Abstract: The invention relates to a system (300) and method for performing end-to-end simulation and testing of an IoT application (102). An IoT data simulator (310) is configured to simulate an IoT environment using data received from different components in the IoT environment, which include IoT messages/data from IoT devices (106), master data from different databases (108) and data from third-party web services (110). Device templates are created that are used as blueprint for defining a plurality of device instances which include simulated device instances and live device instances. An IoT application validator (326) is configured for testing and validating the IoT application (102) by transmitting a plurality of IoT messages to the IoT application (102) and validating the behavior of the IoT application (102) to the plurality of IoT messages for all layers including, but not limited to, a UI layer (112), a business logic (114) and a data layer (116), using one or more device instances.

Abstract: The invention relates to a system (300) and method for performing end-to-end simulation and testing of an IoT application (102). An IoT data simulator (310) is configured to simulate an IoT environment using data received from different components in the IoT environment, which include IoT messages/data from IoT devices (106), master data from different databases (108) and data from third-party web services (110). Device templates are created that are used as blueprint for defining a plurality of device instances which include simulated device instances and live device instances. An IoT application validator (326) is configured for testing and validating the IoT application (102) by transmitting a plurality of IoT messages to the IoT application (102) and validating the behavior of the IoT application (102) to the plurality of IoT messages for all layers including, but not limited to, a UI layer (112), a business logic (114) and a data layer (116), using one or more device instances.

Abstract: The invention relates to a method and system for monitoring a plurality of critical assets (102a-102n) associated with a production/process management system using one or more edge devices (104a-104n). The one or more edge devices (104a-104n) track operations of the plurality of critical assets (102a-102n), which comprises obtaining consolidated information related to the operations of the plurality of critical assets (102a-102n). The one or more edge devices (104a-104n) then derive insights corresponding to the plurality of critical assets (102a-102n) based on the consolidated information using descriptive analytics and an AI/ML model (114) and derive a set of actionable insights to optimize the operations. The derived insights are then rendered in a real-time consolidated view, to enable a user to take immediate actions and decisions in relation to the plurality of critical assets (102a-102n).