Abstract: A device determines the positioning of objects in a scene by implementing a robust and deterministic method. The device obtains object detection data (ODD) which identifies the objects and locations of reference points of the objects in views of the scene. The obtained ODD is processed to identify a first image object of a first view as a mirror reflection of a real object. A virtual view associated with a virtual camera position is created, including the ODD associated with the first image object of the first view. The ODD associated with the first image object is removed from the first view. Based on the ODD associated with at least said virtual view and a further view of the one or more views, a position of said first image object is computed.

Abstract: An electronic device includes a memory circuitry, an interface circuitry, a sensor circuitry, and a processor circuitry having a predictor circuitry configured to operate according to a prediction model. The processor circuitry is configured to obtain sensor data. The processor circuitry is configured to determine, based on the sensor data, using the predictor circuitry, a predicted time parameter indicative of a prediction of a time slot to initiate an establishment of a network with one or more other electronic devices. The processor circuitry is configured to initiate the establishment of the network with the one or more other electronic devices according to the predicted time parameter.

Abstract: A control system in a delivery system performs a method of controlling unmanned aerial vehicles, UAVs, which are organized in a group or swarm to perform one or more missions to deliver and/or pick up goods. The method includes obtaining drag data indicative of air resistance for one or more UAVs in the group, determining, as a function of the drag data, a respective relative position of at least the one or more UAVs within the group, and controlling at least the one or more UAVs to attain the respective relative position. Such adjustment in the relative position of one or more UAVs enables improved energy efficiency and may be made to reduce energy consumption, increase reach or decrease travel time of at least one UAV in the group.

Abstract: A control system in a delivery system performs a method to deliver a payload by an unmanned aerial vehicle, UAV, without requiring presence of the recipient even if the payload comprises sensitive or vulnerable goods. The method comprises obtaining a designated location for delivery of the payload, obtaining at least one payload vulnerability index for the payload, and obtaining a pick-up time indicative of a time point when the payload is expected to be retrieved by the recipient. The method further comprises selecting a final delivery area at or near the designated location as a function of the at least one payload vulnerability index and the pick-up time, and operating the UAV to deliver the payload to the final delivery area.

Abstract: A scheduling device performs a method of scheduling transports by a fleet of unmanned aerial vehicles, UAVs, to enable improved utilization of the fleet. The method includes computing, for the fleet, aggregated cost data, ACM, that associates utilization cost with distributed sub-regions within a geographic region, the utilization cost of a respective sub-region representing an estimated cost for directing at least one of the UAVs to the respective sub-region. The method further includes receiving a query indicative of one or more potential locations for pick-up or delivery of a payload, determining, based on the ACM, a transportation price for at least one potential location, and presenting the transportation price for the at least one potential location. The scheduling device thereby provides an interactive ordering system that enables utilization of the fleet to be automatically optimized by swarm intelligence.

Abstract: A coordinator electronic device includes a memory circuitry, a processor circuitry, and an interface circuitry. The processor circuitry is configured to obtain sensor data from a first sensor device. The processor circuitry is configured to provide to the first sensor device, based on the sensor data obtained, a first configuration parameter indicative of scheduling of reporting from the first sensor device.

Abstract: Based on control data (1002) indicative of a user engagement in a mobile edge application (1001) which is being executed on a source mobile edge server (201-203) of a mobile edge system (200) and on a terminal (130), relocation of the mobile edge application (1001) from the source mobile edge server (201-203) to a target mobile edge server (201-203) is facilitated.

Abstract: A portable electronic device comprises at least one sensor configured to sense sensor data, including at least one first sensor data representing a first sensed condition. The portable electronic device comprises a processor configured to create a learned sensor data pattern and create a learning function. The processor is also configured to obtain the first sensor data, estimate using the learning function a first estimated transmission cost associated with an upcoming data transmission when the device experiences the first sensed condition, predict using the learned sensor data pattern an upcoming second sensor data representing a predicted second sensed condition, and estimate using the learning function a second estimated transmission cost associated with the upcoming data transmission when the device experiences the predicted second sensed condition. The processor is configured to compare the first estimated transmission cost with the second estimated transmission cost.

Abstract: A method (10) is provided for providing location information of a group of mobile devices (20A-20C) of a wireless network (21-23) to a network node (40) of the wireless network (21-23), the method (10) comprising: repetitively transmitting, by at least one mobile device (20A-20C) of the group of mobile devices (20A-20C), a location information (11, 11 A) of the respective mobile device (20A-20C) at a respective reporting frequency (fA-fC), which depends on an energy balance of the respective mobile device (20A-20C). A corresponding method (30) of operating a network node (40), a mobile device (20A-20C) and a network node (40) are also provided.

Abstract: A service provided by a mobile edge server is relocated. A base station associated with the mobile edge server sends a control message to a mobile edge system, the control message being indicative of a predicted handover of the terminal from the base station to one or more candidate base stations.

Abstract: A method for distributed computation in a hierarchical system having a compute deployment including a plurality of compute nodes, comprising providing a control function communicatively connected to said compute nodes; determining a cost function for the system, which cost function includes at least one first parameter associated with carrying out a compute task and at least one second parameter associated with escalating a compute task; employing a machine learning mechanism in the control function to optimize said cost function; and configuring said compute deployment based on the optimization of the cost function by the machine learning mechanism.

Abstract: Methods (10A; 10B) for grouping of mobile devices are provided. A method (10B) comprises receiving (15B), from each mobile device (40A-40C) of a plurality of mobile devices (40A-40C), control data (30A, 30B) indicative of at least one anomaly detected in a time series of measurement values of a physical observable monitored by a sensor (43) of the respective mobile device (40A-40C); determining (17), based on a comparison of anomalies indicated by the control data (30A, 30B) from the plurality of mobile devices (40A-40C), an assignment of the plurality of mobile devices (40A-40C) into at least one location sensing group; and implementing (20B) group sensor reporting in accordance with the at least one location sensing group.

Abstract: A method for monitoring a primary variable is carried out in a device having access to a set of sensors. The method includes the steps of receiving, from a network service, a series of forecasted values for the primary variable, each forecasted value being associated with one of a series of future time points; for at least one of the future time points, predicting a value for the primary variable using data of at least one secondary variable captured by a subset of the set of sensors, comparing the predicted value to the forecasted value associated with the future time point, and switching to a different subset of the set of sensors, if the predicted value deviates from the forecasted value with more than a specified threshold value.

Abstract: A method for generating a profile for a user based on the user's behaviour and altering a setup of at least one computer program based on the generated user profile. The generic user profile for a user may be updated to include information from a similar user (e.g., a user having similar preferences). Using information from similar users allows for a generic user profile to be generated using information extracted from applications (e.g., both social media and games) and/or based on the behaviour of connections (e.g., social media contact, etc.). The generated generic user profile may be used to change the set-up for applications (e.g., executed/stored on the user's mobile device).

Abstract: A method for controlling relocation of a session of an application hosted in a first server (220) connected to a radio station (301) configured for communication with wireless devices (303), comprising the steps of running (51) a session of the application between an application host in said server and an application client in a first wireless device; obtaining (53) context data in the server, which context data is related to the first wireless device during said session; providing (55) said context data to a management entity configured to control relocation of said session from the first server to a second server.

Abstract: A method for controlling a session of an application executed by a User Equipment (UE) (303), using an Edge Computing (EC) management entity (300) configured to manage EC servers (220, 520) comprising compute resources, said EC management entity obtaining (703) server information including mobility information related to a first movable EC server (520); managing a connection between the UE and the first movable EC server based on the received mobility information.

Abstract: A system for distribution of goods, comprising a plurality of returnable product carriers (150) and a return station (405). Each product carrier (150) comprises a carrier member (151) for holding goods, and a wireless communications device (100) connected to the carrier member. The wireless communications device comprises an M2M radio device (110) including a radio transceiver (111) configured to communicate with a network (1); a control unit (113) connected to the transceiver; a sensor (116) connected to the control unit, configured to sense a parameter; and a short range wireless transceiver (117) configured to emit a presence signal responsive to the sensor sensing a predetermined parameter characteristic. The return station includes a triggering device (502) configured to subject the product carriers to said predetermined parameter characteristic; and a detector device (503) configured to detect a presence signal emitted from a proximate product carrier.

Abstract: A wireless communications device (100) comprising a machine-to-machine radio device (110) including a radio transceiver (111) configured to communicate with a network (1), and a control unit (113) connected to control the transceiver; a boot system (120) for the machine-to-machine radio device; and a reset mechanism (130) including a reset signal transceiver (131), and a reset controller (132) connected to the reset signal transceiver and connected to the boot system to request reboot of the machine-to-machine radio device responsive to a received reset signal.

Abstract: A method and a corresponding first device for computing estimation output data. The method includes obtaining first sensor data; computing a first estimation score based on said first sensor data, using a first estimation model; transmitting said first sensor data or a computation request to a second device; receiving a second estimation score based on said first sensor data or second sensor data obtained from a second sensor, computed using a second estimation model in the second device; and dependent on the first estimation score and the received second estimation score, determining estimation output data.

Abstract: Based on control data (1002) indicative of a user engagement in a mobile edge application (1001) which is being executed on a source mobile edge server (201-203) of a mobile edge system (200) and on a terminal (130), relocation of the mobile edge application (1001) from the source mobile edge server (201-203) to a target mobile edge server (201-203) is facilitated.