Headset and system for automatically generating turbulence reports

A pilot headset and system for automatically generating turbulence reports is provided. The turbulence reporting pilot headset includes a headset body having a motion sensor positioned therein that is adapted to collect motion data representative of changes in motion experienced by the headset body, and a motion data correlation module which is programmed, structured and/or configured to correlate the collected motion data to turbulence level data.

BACKGROUND

The present disclosure is directed generally to air turbulence reporting and more particularly to pilot headsets adapted to sense turbulence data.

A pilot report (PIREP) is a report of weather and flying conditions (including turbulence) encountered in flight. This information is usually relayed by aircraft radio to the nearest ground station. However, when pilots are flying, a PIREP may only be completed by a pilot when time and work load permit. Also, when experiencing turbulence, it is less likely a pilot will have time at that moment to provide the turbulence data on a PIREP.

A PIREP will contain several data fields. The following is a list of the types of data fields typically included in a PIREP: UA or UUA used to identify the PIREP as routine or urgent; /OV location of the PIREP, in relation to a NAVAID, an aerodrome or geographical coordinates; /TM time the PIREP was received from the pilot (UTC); /FL flight level or altitude above sea level at the time the PIREP is filed; it is essential for turbulence and icing reports; /TP aircraft type; it is essential for turbulence and icing reports. Optionally, the following data can also be supplied in the PIREP: /SK sky cover; /TA ambient temperature; important for icing reports; /WV wind vector referenced in terms of true north (ICAO), or magnetic north; /TB turbulence; intensity, whether it occurred in or near clouds, and duration; /IC icing; /RM remarks; /WX flight visibility and weather. The existing weather, navigation (e.g., GPS), orientation (e.g., compass) and icing sensors on the aircraft can automatically supply data corresponding to those particular fields. Turbulence data, however, is manually entered/provided by a pilot.

SUMMARY

The present disclosure is directed to a turbulence reporting pilot headset and a system for automatically generating turbulence reports.

In one aspect, a headset system is provided. The headset system includes: a headset body having a motion sensor in communication therewith and configured to collect motion data representative of changes in motion of the headset body; and a motion data correlation module programmed, structured and/or configured to correlate the collected motion data to turbulence level data.

In an example, the motion sensor is adapted to collect motion data in each of the X, Y, and Z axes.

In an example, the motion data correlation module is positioned on or within the headset body.

In an example, the motion data correlation module is located remotely from the headset body.

In an example, the headset system further includes a transmitter for wirelessly transmitting the motion data from the motion sensor to the motion data correlation module.

In an example, the headset system further includes wired connection between the motion sensor and the motion data correlation module.

In another aspect, a system for reporting turbulence data is provided. The system includes: a headset having a motion sensor in communication therewith that is configured to collect motion data representative of changes in motion of the headset body; a motion data correlation module programmed, structured and/or configured to correlate the collected motion data to turbulence level data; and a pilot reporting module adapted to receive the turbulence level data and generate pilot reports.

In an example, the motion sensor is adapted to collect motion data in each of the X, Y, and Z axes.

In an example, the system further includes a database in which is stored baseline data of motion changes in the X, Y, and Z axes and corresponding turbulence levels.

In an example, the motion data correlation module compares the collected X, Y, and Z axis motion data to the baseline of X, Y, and Z motion data stored in the database for correlating the collected motion data to a turbulence level.

In an example, the system further includes a transmitter for wirelessly transmitting the motion data to the motion data correlation module.

In an example, the system further includes a wired connection between the motion sensor and the motion data correlation module.

In an example, the system further includes a transmitter for wirelessly transmitting the pilot reports to a receiving station.

In an example, the motion sensor is packaged in a module adapted to connect and draw power and communication functions to the pilot reporting module via the headset.

In a further aspect, a method for generating a turbulence report is provided. The methods includes the steps of: collecting motion data in a pilot headset representative of changes in motion of the headset; correlating the collected motion data to turbulence data; and reporting the turbulence data to a pilot reporting module and generating a pilot report.

In an example, the method further includes the step of providing a database that has stored therein baseline data of motion changes in the X, Y, and Z axes and corresponding turbulence levels.

In an example, the step of collecting motion data includes collecting motion data in X, Y, and Z axes.

In an example, the method further includes the step of comparing the collected X, Y, and Z axis data to the baseline data of motion changes in the X, Y, and Z axes for correlating to a turbulence level.

In an example, the step of correlating the collected motion data includes using a motion data correlation module programmed, structured and/or configured to correlate the collected motion data to turbulence level data.

In an example, the method further includes the step of assigning a turbulence level based on a correlation of the collected motion data to the turbulence level data.

DETAILED DESCRIPTION

The present disclosure describes a pilot headset10that senses turbulence and a system100for receiving turbulence data from headset10and automatically generating a pilot report (PIREP)100(seeFIG. 2).

Referring toFIGS. 1A and 1B, in alternate examples, is a pilot headset10that comprises a motion sensor12incorporated therein. Pilot headset10may comprise an over the ear type model (FIG. 1A) or an in-ear model (FIG. 1B), as well as any other form factor used on pilot headsets. Sensor12may be one or several accelerometers, an IMU, or any other type or combination of sensors adapted to sense changes in movement. When headset10is worn on the pilot's head, sensor12may collect data in real-time when changes to the altitude and/or attitude (pitch, roll and yaw positioning) occur and are sensed by the sensor12positioned on the headset10. Preferably, sensor12is adapted to sense motion changes in the X (pitch), Y (yaw), and Z (roll) axes (e.g., an IMU) and collect linear and angular acceleration about the three axes. A data transmitter14adapted to transmit the motion data may also be equipped on headset10. While the sensor12and data transmitter14are schematically shown inFIG. 1as being mounted to an external surface of the headset10, in other examples the sensor12and transmitter are contained within the headset10, e.g., in an earcup, earbud, headband, and any connecting structures.

Aspects and implementations disclosed herein may be applicable to a wide variety of audio systems, such as headphones and other wearable audio devices in various form factors. A headphone refers to a device that fits around, on, or in an ear and that radiates acoustic energy into the ear canal. Headphones are sometimes referred to as earphones, earpieces, headsets, earbuds or sport headphones, and can be wired or wireless. A headphone includes an acoustic driver to transduce audio signals to acoustic energy. The acoustic driver may be housed in an earcup. While some of the figures and descriptions following may show a single headphone, a headphone may be a single stand-alone unit or one of a pair of headphones (each including a respective acoustic driver and earcup), one for each ear. A headphone may be connected mechanically to another headphone, for example by a headband and/or by leads that conduct audio signals to an acoustic driver in the headphone. A headphone may include components for wirelessly receiving audio signals. A headphone may include components of an active noise reduction (ANR) system. Headphones may also include other functionality such as a microphone so that they can function as a headset. WhileFIG. 1shows an example of an around-ear headset, in other examples the headset may be an in-ear, on-ear, or near-ear headset.

Unless specified otherwise, the term wearable audio device, as used in this document, includes headphones and various other types of personal audio devices such as head, shoulder or body-worn acoustic devices (e.g., audio eyeglasses or other head-mounted audio devices) that include one or more acoustic drivers to produce sound, with or without contacting the ears of a user. It should be noted that although specific implementations of speaker systems primarily serving the purpose of acoustically outputting audio are presented with some degree of detail, such presentations of specific implementations are intended to facilitate understanding through provision of examples and should not be taken as limiting either the scope of disclosure or the scope of claim coverage.

With reference toFIG. 4, the motion data that is sensed by sensor12is sent to a motion data correlation computer module positioned on or within the headset (not shown) or transmitted via a transmitter14(either wirelessly or via hard-wire connection) to the aircraft panel, to a separate computing device (e.g., a mobile phone, tablet, or other computer), or the electronic flight bag200as illustrated inFIG. 3. It should be noted that electronic flight bag200is a conventional electronic information management device that helps flight crews perform flight management tasks more easily and efficiently with less paper. It is a general purpose computing platform intended to reduce, or replace, paper-based reference material often found in the pilot's carry-on flight bag, including the aircraft operating manual, flight-crew operating manual, and navigational charts (including moving map for air and ground operations). In addition, electronic flight bag200can host purpose-built software applications, as with the present invention, to automate other functions normally conducted by hand, such as performance take-off calculations. From the panel, separate computing device, or electronic flight bag200, the data is transmitted to and stored in the non-volatile memory of a computer16(which may be a part of the electronic flight bag/panel200or separate). Computer16further includes a database18(either internal within memory or external which it can electronically access) that has stored thereon baseline motion data (e.g., motion data in the X, Y, and Z axes that correlate with various air conditions, for example normal air conditions, light, moderate, severe and extreme turbulence conditions). A computer program product20stored in computer16and the computer's processor include a correlation module22that will correlate the collected motion data with the stored baseline motion data and determine the appropriate turbulence level to assign to the to the collected motion data. The correlation module22accounts for movement of the pilot's head (e.g., head nods, head shakes, or any other movements of the head) so that such movements will not be correlated as indicative of turbulence. As illustrated inFIGS. 4 and 5, motion data may be correlated with a turbulence intensity level (e.g., light, moderate, severe, or extreme) based on the motion sensed at the headset of the pilot. For example, if the sensor12senses motion that is a slight, erratic change in altitude or attitude (pitch, roll or yaw), computer program18may correlate the data with light turbulence. This may be achieved by taking the X, Y, and Z acceleration data collected from motion sensor12over time, averaging the data and then comparing the actual data to a baseline level of acceleration in the X, Y, and Z axes indicative of normal movement, light, moderate, severe, and extreme turbulence.

Computer program20further comprises a reporting module24that will automatically populate a PIREP100with the turbulence data in section “/TB”, as reflected in the example form shown inFIG. 2. It is noted that all other sections of the PIREP100can also be automatically completed (e.g., by collecting data with pre-existing sensors equipped on aircraft) without manual entry by the pilot at the time of flying, aside from the “Remarks” section. Thus, with the turbulence section of the PIREP100being automatically completed, most of the remainder of the PIREP can also be automatically completed. In one example, once the pilot verifies the accuracy of the assigned turbulence level in computer program20, the PIREP100can be made available for other aircraft flying in the same general vicinity in real-time.

A machine learning module28can also be incorporated into computer program product20and used to continuously improve the accuracy of the turbulence reporting based on motion data collected over time and stored in database24. As more and more data is collected using the motion sensor12equipped headset10, when coupled with other data, such as weather and location data, the program can become more accurate at correlating the sensed data to turbulence levels.

FIG. 6illustrates a flowchart describing a method for generating a turbulence report. In step100, a pilot headset10equipped with a motion sensor12collects motion data (for example in the X, Y, and Z axes). In step102, the motion data is transmitted and optionally stored in the memory of a computer16. In step104, a motion data correlation module22correlates the collected motion data with baseline motion data stored in database18, and assigns a turbulence level to the collected motion data set. In optional step106, a machine learning module28identifies pilot reactions versus the real conditions and updates and improves upon the comparisons made by the correlation module22. In step108, the PIREP100can be automatically populated with the turbulence level (and other sensed parameters). In optional step110, a pilot verifies the turbulence level assigned to the collected motion data, and the PIREP is made available for others in step112.

With reference toFIG. 7, sensor12may be packaged as a module300adapted for operable interconnection to headset10. Module300is structured to draw power and communication functions to the electronic flight bag200via the headset10. Thus, configuration of the module300is dependent on the headset10for processing, power and communication to the electronic flight bag200.

The above-described examples of the described subject matter can be implemented in any of numerous ways. For example, some examples may be implemented using hardware, software or a combination thereof. When any aspect of an example is implemented at least in part in software, the software code can be executed on any suitable processor or collection of processors, whether provided in a single device or computer or distributed among multiple devices/computers.