies across multiple organizations associated with the parent asset. The method further includes associating a plurality of stakeholders with each of the plurality of role hierarchies. The method includes associating data contracts with each of the plurality of stakeholders and each of the at least one sub-asset based on the plurality of role hierarchies and the asset data model.

Abstract: A method and device for tracing issues in an end-to-end process is disclosed. The method includes identifying a plurality of stakeholders involved in the end-to-end process and a plurality of vectors associated with each of the plurality of stakeholders, determining a plurality of parameters associated with each of the plurality of vectors for each of the plurality of stakeholder, comparing values associated with each of the plurality of parameters with corresponding threshold values for each of the plurality of stakeholders, collating deviation information associated with at least one of the plurality of parameters based on the comparing on a distributed ledger network, evaluating a resultant product or service obtained after the end-to-end process based on predefined quality standards, and upon evaluating, tracing an issue and a location of the issue in the end-to end process using the deviation information collated on the distributed ledger network.

Abstract: The system may receive a group of project requirements from a client for development of a software application. The system may identify the client based on the received group of project requirements. The system may to determine, based on the group of project requirements of the client, a past project requirement submitted by the client or another client or created previously as a generic project requirement and corresponding to a first project requirement of the group of project requirements. The system may determine information created or used for the past project requirement. The system may create information for a second project requirement of the group of project requirements. The system may generate a prototype of the software application based on the information created or used for the past project requirement and the information created for the second project requirement. The system may output the prototype.

Abstract: Intelligent application back stack management may include generating a first back stack for activities of an application that have been executed by a device that executes the application. The first back stack may include a back stack size limit. A further back stack may be generated for selected ones of the activities of the application if a total number of the activities of the application and further activities of the application exceeds the back stack size limit. The first back stack may be an in-memory back stack for the device that executes the application, and the further back stack may include an external on-device back stack for the device that executes the application and/or a Cloud storage based back stack. Intelligent application back stack management may further include regenerating an activity of the selected ones of the activities that is pulled from the further back stack.

Abstract: Intelligent application back stack management may include generating a first back stack for activities of an application that have been executed by a device that executes the application. The first back stack may include a back stack size limit. A further back stack may be generated for selected ones of the activities of the application if a total number of the activities of the application and further activities of the application exceeds the back stack size limit. The first back stack may be an in-memory back stack for the device that executes the application, and the further back stack may include an external on-device back stack for the device that executes the application and/or a Cloud storage based back stack. Intelligent application back stack management may further include regenerating an activity of the selected ones of the activities that is pulled from the further back stack.

Abstract: The system may receive a group of project requirements from a client for development of a software application. The system may identify the client based on the received group of project requirements. The system may to determine, based on the group of project requirements of the client, a past project requirement submitted by the client or another client or created previously as a generic project requirement and corresponding to a first project requirement of the group of project requirements. The system may determine information created or used for the past project requirement. The system may create information for a second project requirement of the group of project requirements. The system may generate a prototype of the software application based on the information created or used for the past project requirement and the information created for the second project requirement. The system may output the prototype.

Abstract: Intelligent application back stack management may include generating a first back stack for activities of an application that have been executed by a device that executes the application. The first back stack may include a back stack size limit. A further back stack may be generated for selected ones of the activities of the application if a total number of the activities of the application and further activities of the application exceeds the back stack size limit. The first back stack may be an in-memory back stack for the device that executes the application, and the further back stack may include an external on-device back stack for the device that executes the application and/or a Cloud storage based back stack. Intelligent application back stack management may further include regenerating an activity of the selected ones of the activities that is pulled from the further back stack.

Abstract: Methods and systems for resource optimized, coarse and fine grained location tracking for planned journey are disclosed. A method for tracking a mobile device with respect to a point of interest (POI) using a mobile location tracker includes a conserve mode in which the mobile location tracker is turned off. The conserve mode comprises determining, by an analyzer module, whether to assess an estimated time to arrive (ETA) at the POI. If determined to assess the ETA, the conserve mode comprises performing an ETA assess operation comprising receiving the ETA; and if the ETA is not greater than a threshold time, switching from the conserve mode to an active mode, wherein in the active mode the mobile location tracker is turned on. It is determined to assess the ETA if a timer measurement is not less than the reassess time or if a trigger to reassess is received.

Abstract: Intelligent application back stack management may include generating a first back stack for activities of an application that have been executed by a device that executes the application. The first back stack may include a back stack size limit. A further back stack may be generated for selected ones of the activities of the application if a total number of the activities of the application and further activities of the application exceeds the back stack size limit. The first back stack may be an in-memory back stack for the device that executes the application, and the further back stack may include an external on-device back stack for the device that executes the application and/or a Cloud storage based back stack. Intelligent application back stack management may further include regenerating an activity of the selected ones of the activities that is pulled from the further back stack.

Abstract: Methods and systems for resource optimized, coarse and fine grained location tracking for planned journey are disclosed. A method for tracking a mobile device with respect to a point of interest (POI) using a mobile location tracker includes a conserve mode in which the mobile location tracker is turned off. The conserve mode comprises determining, by an analyzer module, whether to assess an estimated time to arrive (ETA) at the POI. If determined to assess the ETA, the conserve mode comprises performing an ETA assess operation comprising receiving the ETA; and if the ETA is not greater than a threshold time, switching from the conserve mode to an active mode, wherein in the active mode the mobile location tracker is turned on. It is determined to assess the ETA if a timer measurement is not less than the reassess time or if a trigger to reassess is received.