Patent Publication Number: US-10319237-B1

Title: Dynamically determining runway conditions

Description:
FIELD 
     This disclosure relates generally to airplanes, and more particularly to dynamically determining runway conditions. 
     BACKGROUND 
     Runway conditions are generally determined based on the subjective judgment of pilots who operate airplanes on the runways. The pilots&#39; subjective feedback may be used to classify a current condition of a runway. Other pilots may use this information to make decisions for operating airplanes on the runway, such as when landing and taking off. Because the pilots&#39; feedback is subjective, however, the pilots&#39; feedback may be inconsistent and/or not accurate. 
     SUMMARY 
     The subject matter of the present application has been developed in response to the present state of the art, and in particular, in response to the problems and disadvantages associated with conventional methods for determining runway conditions. Accordingly, the subject matter of the present application has been developed to dynamically determine runway conditions that overcomes at least some of the above-discussed shortcomings of prior art techniques. 
     Described herein is an airport computing system that is communicatively coupled to a first airplane and to one or more second airplanes over a network system. The airport computing system comprises a plurality of sensors associated with the first airplane. The airport computing system further comprises a data module configured to receive data from the first airplane over the network. The data comprises runway data sampled using the plurality of sensors while the first airplane is on a runway. The airport computing system also comprises a parameter module configured to determine one or more parameters that describe a condition for the runway based on the received runway data. The airport computing system further comprises a transmission module configured to transmit the one or more parameters to the one or more second airplanes over the network. At least a portion of said modules comprise one or more of hardware circuits, programmable hardware devices, and executable code, the executable code stored on one or more computer readable storage media. The preceding subject matter of this paragraph characterizes example 1 of the present disclosure. 
     The data module receives a plurality of runway data sets from a plurality of first airplanes. The parameter module determines the one or more parameters based on a combination of each of the plurality of runway data sets. The preceding subject matter of this paragraph characterizes example 2 of the present disclosure, wherein example 2 also includes the subject matter according to example 1, above. 
     The data module receives new runway data over the network from a different first airplane. The parameter module updates, in real-time, the one or more parameters based on the new runway data. The transmission module transmits the one or more updated parameters to the one or more second airplanes over the network. The preceding subject matter of this paragraph characterizes example 3 of the present disclosure, wherein example 3 also includes the subject matter according to any one of examples 1 or 2, above. 
     The data module receives the runway data while the first airplane is landing on the runway. The preceding subject matter of this paragraph characterizes example 4 of the present disclosure, wherein example 4 also includes the subject matter according to any one of examples 1-3, above. 
     The runway data comprises an amount of force applied to the first airplane&#39;s brakes over a period of time while the first airplane is landing. The amount of force applied is determined using the plurality of sensors. The preceding subject matter of this paragraph characterizes example 5 of the present disclosure, wherein example 5 also includes the subject matter according to example 4, above. 
     The one or more parameters that the parameter module determines is an average brake force calculated from the time that the first airplane first applies the brakes until a time when the brakes are not applied while the first airplane is landing. The preceding subject matter of this paragraph characterizes example 6 of the present disclosure, wherein example 6 also includes the subject matter according to example 5, above. 
     The runway data comprises deceleration data sampled over a period of time while the first airplane is landing, the deceleration data sampled using the plurality of sensors. The preceding subject matter of this paragraph characterizes example 7 of the present disclosure, wherein example 7 also includes the subject matter according to any one of examples 4-6, above. 
     The one or more parameters that the parameter module determines is a rate of deceleration for the first airplane based on the deceleration data. The preceding subject matter of this paragraph characterizes example 8 of the present disclosure, wherein example 8 also includes the subject matter according to example 7, above. 
     The one or more parameters that the parameter module determines comprises a coefficient of friction for the runway that is determined based on the runway data. The preceding subject matter of this paragraph characterizes example 9 of the present disclosure, wherein example 9 also includes the subject matter according to any one of examples 1-8, above. 
     The data module receives the runway data while the first airplane is taking off from the runway. The preceding subject matter of this paragraph characterizes example 10 of the present disclosure, wherein example 10 also includes the subject matter according to any one of examples 1-9, above. 
     The runway data comprises an amount of thrust applied to the first airplane over a period of time while the first airplane is taking off from the runway. The amount of thrust applied is determined using the plurality of sensors. The preceding subject matter of this paragraph characterizes example 11 of the present disclosure, wherein example 11 also includes the subject matter according to example 10, above. 
     The one or more parameters that the parameter module determines is an average thrust calculated from the time that thrust is first applied to the first airplane until when the first airplane takes off from the runway. The preceding subject matter of this paragraph characterizes example 12 of the present disclosure, wherein example 12 also includes the subject matter according to example 11, above. 
     The runway data comprises acceleration data sampled over a period of time while the first airplane is taking off, the acceleration data sampled using the plurality of sensors. The preceding subject matter of this paragraph characterizes example 13 of the present disclosure, wherein example 13 also includes the subject matter according to any one of examples 10-12, above. 
     The one or more parameters that the parameter module determines is a rate of acceleration for the first airplane based on the acceleration data. The preceding subject matter of this paragraph characterizes example 14 of the present disclosure, wherein example 14 also includes the subject matter according to example 13, above. 
     Further described herein is an apparatus that comprises a data module configured to receive, at an airport computing system, data from a first airplane over a network. The data comprises runway data sampled using a plurality of sensors located on the first airplane while the first airplane is on a runway. The apparatus also comprises a parameter module configured to determine one or more parameters that describe a condition for the runway based on the received runway data. The apparatus further comprises a transmission module configured to transmit, from the airport computing system, the one or more parameters to one or more second airplanes over the network. At least a portion of said modules comprise one or more of hardware circuits, programmable hardware devices, and executable code, the executable code stored on one or more computer readable storage media. The preceding subject matter of this paragraph characterizes example 15 of the present disclosure. 
     The data module receives a plurality of runway data sets from a plurality of first airplanes. The parameter module determines the one or more parameters based on a combination of each of the plurality of runway data sets. The preceding subject matter of this paragraph characterizes example 16 of the present disclosure, wherein example 16 also includes the subject matter according to example 15, above. 
     The data module receives new runway data over the network from a different first airplane. The parameter module updates, in real-time, the one or more parameters based on the new runway data. The transmission module transmits the one or more updated parameters to the one or more second airplanes over the network. The preceding subject matter of this paragraph characterizes example 17 of the present disclosure, wherein example 17 also includes the subject matter according to any one of examples 15 or 16, above. 
     The data module receives the runway data while the first airplane is landing on the runway. The runway data comprising one or more of an amount of force applied to the first airplane&#39;s brakes over a period of time while the first airplane is landing, the parameter module calculating an average brake force based on the amount of force applied to the first airplane&#39;s brakes, and deceleration data sampled over a period of time while the first airplane is landing, the parameter module calculating a rate of deceleration for the first airplane based on the deceleration data. The preceding subject matter of this paragraph characterizes example 18 of the present disclosure, wherein example 18 also includes the subject matter according to any one of examples 15-17, above. 
     The one or more parameters that the parameter module determines comprises a coefficient of friction for the runway. The coefficient of friction is determined based at least in part on one or more of the average brake and the rate of deceleration. The transmission module transmits the determined coefficient of friction to the one or more second airplanes over the network. The preceding subject matter of this paragraph characterizes example 19 of the present disclosure, wherein example 19 also includes the subject matter according to example 18, above. 
     Additionally described herein is a method that comprises receiving, at an airport computing system, data from a first airplane over a network. The data comprises runway data sampled using a plurality of sensors located on the first airplane while the first airplane is on a runway. The method also comprises determining one or more parameters that describe a condition for the runway based on the received runway data. The method further comprises transmitting, from the airport computing system, the one or more parameters to one or more second airplanes over the network. The preceding subject matter of this paragraph characterizes example 20 of the present disclosure. 
     The described features, structures, advantages, and/or characteristics of the subject matter of the present disclosure may be combined in any suitable manner in one or more embodiments and/or implementations. In the following description, numerous specific details are provided to impart a thorough understanding of embodiments of the subject matter of the present disclosure. One skilled in the relevant art will recognize that the subject matter of the present disclosure may be practiced without one or more of the specific features, details, components, materials, and/or methods of a particular embodiment or implementation. In other instances, additional features and advantages may be recognized in certain embodiments and/or implementations that may not be present in all embodiments or implementations. Further, in some instances, well-known structures, materials, or operations are not shown or described in detail to avoid obscuring aspects of the subject matter of the present disclosure. The features and advantages of the subject matter of the present disclosure will become more fully apparent from the following description and appended claims, or may be learned by the practice of the subject matter as set forth hereinafter. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       In order that the advantages of the subject matter may be more readily understood, a more particular description of the subject matter briefly described above will be rendered by reference to specific embodiments that are illustrated in the appended drawings. Understanding that these drawings depict only typical embodiments of the subject matter and are not therefore to be considered to be limiting of its scope, the subject matter will be described and explained with additional specificity and detail through the use of the drawings, in which: 
         FIG. 1  is a schematic block diagram of a system for dynamically determining runway conditions, according to one or more examples of the present disclosure; 
         FIG. 2  is a schematic block diagram of an apparatus for dynamically determining runway conditions, according to one or more examples of the present disclosure; 
         FIG. 3  is a schematic block diagram of a system for dynamically determining runway conditions, according to one or more examples of the present disclosure; 
         FIG. 4  is a schematic flow diagram of a method for dynamically determining runway conditions, according to one or more examples of the present disclosure; 
         FIG. 5  is a schematic flow diagram of a method for dynamically determining runway conditions, according to one or more examples of the present disclosure; 
         FIG. 6  is a schematic flow diagram of a method for dynamically determining runway conditions, according to one or more examples of the present disclosure; and 
         FIG. 7  is a schematic flow diagram of a method for dynamically determining runway conditions, according to one or more examples of the present disclosure. 
     
    
    
     DETAILED DESCRIPTION 
     Reference throughout this specification to “one embodiment,” “an embodiment,” or similar language means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present disclosure. Appearances of the phrases “in one embodiment,” “in an embodiment,” and similar language throughout this specification may, but do not necessarily, all refer to the same embodiment. Similarly, the use of the term “implementation” means an implementation having a particular feature, structure, or characteristic described in connection with one or more embodiments of the present disclosure, however, absent an express correlation to indicate otherwise, an implementation may be associated with one or more embodiments. 
       FIG. 1  is a schematic block diagram illustrating one embodiment of a system  100  for dynamically determining runway conditions. The system  100  includes one or more information handling devices  102 , one or more runway condition apparatuses  104 , one or more data networks  106 , one or more servers  108 , and one or more airplanes  110 . Even though a specific number of information handling devices  102 , runway condition apparatuses  104 , data networks  106 , servers  108 , and airplanes  110  are depicted in  FIG. 1 , one of skill in the art will recognize, in light of this disclosure, that any number of information handling devices  102 , runway condition apparatuses  104 , data networks  106 , servers  108 , and airplanes  110  may be included in the system  100 . 
     The information handling devices  102  of the system  100  may include one or more of a desktop computer, a laptop computer, a tablet computer, a smart phone, a smart speaker (e.g., Amazon Echo®, Google Home®, Apple HomePod®), a security system, a set-top box, a gaming console, a smart TV, a smart watch, a fitness band or other wearable activity tracking device, an optical head-mounted display (e.g., a virtual reality headset, smart glasses, or the like), a High-Definition Multimedia Interface (“HDMI”) or other electronic display dongle, a personal digital assistant, a digital camera, a video camera, or another computing device comprising a processor (e.g., a central processing unit (“CPU”), a processor core, a field programmable gate array (“FPGA”) or other programmable logic, an application specific integrated circuit (“ASIC”), a controller, a microcontroller, and/or another semiconductor integrated circuit device), a volatile memory, and/or a non-volatile storage medium. 
     In certain embodiments, the information handling devices  102  are communicatively coupled to one or more other information handling devices  102 , one or more servers  108 , and/or one or more airplanes  110  over the data network  106 , described below. The information handling devices  102  may include processors, processor cores, and/or the like that are configured to execute various programs, program code, applications, instructions, functions, and/or the like. 
     In one embodiment, the runway condition apparatus  104  is configured to receive, at an airport computing system, runway data from a first airplane over a network. The runway data may be sampled using a plurality of sensors located on the first airplane. The runway condition apparatus  104 , in further embodiments, is configured to determine one or more parameters that describe a condition for a runway based on the received runway data. In certain embodiments, the runway condition apparatus  104  is configured to transmit, from the airport computing system, the one or more parameters to one or more second airplanes over the network. 
     In one embodiment, the runway condition apparatus  104  provides a solution to drawbacks in conventional systems for detecting runway conditions. Runway conditions are conventionally determined based on feedback from pilots or others that use runways. For instance, a pilot may report that the runway is wet, dry, snowy, slushy, windy, and/or the like. However, due to the subjectivity of the feedback, the reported conditions may be inaccurate, not accurate enough, and/or inconsistent. 
     The runway condition apparatus  104  improves upon conventional methods for determining runway conditions by sampling runway data in real-time using various sensors of an airplane, dynamically determining factors related to the runway conditions, and sharing the determined runway condition factors with other airplanes that are using the runway. Furthermore, the runway condition apparatus  104  continuously updates and shares the determined runway condition factors when new data is received from airplanes that are using the runway. In this manner, a more consistent and accurate determination of runway conditions can be performed and used by pilots to control or adjust the operation of their airplanes. 
     In various embodiments, the runway condition apparatus  104  may be embodied as a hardware appliance that can be installed or deployed on an information handling device  102 , on a server  108 , or elsewhere on the data network  106 . In certain embodiments, the runway condition apparatus  104  may include a hardware device such as a secure hardware dongle or other hardware appliance device (e.g., a set-top box, a network appliance, or the like) that attaches to a device, a laptop computer, a server  108 , a tablet computer, a smart phone, a security system, or the like, either by a wired connection (e.g., a universal serial bus (“USB”) connection) or a wireless connection (e.g., Bluetooth®, Wi-Fi, near-field communication (“NFC”), or the like); that attaches to an electronic display device (e.g., a television or monitor using an HDMI port, a DisplayPort port, a Mini DisplayPort port, VGA port, DVI port, or the like); and/or the like. A hardware appliance of the runway condition apparatus  104  may include a power interface, a wired and/or wireless network interface, a graphical interface that attaches to a display, and/or a semiconductor integrated circuit device as described below, configured to perform the functions described herein with regard to the runway condition apparatus  104 . 
     The runway condition apparatus  104  may include a semiconductor integrated circuit device (e.g., one or more chips, die, or other discrete logic hardware), or the like, such as a field-programmable gate array (“FPGA”) or other programmable logic, firmware for an FPGA or other programmable logic, microcode for execution on a microcontroller, an application-specific integrated circuit (“ASIC”), a processor, a processor core, or the like. In one embodiment, the runway condition apparatus  104  may be mounted on a printed circuit board with one or more electrical lines or connections (e.g., to volatile memory, a non-volatile storage medium, a network interface, a peripheral device, a graphical/display interface, or the like). The hardware appliance may include one or more pins, pads, or other electrical connections configured to send and receive data (e.g., in communication with one or more electrical lines of a printed circuit board or the like), and one or more hardware circuits and/or other electrical circuits configured to perform various functions of the runway condition apparatus  104 . 
     The semiconductor integrated circuit device or other hardware appliance of the runway condition apparatus  104 , in certain embodiments, includes and/or is communicatively coupled to one or more volatile memory media, which may include but is not limited to random access memory (“RAM”), dynamic RAM (“DRAM”), cache, or the like. In one embodiment, the semiconductor integrated circuit device or other hardware appliance of the runway condition apparatus  104  includes and/or is communicatively coupled to one or more non-volatile memory media, which may include but is not limited to: NAND flash memory, NOR flash memory, nano random access memory (nano RAM or NRAM), nanocrystal wire-based memory, silicon-oxide based sub-10 nanometer process memory, graphene memory, Silicon-Oxide-Nitride-Oxide-Silicon (“SONOS”), resistive RAM (“RRAM”), programmable metallization cell (“PMC”), conductive-bridging RAM (“CBRAM”), magneto-resistive RAM (“MRAM”), dynamic RAM (“DRAM”), phase change RAM (“PRAM” or “PCM”), magnetic storage media (e.g., hard disk, tape), optical storage media, or the like. 
     The data network  106 , in one embodiment, includes a digital communication network that transmits digital communications. The data network  106  may include a wireless network, such as a wireless cellular network, a local wireless network, such as a Wi-Fi network, a Bluetooth® network, a near-field communication (“NFC”) network, an ad hoc network, and/or the like. The data network  106  may include a wide area network (“WAN”), a storage area network (“SAN”), a local area network (LAN), an optical fiber network, the internet, or other digital communication network. The data network  106  may include two or more networks. The data network  106  may include one or more servers, routers, switches, and/or other networking equipment. The data network  106  may also include one or more computer readable storage media, such as a hard disk drive, an optical drive, non-volatile memory, RAM, or the like. 
     The wireless connection may be a mobile telephone network. The wireless connection may also employ a Wi-Fi network based on any one of the Institute of Electrical and Electronics Engineers (“IEEE”) 802.11 standards. Alternatively, the wireless connection may be a Bluetooth® connection. In addition, the wireless connection may employ a Radio Frequency Identification (“RFID”) communication including RFID standards established by the International Organization for Standardization (“ISO”), the International Electrotechnical Commission (“IEC”), the American Society for Testing and Materials® (ASTM®), the DASH7™ Alliance, and EPCGlobal™. 
     Alternatively, the wireless connection may employ a ZigBee® connection based on the IEEE 802 standard. In one embodiment, the wireless connection employs a Z-Wave® connection as designed by Sigma Designs®. Alternatively, the wireless connection may employ an ANT® and/or ANT+® connection as defined by Dynastream® Innovations Inc. of Cochrane, Canada. 
     The wireless connection may be an infrared connection including connections conforming at least to the Infrared Physical Layer Specification (“IrPHY”) as defined by the Infrared Data Association® (“IrDA”®). Alternatively, the wireless connection may be a cellular telephone network communication. All standards and/or connection types include the latest version and revision of the standard and/or connection type as of the filing date of this application. 
     The one or more servers  108 , in one embodiment, may be embodied as blade servers, mainframe servers, tower servers, rack servers, and/or the like. The one or more servers  108  may be configured as mail servers, web servers, application servers, FTP servers, media servers, data servers, web servers, file servers, virtual servers, and/or the like. The one or more servers  108  may be communicatively coupled (e.g., networked) over a data network  106  to one or more information handling devices  102 . The one or more servers  108  may store data associated with an information handling device  102 . 
     The one or more airplanes  110  may include various airplanes such as commercial airplanes, private airplanes, jets, propeller airplanes, and/or the like. In some embodiments, the airplanes  110  (or aircraft) include multiple sensors for detecting and sampling data about the airplane  110 , data about the airplane&#39;s external environment, and/or the like. In certain embodiments, the airplane&#39;s sensors include sensors for detecting an amount of pressure or force that is applied to the airplane&#39;s brakes; sensors for detecting the airplane&#39;s acceleration and/or deceleration; sensors for detecting an amount of thrust applied and/or output by the airplane&#39;s engines; and/or the like. 
     In certain embodiments, the airplanes  110  include computing systems onboard that may be communicatively coupled to the sensors, to an airport computing system, and/or computing systems of other airplanes. In this manner, sensor data, for instance, may be transmitted from an airplane to an airport computing system and/or one or more other airplanes over a data network  106  such as a secure wireless communication network. The system  100  may include one airplane  110  or a plurality of airplanes  112 , and, in some embodiments, the airplanes  110  may or may not be an affirmative part of the system  100 . 
       FIG. 2  depicts one embodiment of an apparatus  200  for dynamically determining runway conditions. The apparatus  200  includes an embodiment of the runway condition apparatus  104 . The runway condition apparatus  104 , in certain implementations, includes one or more of a data module  202 , a parameter module  204 , and a transmission module  206 , which are described in more detail below. 
     The data module  202 , in one embodiment, is configured to receive runway data from an airplane  110 , e.g., while the airplane  110  is using the runway to land or take off. In certain embodiments, the runway data is sampled using various sensors integrated with, coupled to, connected to, and/or the like the airplane  110 . For instance, the sensors may include sensors for measuring or detecting an amount of force or pressure applied to the airplane&#39;s brakes while the airplane  110  is landing. In some embodiments, the sensors include sensors for detecting the acceleration, deceleration, speed, velocity, and/or the like of the airplane  110  while it is landing or taking off. In further embodiments, the sensors include sensors for determining or detecting an amount of thrust, e.g., forward or reverse thrust, applied to the airplane&#39;s engines. 
     In one embodiment, the data module  202  receives runway data from an airplane  110  at an airport computing system over a data network. For example, the data module  202  may receive runway data from the airplane  110  every second, every 500 microseconds or milliseconds, and/or the like while the airplane is in the process of landing and/or taking off from the runway. Thus, the airplane&#39;s sensor may begin sensing data that may be used to determine the runway conditions, e.g., the amount of force applied to the airplane&#39;s brakes, the airplane&#39;s acceleration or deceleration, the amount of thrust provided by the airplane&#39;s engines, and/or the like, when the airplane  110  first touches down on the runway when landing or when the airplane  110  begins taking off, and may send the data to the airport computing system over a wireless communication channel between the airplane  110  and the airport computing system throughout the landing and/or taking off process. 
     In another example, the data module  202  may receive the runway data from the airplane  110  when the airplane  110  has completely finished its landing process, e.g., comes to a stop or is moving below a threshold speed, or takes off from the runway, e.g., when its wheel(s) leave the runway. In one embodiment, the sampled runway data may be normalized, formatted, organized, or otherwise converted to a useable format prior to sending the data to the airport computing system. For instance, the sampled runway data may be aggregated, categorized by data source/sensor, structured using a structured language (e.g., XML), and/or the like prior to the data being sent to the airport computing system. 
     In one embodiment, the parameter module  204  is configured to determine one or more parameters that describe a condition for the runway based on the received runway data. As used herein, a runway condition parameter may be a variable, factor, coefficient, and/or the like that describes a condition of the runway and/or may be used to determine how to operate one or more aspects of the airplane  110  while landing or raking off from the runway. In such an embodiment, the parameter module  204  may be located on the airport computing system and may calculate, determine, and/or the like the runway condition parameters in response to the data module  202  receiving the runway data at the airport computing system. 
     In one embodiment, the one or more parameters that the parameter module  204  determines using the runway data includes a coefficient of friction for the runway. The coefficient of friction, as used herein, may describe a ratio between the force necessary to move one surface (e.g., an airplane, or more particularly the tires of the airplane) horizontally over another surface (e.g., the runway surface) and the pressure between the two surfaces. 
     For instance, the parameter module  204  may use the brake force data (e.g., an average brake force over a period of time while the airplane  110  is landing), the deceleration data (e.g., the rate of deceleration over the period of time while the airplane  110  as landing), and/or the reverse thrust data to calculate the coefficient of friction while the airplane  110  is landing. Similarly, the parameter module  204  may use the acceleration data (e.g., the rate of acceleration of the period of time while the airplane  110  is taking off) and/or the thrust data to calculate the coefficient of friction while the airplane  110  is taking off. 
     For example, the following calculations may be used to determine the coefficient of friction using the runway data for an airplane  110 : 
     
       
         
           
             
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     where α=acceleration, μ S =coefficient of (static) friction, V f,i =Velocity final, initial, Δx=change in position, m a =airplane mass, g=gravity, f L =Lift force, f W =Weight force, f D =Drag force, f S =Force of (static) friction, f B =Braking force, and f RT =Reverse thrust force. 
     In certain embodiments, the drag force may include a positive or negative component due to wind drag. Furthermore, the above calculation assumes no slippage or calculation of kinetic force. In conditions where slippage occurs, only the coefficients of slow moving airplane of the slower part of the airplanes&#39; deceleration are calculated (e.g., areas where no slippage occurs). The airplane&#39;s  110  sensors may also be used to determine the airplane&#39;s  110  acceleration, and as described above, the airplane&#39;s  110  sensors are used to determine the brake force and the amount of reverse thrust applied to the airplane  110  during landing, for example. 
     In one embodiment, the transmission module  206  transmits the one or more determined parameters to other airplanes  110  that are landing and/or taking off. In certain embodiments, the transmission module  206  transmits the determined parameters to the other airplanes  110  over a data network  106  from the airport computing system, e.g., from the traffic control tower system. In further embodiments, the data module  202  may be located on the airplane  110  that captures the runway data and may receive the runway data from the various sensors, the parameter module  204  may determine the one or more parameters on the airplane  110  that capture the runway data, and may share the determined parameters directly with airplanes landing and/or taking off from the runway, e.g., over a peer-to-peer network, a mesh network, an ad-hoc network, and/or other wireless network. 
     In certain embodiments, the transmission module  206  and/or the parameter module  204  stores the one or more determined parameters in a remote location, a cloud location, at the airport computing system, and/or the like. In one embodiment, the transmission module  206  accesses the one or more determined parameters from the storage location and sends, transmits, shares, and/or the like the one or more determined parameters to/with airplanes  110  that are landing and/or taking off. In certain embodiments, airplanes  110  that are landing and/or taking off may have direct access to the storage locations for the parameter data, and may access the parameter data from the storage location, e.g., a cloud or other remote location, while bypassing the airport computing system. 
     In some embodiments, the data module  202  also receives subjective data from pilots operating airplanes  110  on the runway, such as the observed conditions of the runway, e.g., wet, dry, etc., which the parameter module  204  may incorporate into the calculation of the one or more parameters and/or otherwise enhance with the one or more parameters. The transmission module  206  may also transmit the subjective data from the pilots to other pilots that are landing and/or taking off from the runway, in addition to the calculated parameters. 
     In certain embodiments, the data module  202  receives a plurality of runway data sets from a plurality of airplanes  112  that are landing and/or taking off from the runway. In such an embodiment, the data module  202  or the parameter module  204  may aggregate the various runway data sets, and calculate the runway condition parameters based on the aggregated data set. 
     In further embodiments, when the data module  202  receives a new runway data set from an airplane  110 , after the parameter module  204  has previously calculated the runway condition parameters, the parameter module  204  updates the previously calculated runway condition parameters, in real-time, based on the newly received data. In such an embodiment, the transmission module  206  may transmit the updated runway condition parameters to other airplanes  110  landing or taking off from the runway. In this manner, the runway condition apparatus  104  provides real-time, dynamic, and up-to-date runway condition information to pilots operating airplanes that are using the runway, e.g., to land and/or take off. 
       FIG. 3  depicts one embodiment of a system  300  for dynamically determining runway conditions. In one embodiment, the system  300  includes runway condition apparatuses  104 , an airport computing system  302 , a first airplane  304  that is communicatively coupled to the airport computing system  302  over a first network  305 , a runway  306 , and a second airplane  308  communicatively coupled to the airport computing system  302  over a second network  307 . 
     In one embodiment, when the first airplane  304  lands on the runway  306 , one or more sensors on the first airplane  304  start collecting, sampling, detecting, and/or the like data that may be used to determine conditions for the runway. For example, the sensors may collect braking force data, deceleration data, reverse thrust data, and/or other external environment data such as wind speed on the runway, surface temperature, and/or the like. The first airplane  304  may send the collected data to the airport computing system  302  over the first network  305 . 
     The data module  202  at the airport computing system  302  may receive the sampled data, e.g., on an ongoing basis while the first airplane  304  is landing and/or after the first airplane  304  has completed the landing process. The parameter module  204  at the airport computing system  302  calculates one or more parameters for describing the runway condition, e.g., a coefficient of friction for the runway, which the transmission module  206  at the airport computing system sends to the second airplane  308  over the second network  307 . The second airplane  308 , and/or the pilot(s) of the second airplane  308 , may then use the received data to make adjustments, settings, configurations, decisions, and/or the like regarding factors that are used when landing the airplane  308 . 
     In this manner, other airplanes that are preparing for landing (or take off) can use the received runway condition parameters to more accurately and safely land (or take off) the airplane based on the real-time conditions of the runway. The specific arrangement of devices, e.g., using a central airport computing system  302  that is connected to both the first airplane  304  and one or more second airplanes  308 , allows for efficient processing of the sensed runway data and efficient dissemination of the calculated parameters to other airplanes that are preparing to use the runway. 
       FIG. 4  is a schematic flow-chart diagram illustrating one embodiment of a method  400  for dynamically determining runway conditions. The method  400  begins, and receives  402 , at an airport computing system  302 , data from a first airplane  304  over a network  305 . In one embodiment, the data includes runway data that is sampled using a plurality of sensors located on the first airplane  304  while the first airplane  304  is on a runway  306 . 
     In certain embodiments, the method  400  determines  404  one or more parameters that describe a condition for the runway  306  based on the received runway data. In some embodiments, the method  400  transmits  406 , from the airport computing system  302 , the one or more parameters to one or more second airplanes  308  over a second network  307 , and the method  400  ends. In certain embodiments, the data module  202 , the parameter module  204 , and the transmission module  206  perform the various steps of the method  400 . 
       FIG. 5  is a schematic flow-chart diagram illustrating one embodiment of a method  500  for dynamically determining runway conditions. The method  500  begins and receives  502  runway data from a first airplane  304  landing on a runway  306  over a data network  305 . The method  500 , in certain embodiments, determines  504  an average braking force and an average deceleration for the first airplane  304  based on the runway data. The method  500 , in various embodiments, calculates  506  a coefficient of friction for the runway  306  based on the average braking force and the average deceleration of the first airplane  304  while it is landing. The method  500 , in one embodiment, sends  508  the calculated coefficient of friction to one or more second airplanes  308  over a second network  307 , and the method  500  ends. In certain embodiments, the data module  202 , the parameter module  204 , and the transmission module  206  perform the various steps of the method  500 . 
       FIG. 6  is a schematic flow-chart diagram illustrating one embodiment of a method  600  for dynamically determining runway conditions. The method  600  begins and receives  602  runway data from a first airplane  304  taking off from a runway  306  over a data network  305 . The method  600 , in certain embodiments, determines an average thrust and an average acceleration for the first airplane  304  based on the runway data. The method  600 , in various embodiments, calculates  606  a coefficient of friction for the runway  306  based on the average thrust and the average acceleration of the first airplane  304  while it is taking off. The method  600 , in one embodiment, sends  608  the calculated coefficient of friction to one or more second airplanes  308  over a network  307   n , and the method  600  ends. In certain embodiments, the data module  202 , the parameter module  204 , and the transmission module  206  perform the various steps of the method  600 . 
       FIG. 7  is a schematic flow-chart diagram illustrating one embodiment of a method  700  for dynamically determining runway conditions. The method  700  begins and receives  702  new runway data from a first airplane  304  over a data network  305 . The method  700 , in some embodiments, updates  704  a current or previously calculated runway condition parameter based on the new runway data. The method  700 , in various embodiments, sends  706  the updated runway condition parameters to one or more second airplanes  308  over a data network  307 , and the method  700  ends. In certain embodiments, the data module  202 , the parameter module  204 , and the transmission module  206  perform the various steps of the method  700 . 
     In the above description, certain terms may be used such as “up,” “down,” “upper,” “lower,” “horizontal,” “vertical,” “left,” “right,” “over,” “under” and the like. These terms are used, where applicable, to provide some clarity of description when dealing with relative relationships. But, these terms are not intended to imply absolute relationships, positions, and/or orientations. For example, with respect to an object, an “upper” surface can become a “lower” surface simply by turning the object over. Nevertheless, it is still the same object. Further, the terms “including,” “comprising,” “having,” and variations thereof mean “including but not limited to” unless expressly specified otherwise. An enumerated listing of items does not imply that any or all of the items are mutually exclusive and/or mutually inclusive, unless expressly specified otherwise. The terms “a,” “an,” and “the” also refer to “one or more” unless expressly specified otherwise. Further, the term “plurality” can be defined as “at least two.” 
     Additionally, instances in this specification where one element is “coupled” to another element can include direct and indirect coupling. Direct coupling can be defined as one element coupled to and in some contact with another element. Indirect coupling can be defined as coupling between two elements not in direct contact with each other, but having one or more additional elements between the coupled elements. Further, as used herein, securing one element to another element can include direct securing and indirect securing. Additionally, as used herein, “adjacent” does not necessarily denote contact. For example, one element can be adjacent another element without being in contact with that element. 
     As used herein, the phrase “at least one of”, when used with a list of items, means different combinations of one or more of the listed items may be used and only one of the items in the list may be needed. The item may be a particular object, thing, or category. In other words, “at least one of” means any combination of items or number of items may be used from the list, but not all of the items in the list may be required. For example, “at least one of item A, item B, and item C” may mean item A; item A and item B; item B; item A, item B, and item C; or item B and item C. In some cases, “at least one of item A, item B, and item C” may mean, for example, without limitation, two of item A, one of item B, and ten of item C; four of item B and seven of item C; or some other suitable combination. 
     Unless otherwise indicated, the terms “first,” “second,” etc. are used herein merely as labels, and are not intended to impose ordinal, positional, or hierarchical requirements on the items to which these terms refer. Moreover, reference to, e.g., a “second” item does not require or preclude the existence of, e.g., a “first” or lower-numbered item, and/or, e.g., a “third” or higher-numbered item. 
     As used herein, a system, apparatus, structure, article, element, component, or hardware “configured to” perform a specified function is indeed capable of performing the specified function without any alteration, rather than merely having potential to perform the specified function after further modification. In other words, the system, apparatus, structure, article, element, component, or hardware “configured to” perform a specified function is specifically selected, created, implemented, utilized, programmed, and/or designed for the purpose of performing the specified function. As used herein, “configured to” denotes existing characteristics of a system, apparatus, structure, article, element, component, or hardware which enable the system, apparatus, structure, article, element, component, or hardware to perform the specified function without further modification. For purposes of this disclosure, a system, apparatus, structure, article, element, component, or hardware described as being “configured to” perform a particular function may additionally or alternatively be described as being “adapted to” and/or as being “operative to” perform that function. 
     The schematic flow chart diagrams included herein are generally set forth as logical flow chart diagrams. As such, the depicted order and labeled steps are indicative of one embodiment of the presented method. Other steps and methods may be conceived that are equivalent in function, logic, or effect to one or more steps, or portions thereof, of the illustrated method. Additionally, the format and symbols employed are provided to explain the logical steps of the method and are understood not to limit the scope of the method. Although various arrow types and line types may be employed in the flow chart diagrams, they are understood not to limit the scope of the corresponding method. Indeed, some arrows or other connectors may be used to indicate only the logical flow of the method. For instance, an arrow may indicate a waiting or monitoring period of unspecified duration between enumerated steps of the depicted method. Additionally, the order in which a particular method occurs may or may not strictly adhere to the order of the corresponding steps shown. 
     Embodiments of the various modules may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, micro-code, etc.) or an embodiment combining software and hardware aspects that may all generally be referred to herein as a “circuit,” “module” or “system.” Furthermore, embodiments may take the form of a program product embodied in one or more computer readable storage devices storing machine readable code, computer readable code, and/or program code, referred hereafter as code. The storage devices may be tangible, non-transitory, and/or non-transmission. The storage devices may not embody signals. In a certain embodiment, the storage devices only employ signals for accessing code. 
     The modules may be implemented as a hardware circuit comprising custom very-large-scale integration (VLSI) circuits or gate arrays, off-the-shelf semiconductors such as logic chips, transistors, or other discrete components. The modules may also be implemented in programmable hardware devices such as field programmable gate arrays, programmable array logic, programmable logic devices or the like. 
     The modules may also be implemented in code and/or software for execution by various types of processors. An identified module of code may, for instance, comprise one or more physical or logical blocks of executable code which may, for instance, be organized as an object, procedure, or function. Nevertheless, the executables of an identified module need not be physically located together, but may comprise disparate instructions stored in different locations which, when joined logically together, comprise the module and achieve the stated purpose for the module. 
     Indeed, a module of code may be a single instruction, or many instructions, and may even be distributed over several different code segments, among different programs, and across several memory devices. Similarly, operational data may be identified and illustrated herein within modules, and may be embodied in any suitable form and organized within any suitable type of data structure. The operational data may be collected as a single data set, or may be distributed over different locations including over different computer readable storage devices. Where a module or portions of a module are implemented in software, the software portions are stored on one or more computer readable storage devices. 
     Any combination of one or more computer readable medium may be utilized by the modules. The computer readable medium may be a computer readable storage medium. The computer readable storage medium may be a storage device storing the code. The storage device may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, holographic, micromechanical, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. 
     More specific examples (a non-exhaustive list) of the storage device would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. 
     Code for carrying out operations for embodiments may be written in any combination of one or more programming languages including an object oriented programming language such as Python, Ruby, Java, Smalltalk, C++, or the like, and conventional procedural programming languages, such as the “C” programming language, or the like, and/or machine languages such as assembly languages. The code may execute entirely on the user&#39;s computer, partly on the user&#39;s computer, as a stand-alone software package, partly on the user&#39;s computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user&#39;s computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider). 
     The present subject matter may be embodied in other specific forms without departing from its spirit or essential characteristics. The described embodiments are to be considered in all respects only as illustrative and not restrictive. All changes which come within the meaning and range of equivalency of the claims are to be embraced within their scope.