Aspects of the subject disclosure may include, for example, wirelessly receiving test signals when an unmanned aircraft is at different positions in proximity to a transmission medium where the first group of test signals is transmitted from different locations, determining RF parameters associated with each of the test signals, and generating placement information indicative of a target location for a communication device to be positioned, where the placement information is generated based on the RF parameters. Other embodiments are disclosed.

An example UAV landing structure includes a landing platform for a UAV, a cavity within the landing platform, and a track that runs along the landing platform and at least a part of the cavity. The UAV may include a winch system that includes a tether that may be coupled to a payload. Furthermore, the cavity may be aligned over a predetermined target location. The cavity may be sized to allow the winch system to pass a tethered payload through the cavity. The track may guide the UAV to a docked position over the cavity as the UAV moves along the landing platform. When the UAV is in the docked position, a payload may be loaded to or unloaded from the UAV through the cavity.

Methods, systems, and apparatus, including computer programs encoded on a storage device, for using a drone to identify a wireless network problem and initiate performance of one or more operations or actions that address the wireless network problem, the drone comprising a processor and a storage device, the storage device storing instructions that, when executed by the processor, cause the processor to perform operations comprising receiving, by the drone, an instruction to analyze a wireless network of a property, responsive to the instruction to analyze the wireless network, traveling, by the drone, to one or more zones of the property, determining, by the drone and based on an analysis of one or more characteristics of the wireless network, that a wireless network problem exists, and based on the determination that the wireless network problem exists, performing, by the drone, one or more operations directed to addressing the wireless network problem.

An approach for determining an infrastructure service interruption is disclosed. The approach relies on utilizing UAVs (unmanned aerial vehicle) to map electronic signals (e.g., Wi-Fi, etc.) that emanates from building structures (e.g., residential, commercial, etc.). Electronic signals having a certain frequency or multiple frequencies may be used. Essentially, the approach can detect power/signal loss by comparing differences in Wi-Fi signal maps pre and post event (e.g., severe thunderstorm, etc.). The 24/7 event monitoring is carried out by using UAVs and the UAVs can operate on a regular or event driven schedule vs. continuously operating multiple fixed data collection units.

Methods and apparatus are disclosed for vehicle navigation with water depth detection. An example disclosed method includes determining a current and a projected water depth for road segments of and around a current route to a destination. Additionally, the example method includes, in response to the current or the projected water depth of the road segments of the current route exceeding a first threshold, determining an alternate route to the destination.

Systems and methods for detecting an unmanned aerial vehicle (UAV). Network access (for example, to the Internet) may he provided by detecting a UAV and fixing one or more beams from one or snore ground terminals to the UAV. In one embodiment, the detection of a UAV includes forming and pointing beams from a ground terminal and ground gateways toward the UAV. The ground terminal may be configured to autonomously steer its antenna beam during initial installation to detect the reference signal from a UAV. In one variant, the ground terminals are steered to more finely track the position of the UAV based on a signal quality metric such as received signal strength and the UAV real-time position location coordinates. In one embodiment, the ground terminal antenna is initially manually pointed toward the UAV, and thereafter allowed to automatically steer to track the position of the UAV. In another embodiment the UAV antenna is steered toward a ground terminal using signal qualify received from the ground terminal and real-time position coordinates and orientation of the UAV.

A disclosed method includes monitoring a plurality of emergency event queues at an emergency network entity; determining that an emergency event in one of the emergency event queues corresponds to an emergency type that can be responded to using an unmanned aerial vehicle; determining that an unmanned aerial vehicle is available that has capabilities corresponding to the emergency type; establishing an unmanned aerial vehicle control link between the unmanned aerial vehicle and the emergency network entity; and deploying the unmanned aerial vehicle to the emergency event location and providing data from the unmanned aerial vehicle on a display of the emergency network entity.

An emergency unmanned aerial vehicle (UAV) and a method for employing a UAV. The method includes storing a digital elevation model (DEM) and associated data including locations of communication networks, updating the locations of communication networks in the associated data via a wireless transceiver, and storing position information determined by a global navigation satellite system (GNSS) receiver. The method includes detecting a predetermined condition using electronic sensors, determining whether the UAV is within a communications range of any communication network via the wireless transceiver, and determining a path to a communication network using the DEM and the associated data. The method also includes causing the UAV to become airborne and fly along the path, and transmitting a distress message via the wireless transceiver to the communication network, the distress message including position information corresponding to a location where the UAV detected the predetermined condition.

Methods, computer program products, and systems are presented. The methods include, for instance: providing a cognitive tour guide service to a group of participants for a tour with an initial route planned by participants registration information and environment information along the initial route. During the tour, real time sensory data on the participants health characteristics, change in environment are collected by a cognitive agent accompanying the group to lead the tour are relayed to a cognitive tour guide engine, and real time multi-objective optimization is modeled and performed. The participants are regrouped responsive to their respective enjoyment and circumstances of the environment and, among a set of optimal solutions, a new route for the tour is selected based on participant preference modeled and trained by participant feedback. During the tour, the cognitive tour guide engine continuously optimizes route responsive to incoming real time sensory data.

Methods, computer program products, and systems are presented. The methods include, for instance: providing a cognitive tour guide service to a group of participants for a tour with an initial route planned by participants registration information and environment information along the initial route. During the tour, real time sensory data on the participants health characteristics, change in environment are collected by a cognitive agent accompanying the group to lead the tour are relayed to a cognitive tour guide engine, and real time multi-objective optimization is modeled and performed. The participants are regrouped responsive to their respective enjoyment and circumstances of the environment and, among a set of optimal solutions, a new route for the tour is selected based on participant preference modeled and trained by participant feedback. During the tour, the cognitive tour guide engine continuously optimizes route responsive to incoming real time sensory data.