Abstract: Methods and systems that allow a user to see the people or groups who have access to files that are maintained by a plurality of cloud content sharing services. In particular, the user may see what specific party has access to each particular file or directory, regardless of multiple cloud content sharing services involved. Moreover, a user interface and exposed application program interface allows the user to manipulate the permissions, e.g., granting access, to another person or group, to a file or directory. The user interface may also allow the user to terminate access to the file or directory for a person or group. The user's action to change a permission may be effected independently of the particular cloud content sharing service.

Abstract: Systems and methods for dynamically creating collaborative teams and managing collaborative work of a team are generally disclosed herein. One example embodiment includes the dynamic creation of a collaborative team by creating an association between team members via a managing module. The managing module may be capable of managing, among other things, team members on a team, tasks and goals of each member of the team, as well as documentation associated with the team. In some embodiments, the managing module may use a chat or messaging protocol to manage collaborative modifications to documents of the team.

Abstract: Techniques are disclosed herein for reconfiguring reprogrammable hardware in an autonomous vehicle system. According to an embodiment, an autonomous driving system includes sensors and a configurable circuit having physical logic units. The autonomous driving system aggregates data observed from each of the sensors. The autonomous driving system detects a trigger indicative of a defect in the configurable circuit. The defect is identified as a function of the aggregated data. The autonomous driving system performs, in response to the trigger, a reconfiguration action on the configurable circuit to repair the defect.

Abstract: Technologies for source degradation and auto-tuning of cameras are disclosed. In one embodiment, a system includes a compute node connected to one or more cameras. The cameras can monitor an environment, such as a manufacturing process in a factory. The compute node may use image processing, such as a machine-learning-based algorithm, to monitor processes. A system integrator may adjust parameters of the camera and/or the algorithm, such as focus, gain, contrast, white balance, etc. The compute node can monitor the system integrator and learn how to adjust parameters in order to improve key performance indicators (KPIs) of the monitored process. In a production environment, the compute node may then automatically adjust parameters of the camera and/or analysis algorithm based on the actions of the system integrator in order to improve performance of the analysis algorithm.

Abstract: Techniques are disclosed herein for providing guidance for autonomous vehicles in areas of low network connectivity, such as rural areas. According to an embodiment, a guidance system receives a request to exchange data with a vehicle within a specified radius thereof over a wireless connection (e.g., a radio frequency protocol-based connection). The data is stored by the guidance system and is indicative of navigation information within the specified radius. The guidance system transmits the stored data to the vehicle. The guidance system also receives, from the vehicle, data indicative of navigation information for a path previously passed by the vehicle.

Abstract: Embodiments of mechanisms for dynamic media content type streaming management for mobile devices are generally described herein. In some embodiments, the mobile device may receive selection input pertaining to generating output from a media file containing at least two of audio data, video data, and closed-captioning data, the selection input selecting at least one of audio, video, and closed-captioning to be output during play of the media content. In some embodiments, the mobile device may generate an audio output as a signal in response to the selection input including audio. In some embodiments, the mobile device may generate a video output as a signal in response to the selection input including video. In some embodiments, the mobile device may generate a closed-captioning output as a signal in response to selection input including closed-captioning.

Abstract: Various systems and methods for implementing a software defined industrial system are described herein. For example, an orchestrated system of distributed nodes may run an application, including modules implemented on the distributed nodes. In response to a node failing, a module may be redeployed to a replacement node. In an example, self-descriptive control applications and software modules are provided in the context of orchestratable distributed systems. The self-descriptive control applications may be executed by an orchestrator or like control device and use a module manifest to generate a control system application. For example, an edge control node of the industrial system may include a system on a chip including a microcontroller (MCU) to convert IO data. The system on a chip includes a central processing unit (CPU) in an initial inactive state, which may be changed to an activated state in response an activation signal.

Abstract: Technologies for monitoring vehicle traffic include a traffic analysis server that receives infrastructure data from infrastructure sensors positioned along a road segment of a road and vehicle data from one or more vehicles travelling along the road segment. The traffic analysis server determines whether anomalies are present in the traffic data through the road segment based on an expected traffic behavior for the road segment. The traffic analysis server determines the expected traffic behavior for the road segment in a particular time window based on a historical traffic pattern associated with the road segment, based on historical vehicle data and historical infrastructure data captured during a prior time window corresponding to the particular time window for that road segment. Other embodiments are described and claimed.

Abstract: Various systems and methods may be used to implement a software defined industrial system. For example, an orchestrated system of distributed nodes may run an application, including modules implemented on the distributed nodes. The orchestrated system may include an orchestration server, a first node executing a first module, and a second node executing a second module. In response to the second node failing, the second module may be redeployed to a replacement node (e.g., the first node or a different node). The replacement mode may be determined by the first node or another node, for example based on connections to or from the second node.

Abstract: System and techniques for cumulative learning robot execution plan generation are described herein. A first execution plan report based on execution of a first execution plan by a first robot may be received. Here, the first execution plan report includes a first metric for a first operation of the first execution plan. A second execution plan report based on execution of a second execution plan by a second robot may also be received that includes a second metric for a second operation of the second execution plan. Here, the second operation corresponds to the first operation. The first metric and the second metric are analyzed to determine that the second operation is an improvement to the first operation. Then, a modified first execution plan that replaces the first operation with the second operation may be transmitted to the first robot.

Abstract: Methods and systems that allow a user to see the people or groups who have access to files that are maintained by a plurality of cloud content sharing services. In particular, the user may see what specific party has access to each particular file or directory, regardless of multiple cloud content sharing services involved. Moreover, a user interface and exposed application program interface allows the user to manipulate the permissions, e.g., granting access, to another person or group, to a file or directory. The user interface may also allow the user to terminate access to the file or directory for a person or group. The user's action to change a permission may be effected independently of the particular cloud content sharing service.

Abstract: A mechanism is described for facilitating dynamic storage management for computing mobile devices according to one embodiment. A method of embodiments, as described herein, includes detecting context-aware data relating to a computing device and a user associated with the computing device, monitoring available space at a local storage of the computing device, and dynamically allocating portions of the space at the local storage based on the context-aware data and results of the monitoring of the space. The dynamic allocation may include providing a first portion of the space to a first content by moving a second content from the local storage to one or more remote storage devices.

Abstract: Embodiments of mechanisms for dynamic media content type streaming management for mobile devices are generally described herein. In some embodiments, the mobile device may receive selection input pertaining to generating output from a media file containing at least two of audio data, video data, and closed-captioning data, the selection input selecting at least one of audio, video, and closed-captioning to be output during play of the media content. In some embodiments, the mobile device may generate an audio output as a signal in response to the selection input including audio. In some embodiments, the mobile device may generate a video output as a signal in response to the selection input including video. In some embodiments, the mobile device may generate a closed-captioning output as a signal in response to selection input including closed-captioning.

Abstract: Systems and methods for dynamically creating collaborative teams and managing collaborative work of a team are generally disclosed herein. One example embodiment includes the dynamic creation of a collaborative team by creating an association between team members via a managing module. The managing module may be capable of managing, among other things, team members on a team, tasks and goals of each member of the team, as well as documentation associated with the team. In some embodiments, the managing module may use a chat or messaging protocol to manage collaborative modifications to documents of the team.

Abstract: According to one embodiment, an apparatus includes an interface to receive sensor data from a plurality of sensors of an autonomous vehicle. The apparatus also includes processing circuitry to apply a sensor abstraction process to the sensor data to produce abstracted scene data, and to use the abstracted scene data in a perception phase of a control process for the autonomous vehicle. The sensor abstraction process may include one or more of: applying a Sensor data response normalization process to the sensor data, applying a warp process to the sensor data, and applying a filtering process to the sensor data.

Abstract: Embodiments herein relate to recognition of an appliance state based on sensor data and determination of a response based at least in part on the appliance state. In various embodiments, an apparatus to recognize an appliance state may include a sensor data module to identify sensor data in one or more signals relating to data from one or more sensors associated with an appliance, an appliance state recognition module to determine an appliance state of the appliance based at least in part on the sensor data, a response module to determine a response based at least in part on the appliance state, and a transmission module to send the response to at least one of an appliance controller for the appliance or a presentation device. Other embodiments may be described and/or claimed.

Abstract: Various systems and methods for implementing a software defined industrial system are described herein. For example, an orchestrated system of distributed nodes may run an application, including modules implemented on the distributed nodes. In response to a node failing, a module may be redeployed to a replacement node. In an example, self-descriptive control applications and software modules are provided in the context of orchestratable distributed systems. The self-descriptive control applications may be executed by an orchestrator or like control device and use a module manifest to generate a control system application. For example, an edge control node of the industrial system may include a system on a chip including a microcontroller (MCU) to convert IO data. The system on a chip includes a central processing unit (CPU) in an initial inactive state, which may be changed to an activated state in response an activation signal.

Abstract: An apparatus comprising at least one interface to receive a signal identifying a second vehicle in proximity of a first vehicle; and processing circuitry to obtain a behavioral model associated with the second vehicle, wherein the behavioral model defines driving behavior of the second vehicle; use the behavioral model to predict actions of the second vehicle; and determine a path plan for the first vehicle based on the predicted actions of the second vehicle.

Abstract: An apparatus comprising at least one interface to receive sensor data from a plurality of sensors of a vehicle; and one or more processors to autonomously control driving of the vehicle according to a path plan based on the sensor data; determine that autonomous control of the vehicle should cease; send a handoff request to a remote computing system for the remote computing system to control driving of the vehicle remotely; receive driving instruction data from the remote computing system; and control driving of the vehicle based on instructions included in the driving instruction data.

Abstract: Sensor data is received from a plurality of sensors, where the plurality of sensors includes a first set of sensors and a second set of sensors, and at least a portion of the plurality of sensors are coupled to a vehicle. Control of the vehicle is automated based on at least a portion of the sensor data generated by the first set of sensors. Passenger attributes of one or more passengers within the autonomous vehicles are determined from sensor data generated by the second set of sensors. Attributes of the vehicle are modified based on the passenger attributes and the sensor data generated by the first set of sensors.