An internet of things is disclosed, comprising plural SDR receivers and possibly a centralised system, where one or more of the receivers may be mobile. The internet of things thus allows for a very large proportion of RF signals present within a city, for example, to be monitored and analysed for the purpose of identifying, tracking and/or preventing criminal behaviour. The receivers may be equipped with secure SDRs for increased security and privacy and the system preferably includes artificial intelligence using machine learning technology, for increased adaptability among others. The system is flexible due to the programmability of the SDRs.

An apparatus includes a capsule configured to be launched or carried towards an unmanned aerial vehicle (UAV). The apparatus also includes a directed energy device within or carried by the capsule. The directed energy device includes a first inductor configured to generate an inductive magnetic field that is able to inductively couple into one or more electronics of the UAV in order to disable or destabilize the UAV. The capsule can be configured to be launched towards the UAV and can include a loiter mechanism (such as a rotor, umbrella, or parachute) configured to maintain a position of the capsule or to slow a descent of the capsule after launch. The capsule can also be configured to be carried towards the UAV by a different UAV, and the apparatus can further include a tether coupling the capsule to the different UAV.

Systems and methods are described for a cyber-physical vehicle management system generated by an Integrated Secure Device Manager (ISDM) Authority configured to manage licensing and approval of Cyber-Physical Vehicle (CPV)s, a public/private key pair and a unique ID for the Authority, create a self-signed Authority token signed by the private key, send the Authority token to a plurality of ISDM Node device configured to verify Module device authenticity and in communication with the Authority, store, by each Node, the Authority token, and mark, by each Node, the Authority token as trusted.

A system for providing integrated detection and deterrence against an unmanned vehicle including but not limited to aerial and similar technology unmanned systems using a detection element, a tracking element, an identification element and an interdiction or deterrent element. Elements contain sensors that observe real time quantifiable data regarding the object of interest to create an assessment of the object of interests risk or threat to a protected area of interest. This assessment is based on the application of machine learning and data mining techniques and protocols to the set of data related to the object of interest. This data product is available to third parties via a set of defined interface protocols and available API. The deterrent element, using other machine learning or artificially intelligent algorithms, selects from a variable menu of possible deterrent actions not limited to those actions currently included in this embodiment, but includes those actions available from third parties such as specialized hunter drones. Though designed for autonomous action, a Human in the Loop may override the automated system solutions.

A cyber-physical vehicle management system may allow for highly reliable and authentic identity management of cyber-physical systems, unforgeable legal interception devices, and robust relay nodes. A cyber-physical vehicle management system may also provide for human and object bi-directional authenticity verification. In some cases, a cyber physical management system may enable a cyber physical vehicle (CPV) detection and intervention system which may be capable or detection, identification, capture, seizure, and immobilization of CPVs. In some embodiments the CPV detection and intervention system includes a geocoding laser subsystem for determining a location of a CPV.

Techniques are described for the exchange of control signals between a controlled unmanned aircraft (i.e. drone) and a ground control station and for the transmission of communication signals, such as video, from the drone to the ground control station so that the signals are more difficult to intercept or jam. The video signal transmitted from the drone can be an analog RF signal employing one or more of video scrambling, RF signal inversion, hopping, usage of a wide frequency range and other techniques. To secure the control signals between the drone and the ground control station, techniques can include hopping, encryption and use of a wide frequency range.

A system for defeating a threat unmanned aerial vehicle including a friendly unmanned aerial vehicle and a containment system. The containment system is deployable from the friendly unmanned aerial vehicle and includes a signal blocking enclosure and a capturing device. The signal blocking enclosure is formed of a conductive material for shielding radio frequency signals from propagating in or out of the signal blocking enclosure. The capturing device is configured for arresting the threat unmanned aerial vehicle and positioning an arrested threat unmanned aerial vehicle within the signal blocking enclosure.

A system for providing integrated detection and countermeasures against unmanned aerial vehicles include a detecting element, a location determining element and an interdiction element. The detecting element detects an unmanned aerial vehicle in flight in the region of, or approaching, a property, place, event or very important person. The location determining element determines the exact location of the unmanned aerial vehicle. The interdiction element can either direct the unmanned aerial vehicle away from the property, place, event or very important person in a non-destructive manner, or can cause disable the unmanned aerial vehicle in a destructive manner.

In accordance with various embodiments of the disclosed subject matter, a system, apparatus and method is configured to receive/process radio frequency emanations of a potentially threatening drone to generate therefrom a human-recognizable audio signal characteristic of the drone (i.e., a voice of the drone) so that a warfighter may be alerted to the activity of the drone and respond accordingly.

A drone defense system (DDS) beacon detects unmanned aerial systems (UAS) traffic and transmits a broadcast signal over a transmission region indicating a no-fly zone in which only UAS having an authorization are allowed to fly. The beacon allows UAS with clearance to enter the no-fly zone. Those UAS without clearance are diverted around the no-fly zone, denied Wi-Fi and/or RF connection, forced to return to home launch sites via activation of standard preprogrammed Return to Home (RTH) routines, or forced to land at specified locations where they may be captured. Military, emergency medical services (EMS), and other UAS are allowed to enter no-fly zones in which other UAS, such as commercial, or consumer UAS, cannot enter. DDS cloud collects and stores log data from all deployed DDS beacons. DDS cloud can send system software updates to DDS beacons, make real-time statistical analysis, and provide report data to outside systems.