Architecture Technology Corporation

Eric R Chartier

William Colligan

Paul C Davis

Andrew Murphy

Douglas Sweet

Evan Eaves

Ian J McLinden

Ryan L Hagelstrom

Judson Powers

Paul Nicotera

Joseph Sirianni

Erin Gambucci

Noel E Schmidt

Andrew Sullivan

Kirk J Swanson

An automatic, autonomous predictive aircraft surface state event track (ASSET) system, includes a mobile device onboard an aircraft and a remote service in communication with the mobile device. The mobile device includes a processor, and an application that in turn includes machine instructions encoded on a non-transitory computer-readable storage medium. The processor executes the machine instructions to receive sensor data from aircraft onboard sensors, the sensor data indicating an operational state of the aircraft; and transmit the sensor data. The remote service receives the sensor data and includes a remote processor that executes machine instructions to compute an operational state of the aircraft; identify an aircraft event associated the aircraft; and using the aircraft operational data, the sensor data, and the event, predict that the aircraft will meet a next scheduled aircraft event within a specified time window.

Autonomous and automatic, predictive aircraft surface state event track system and corresponding methods

An automatic, autonomous, and aircraft-centric interference advisory method is executed entirely on a fist aircraft operating on a movement area of a runway, the movement are including ramps, taxiways, and runways. The method includes a processor onboard the first aircraft computing a first movement projection for the first aircraft using first aircraft data received at the first aircraft; the processor computing additional second movement projections for multiple second aircraft operating on the movement area of the airport using second data regarding each of the multiple second aircraft; the processor detecting a threat to the first aircraft on approach to a defined intersection of the movement area from any of the multiple second aircraft based on a corresponding second movement projection within a configurable time limit of entry into the defined intersection by the first aircraft; and providing on the first aircraft, a threat advisory for a detected threat.

Advisor system and method

A method for minimizing aircraft collisions, includes detecting a flight of an unmanned aerial system (UAS) in a restricted area and determining a location of a radio frequency (RF) emitter in communication with the UAS. The method includes, at each of a plurality of RF sensors of a network of wireless RF sensors, receiving RF emissions within an RF band pertaining to UAS control, processing the received RF emissions, and transmitting data derived from the processed RF emissions. The method further includes at a designated one of the plurality of RF sensors, receiving the transmitted data from the RF sensors, a processor computing, using the transmitted data received from the RF sensors, a location estimate for the RF emitter and to predict the UAS is flying, and based on the prediction, the processor generating an alert.

Mobile emergency perimeter system and method

A method, executed by a processor, includes the processor receiving signals information from a device located on a departing airplane; verifying an identification of the airplane and identifying an expected departure sequence of aircraft surface states; monitoring and identifying additional signals information received from the mobile device, including comparing the additional signals information to known data; logging the additional signals information, and processing the additional signals information, and determining the logged data corresponds to events indicative of an aircraft surface state; sending an aircraft surface state reached message to Local and Center flight management; and executing a statistical routine and providing statistical data from the execution relating to an occurrence of upcoming aircraft surface state event and sending the statistical data with the aircraft surface state message.

Aircraft surface state event track system and method

A system and a corresponding computer-implemented method identifies and classifies community-sourced documents as true documents. The community-sourced documents include one or more data objects such as data items, including text, strings, phrases, and words; image items, including still image items, video image items, and icons; and drawing items. The system and corresponding method then report the analysis results.

Systems and methods for identifying and classifying community-sourced documents as true documents

A computer-implemented method for establishing and controlling a mobile perimeter and for determining a geographic location of an RF emitting source at or within the mobile perimeter includes receiving from RF sensors in a network, processed RF emissions from the source collected at RF sensors. The RF emissions follow a wireless protocol and include frames encoding RF emitting source identification information. The method further includes extracting RF emitting source identification information from the frames, processing the source identification information to identify the RF emitting source, and classifying the RF emitting source by one or more of UAS type, UAS capabilities, and UAS model. The method also includes receiving from the RF sensors, a geographic location of each RF sensor and a time of arrival (TOA) of the RF emissions at the RF sensor; and executing a multilateration process to estimate a geographic location of the RF emitting source.

Systems and methods for identifying, classifying, locating, and tracking radio-frequency emitting objects in a temporary flight restriction area

In general, this disclosure describes methods and devices for analyzing source code to detect potential bugs in the code. Specifically, a device retrieves source code of an application. For each distinct execution of a plurality of executions of the application, the device initiates the respective execution at a particular starting point of the source code and inputs, into the source code, a unique set of inputs relative to any other execution. The device stores, into a path log, an indication of each line of source code and stores, into an output log, an indication of each output object encountered during the respective execution. Each output object includes a local variable dependent on the inputs. The device analyzes, using a machine learning model, the path and output logs to identify an abnormality indicative of a potential bug in the source code. The device outputs a graphical representation of the abnormality.

Automated software bug discovery and assessment

An automatic, autonomous, and aircraft-centric interference advisory method is executed entirely on a first aircraft operating on a movement area of a runway, the movement are including ramps, taxiways, and runways. The method includes a processor onboard the first aircraft computing a first movement projection for the first aircraft using first aircraft data received at the first aircraft; the processor computing additional second movement projections for multiple second aircraft operating on the movement area of the airport using second data regarding each of the multiple second aircraft; the processor detecting a threat to the first aircraft on approach to a defined intersection of the movement area from any of the multiple second aircraft based on a corresponding second movement projection within a configurable time limit of entry into the defined intersection by the first aircraft; and providing on the first aircraft, a threat advisory for a detected threat.

A method for minimizing aircraft collisions, comprising includes detecting a flight of an unmanned aerial system (UAS) in a restricted area and determining a location of a radio frequency (RF) emitter in communication with the UAS. The method includes, at each of a plurality of RF sensors of a network of wireless RF sensors, receiving RF emissions within an RF band pertaining to UAS control, processing the received RF emissions, and transmitting data derived from the processed RF emissions. The method further includes at a designated one of the plurality of RF sensors, receiving the transmitted data from the RF sensors, a processor computing, using the transmitted data received from the RF sensors, a location estimate for the RF emitter and to predict the UAS is flying, and based on the prediction, the processor generating an aircraft collision alert.

A computer-implemented method for training a neural network system to classify data items as true mentions of relevant data objects includes, based on a domain of interest, a processor controlling an input component and a data store to receive and store a document related to the domain of interest, control a natural language processor to extract data items related to the domain of interest from the document, create a first training data set of selected ones of the data items, using the first training data set, train the neural network to identify true mentions of data objects relevant to the domain of interest, apply tweaks to one or more of the data items to create a list of tweaked data items, creating a second training data set including the tweaked data items, and using the first and second training data sets, further train the neural network to identify true mentions of relevant data objects.

Community-based reporting and analysis system and method

A computer-implemented method for establishing and controlling a mobile perimeter and for determining a geographic location of an RF emitting source at or within the mobile perimeter includes receiving from RF sensors in a network, processed RF emissions from the source collected at RF sensors. The RF emissions follow a wireless protocol and include frames encoding RF emitting source identification information. The method further includes extracting RF emitting source identification information from one or more of the frames, processing the source identification information to identify the RF emitting source, and classifying the RF emitting source by one or more of UAS type, UAS capabilities, and UAS model. The method also includes receiving from the RF sensors, a geographic location of each RF sensor and a time of arrival (TOA) of the RF emissions at the RF sensor; and executing a multilateration process to estimate a geographic location of the RF emitting source.

An advisor system includes a computer-readable storage medium having encoded thereon a program of instructions. Execution of the instructions causes a processor to determine a current state of a first aircraft operating on a movement area of an airport including determining a path vector for the first aircraft. The path vector includes a speed and direction of travel of the first aircraft and identification of a runway intersection the first aircraft is projected to enter. The processor processes a surveillance signal transmitted from a second aircraft operating on the movement area, including determining a quality of the surveillance signal. The processor further determines a movement vector of the second aircraft, and compares the path vector and the movement vector to identify possible interference. Finally, the processor provides an advisory at the first aircraft based on the compared path vector and the movement vector.

Growing community of inventors

Saint Louis Park, MN, United States of America

Eric R Chartier