Abstract: Aspects of the present invention provide a software defined radio (SDR) system and/or an approach for enabling heterogeneous device communications using a SDR device in an internet of things (IoT) environment. In an embodiment, the SDR device (e.g., a network adapter thereof) obtains a set of communications sent by an IoT device. Based on an analysis of the set of communications by an SDR bot running on the SDR device, a protocol of the set of communications is determined. The SDR bot interprets a communication of the set of communications, and, based on the interpreted communication, a notification is forwarded by the SDR device (e.g., by the network adapter). This notification can include an instruction to another IoT device to perform a task, a report based on communications from multiple IoT devices, or the like.

Abstract: Generating a risk and constraint labeled context map of an operational space is provided. The risk and constraint labeled context map of the operational space corresponding to a user of a cognitive suit is generated to drive the cognitive suit contextually using three-dimension reconstruction, virtual reality, and semi-supervised learning. Labeled risks and constraints in the risk and constraint labeled context map are associated with cognitive suit actuation events to deploy a set of mitigation strategies to address the labeled risks and constraints. An apparatus embedded in the cognitive suit is actuated to deploy the set of mitigation strategies in response to sensing a labeled risk or labeled constraint proximate to the user along a trajectory of the user in the operational space.

Abstract: A method for placing a linked hyper-video within a hyper-video. The method includes identifying one or more points of interest in the hyper-video, detecting one or more features of the hyper-video, extracting at least one of the one or more features, and displaying the linked hyper-video, within the hyper-video, based on the one or more identified points of interest and based on the extracted at least one of the one or more features. The method further includes extracting one or more features from the hyper-video that depict one or more viewing characteristics of a user. The method includes analyzing the one or more features from the hyper-video to identify a low-saliency area of the hyper-video, a low-frequency region within the low-saliency area, and a homogenous sub-region within the low-frequency region. The method further includes placing a linked hyper-video at the homogenous sub-region within the low-frequency region of the hyper video.