Abstract: An application development system for development of Internet of Things (IoT) application includes a cataloging module to obtain an input from an application developer. The input comprises data related to the IoT application to be developed. The cataloging module further retrieves a plurality of reusable artefacts from a knowledge database based on the input. A recommendation module in the application development system recommends, to the application developer, artefacts from amongst the plurality of reusable artefacts, based at least on one of a feedback associated with each of the plurality of reusable artefacts, an expert analysis, and a combination of the expert analysis and the feedback. An association module in the application development system associates artefacts selected by the application developer with each other for development of the IoT application.

Abstract: A system and method for generating a plan to complete a task by providing a framework facilitating use of heterogeneous data sources without altering a planning algorithm are disclosed. The method includes using a first dataset of logical atoms represented in predicate schema and second dataset of database atoms represented in non-predicate schema, and modifying a grammar rule, a domain definition, and a problem definition, and selecting and executing task methods and task operators to complete a task. Execution of task operator includes verifying a precondition, assigning variables with values when the precondition is valid, and modifying (delete and add) a plan state. Execution of the task method includes verifying a precondition of the task method, assigning variables with values when the precondition is valid, decomposing the task into sub-tasks, assigning arguments of task method to sub-tasks, and adding sub-tasks to a task list. Thereafter, a plan is generated.

Abstract: A system and method for generating a plan to complete a task by providing a framework facilitating use of heterogeneous data sources without altering a planning algorithm are disclosed. The method includes using a first dataset of logical atoms represented in predicate schema and second dataset of database atoms represented in non-predicate schema, and modifying a grammar rule, a domain definition, and a problem definition, and selecting and executing task methods and task operators to complete a task. Execution of task operator includes verifying a precondition, assigning variables with values when the precondition is valid, and modifying (delete and add) a plan state. Execution of the task method includes verifying a precondition of the task method, assigning variables with values when the precondition is valid, decomposing the task into sub-tasks, assigning arguments of task method to sub-tasks, and adding sub-tasks to a task list. Thereafter, a plan is generated.

Abstract: An application development system for development of Internet of Things (IoT) application includes a cataloging module to obtain an input from an application developer. The input comprises data related to the IoT application to be developed. The cataloging module further retrieves a plurality of reusable artefacts from a knowledge database based on the input. A recommendation module in the application development system recommends, to the application developer, artefacts from amongst the plurality of reusable artefacts, based at least on one of a feedback associated with each of the plurality of reusable artefacts, an expert analysis, and a combination of the expert analysis and the feedback. An association module in the application development system associates artefacts selected by the application developer with each other for development of the IoT application.

Abstract: The present invention envisages a personalized plan generation system and a method that satisfies maximum user preferences and constraints; besides including a number of enabling features like of plan repair or revision with dynamically changing situations or contextual information. Moreover, the system is able to perform a collaborative planning by opinion mining in social networks to achieve better optimization. Significantly, the explanation for the selection of plan steps or a change in plan altogether can be expressed in natural language.