Abstract: Embodiments herein disclose methods and systems for identifying behavioural trends across users. The system includes electronic devices. The electronic devices include a behavioural recommendation controller. The behavioural recommendation controller is configured to: detect a first plurality of activities performed by a plurality of first users in relation with a plurality of contexts; recognize the first plurality of physical activities in relation with the plurality of contexts for the first user; recognize multiple activities performed using smart devices by the first user during each first physical activity in each context; and recognize a second plurality of physical activities performed by multiple concurrent second users during each context to refer current behavior or new behavior of the users.

Abstract: A method and system for learning universal vector representation of concepts in a distributed environment comprising a plurality of edge devices are provided. The method includes obtaining data from one or more sources available at the candidate edge device, determining a plurality of concepts from the obtained data, training on-device artificial intelligence (AI) model locally available at the candidate edge device using the plurality of concepts. The method also includes transmitting the at least one trained on-device AI model to a server and receiving a global AI model for deployment from the server. The method further includes deploying the global AI model for universal vector representation of concepts in the candidate edge device.