Abstract: A dispatcher virtual assistant (DVA) that can augment the capability of emergency dispatchers while reducing human errors. Major functions of the DVA include updating an emergency incident's status in real time, recommending or reminding the dispatcher to take proper actions at the right timing, answering the dispatcher's inquiries for task-related information, and fulfilling the dispatcher's request for an incident report. The DVA system includes a dispatcher language model based on machine-learning and deep-learning algorithms, for extracting the status of a live incident from incoming incident logs, and for processing and answering inquiries or requests from the dispatcher. It is customizable for different types of emergencies and for different local communities. The DVA can be used in tandem with an existing CAD system.

Abstract: Systems and methods of instant-messaging bot for robotic process automation (RPA) and robotic textual-content extraction from digital images include a chatbot application, a software RPA manager, and an instant-messaging (IM) platform, all built for an enterprise. The enterprise IM platform is connected to one or more public IM platforms over the Internet. The RPA manager contains multiple modules of enterprise workflows and receives instructions from the enterprise chatbot for executing individual workflows. The system allows enterprise users connected to the enterprise IM platform, and external users connected to the public IM platforms, to use instant messaging to initiate enterprise workflows that are automated with the help of the enterprise chatbot and delivered via instant messaging. Furthermore, textual-content extraction from digital images is incorporated in the RPA manager as an enterprise workflow, and provides improved convolutional neural network (CNN) methods for textual-content extraction.

Abstract: A dispatcher virtual assistant (DVA) that can augment the capability of emergency dispatchers while reducing human errors. Major functions of the DVA include updating an emergency incident's status in real time, recommending or reminding the dispatcher to take proper actions at the right timing, answering the dispatcher's inquiries for task-related information, and fulfilling the dispatcher's request for an incident report. The DVA system includes a dispatcher language model based on machine-learning and deep-learning algorithms, for extracting the status of a live incident from incoming incident logs, and for processing and answering inquiries or requests from the dispatcher. It is customizable for different types of emergencies and for different local communities. The DVA can be used in tandem with an existing CAD system.

Abstract: A system and method of instant-messaging bot that provide a chatbot and human agents working in accord in communicating with users over a public instant-messaging (IM) platform includes a chatbot application and an IM platform, both built for an enterprise. The enterprise IM platform is connected to the chatbot application and separately connected to one or more public IM platforms via the Internet. The chatbot application contains software for receiving, processing, analyzing and responding to human-generated messages in a human-like manner. The enterprise IM platform contains software for managing traffic of IM messages exchanged among the chatbot, one or more human agents connected to the enterprise IM platform, and any user connected to one of the public IM platforms.

Abstract: Systems and methods of instant-messaging bot for robotic process automation (RPA) and robotic textual-content extraction from digital images include a chatbot application, a software RPA manager, and an instant-messaging (IM) platform, all built for an enterprise. The enterprise IM platform is connected to one or more public IM platforms over the Internet. The RPA manager contains multiple modules of enterprise workflows and receives instructions from the enterprise chatbot for executing individual workflows. The system allows enterprise users connected to the enterprise IM platform, and external users connected to the public IM platforms, to use instant messaging to initiate enterprise workflows that are automated with the help of the enterprise chatbot and delivered via instant messaging. Furthermore, textual-content extraction from digital images is incorporated in the RPA manager as an enterprise workflow, and provides improved convolutional neural network (CNN) methods for textual-content extraction.

Abstract: A system and method of instant-messaging bot that provide a chatbot and human agents working in accord in communicating with users over a public instant-messaging (IM) platform includes a chatbot application and an IM platform, both built for an enterprise. The enterprise IM platform is connected to the chatbot application and separately connected to one or more public IM platforms via the Internet. The chatbot application contains software for receiving, processing, analyzing and responding to human-generated messages in a human-like manner. The enterprise IM platform contains software for managing traffic of IM messages exchanged among the chatbot, one or more human agents connected to the enterprise IM platform, and any user connected to one of the public IM platforms.

Abstract: A server and a number of client devices are connected via a network. Interactive objects are initiated in one of the client devices and delivered to any number of other client devices over the network. Real-time interactions between the object sender and the object receiver(s) can then be engaged using event-triggering mechanisms built into the client devices and applied onto the objects, and be coordinated by a coordinating module in the server. The interactive objects may carry instructions for event-triggered loading, activating and execution of functional widgets, such as workflows or collaborations, stored in the same server or elsewhere on the network. Once loaded in a client device, a widget needs not to be reloaded upon further use. Furthermore, the coordinating module may be linked to a machine-learning module in the same server or elsewhere on the network.

Abstract: This invention provides programmable intelligent agents that facilitate and manage voice or video conversations between human users and chatbots over the Internet or the Public Switched Telephone Network. Functions of said intelligent agents include providing the communication connectivity, coordinating the human-chatbot conversation, reacting and responding to the human user's conversational behavior, and in certain applications, sending controlling signals to peripheral devices according to intents of the conversation, or receiving data from peripheral sensors as references to alter the course of the conversation. Furthermore, a said intelligent agent can serve as a user interface that enables human users in the vicinity of the intelligent agent to engage in an interactive three-way conversation with a chatbot and remote human users.

Abstract: A server and a number of client devices are connected via a network. Interactive objects are initiated in one of the client devices and delivered to any number of other client devices over the network. Real-time interactions between the object sender and the object receiver(s) can then be engaged using event-triggering mechanisms built into the client devices and applied onto the objects, and be coordinated by a coordinating module in the server. The interactive objects may carry instructions for event-triggered loading, activating and execution of functional widgets, such as workflows or collaborations, stored in the same server or elsewhere on the network. Once loaded in a client device, a widget needs not to be reloaded upon further use. Furthermore, the coordinating module may be linked to a machine-learning module in the same server or elsewhere on the network.