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 performs a method for configuring a delivery system that includes first storages with predefined positions, second storages with variable positions, and unmanned aerial vehicles which are operable to transport goods between destination points and the first and second storages. The method includes obtaining position data for the destination points, operating a clustering algorithm on the position data to determine clusters of destination points, and evaluating the clusters in relation to the predefined positions of the first storages to determine a set of stopping positions for at least one of the second storages. The stopping position(s) may thereby be adapted in a resource efficient way to improve the overall capabilities of the delivery system.

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: A method for controlling upload of data, performed in an electronic device (100), wherein said electronic device is configured to intermittently upload data (520) to a wireless network to operate as a tracker, said method comprising: obtaining (500) a current position of the electronic device, determining, dependent on network coverage associated with said position, to either upload data (530) to the network or postpone (430) upload of data.

Abstract: An electronic device includes a memory circuitry, an interface circuitry, a processor circuitry having a controller circuitry, and an inference circuitry configured to operate according to a first inference model of a plurality of inference models. The processor circuitry is configured to obtain first primary detection data from a detection circuitry. The processor circuitry is configured to obtain one or more criteria. The processor circuitry is configured to obtain, from the inference circuitry, a first primary probability associated with the first primary detection data, based on the first inference model. The processor circuitry is configured to generate a first set, based on the one or more criteria, by determining whether the first primary probability associated with the first primary detection data satisfies at least one of the one or more criteria.

Abstract: A tag (10) is configured to be attached to an object (12). The tag includes a sensor (24) configured to generate data indicative of movement of the tag in three dimensions. A control circuit (14) of the tag is configured to determine an amount of change in orientation of the tag over a predetermined period of time based on the data indicative of movement of the tag in three dimensions generated by the sensor; and to determine that the amount of change in orientation indicates that the tag is in one of an attached state relative to the object or is in a detached state relative to the object. A signal may be transmitted to a host computing device (28) if it is determined that the tag has become detached from the object.

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 monitoring system detects and mitigates traffic risks among a group of vehicles. The group of vehicles includes a ground-based vehicle (GBV), e.g. an automotive vehicle, and an air-based vehicle (ABV), e.g. a drone, which is operated to track a ground-based object (GBO), e.g. an unprotected road user or an animal. The monitoring system performs a method comprising: obtaining (301) predicted navigation data for the ground-based vehicle and the air-based vehicle, processing (302) the predicted navigation data to obtain one or more future locations of the ground based-object and to detect an upcoming spatial proximity between the ground-based object and the ground-based vehicle, and causing (305), upon detection of the upcoming spatial proximity, an alert signal to be provided to at least one of the ground-based object and the ground-based vehicle.

Abstract: Drones are controlled by one or more control devices and comprise a respective camera for image capture. The one or more control devices perform a method including obtaining projected flight paths of the drones, obtaining a projected camera setting of the respective camera, computing, as a function of the projected camera setting, a projected viewing frustum of the respective camera, defining, for the drones, projected time-space trajectories of no-fly zones based on the projected viewing frustum of the respective camera, analyzing the projected flight paths of the drones in relation to the projected time-space trajectories for detection of a violation of one or more of the no-fly zones, and setting an operative flight path and/or an operative camera setting for at least one selected drone to prevent the violation.

Abstract: A control device operates a drone with an onboard camera. The control device obtains a current performance metric to be computed for an activity performed by an individual, determines, based on a positioning rule associated with the current performance metric, a selected relative position, SRP, between the individual and the onboard camera, identifies a reference plane of the individual, operates the drone to move the onboard camera from an initial relative position to attain the SRP in relation to the reference plane; operates the onboard camera, when in the SRP, to capture image(s) of the individual, and provides the image(s) for computation of the current performance metric for the activity performed by the individual. The SRP may be defined, by the positioning rule, to ensure that the orientation of the individual in the image(s) is relevant or optimal for the current performance metric.

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: The present disclosure provides a method, performed at an electronic device, for determining a geofence parameter of a geofence area related to a point of interest, POI. The method comprises obtaining a location of the POI, obtaining first POI data based on the location of the POI. The method may comprise determining, based on the location of the POI, one or more entities in proximity of the POI. The method comprises obtaining second POI data related to at least one entity of the one or more entities. The method comprises generating a set of enclosing features related to the POI based on the second POI data, wherein generating the set of enclosing features comprises applying a processing scheme to the second POI data; and determining a geofence parameter based on the first POI data and the set of enclosing features.

Abstract: Provided are devices, methods, and computer readable products for adjusting an estimated time of arrival for an object to arrive at a destination. Example aspects provide a method that includes determining the object is at an intermediate waypoint; determining place data related to a place that is proximate to the intermediate waypoint; calculating an adjustment based on the place data related to the place that is proximate to the intermediate waypoint; and adjusting the estimated time of arrival for the object based on the adjustment.

Abstract: A method for tracking an object in a transportation system is described. The method includes determining, at a first time, a first location of the object based on a positioning system. A first area includes the first location. The method includes determining, based on a movement sensor, that the object is moving. The movement sensor determines that the object is moving at a second time that is after the first time. The method includes determining, at a third time that is after the second time, based on the positioning system, a second location of the object, and setting the moving time of the object to be the second time, responsive to determining that the object has moved to the second location that is in a second area that is different from the first area. Related systems, devices and computer program products are also described.