Patent Publication Number: US-2015073697-A1

Title: Geographical location aggregation from multiple sources

Description:
PRIORITY PATENT APPLICATION 
     This is a continuation-in-part patent application of co-pending U.S. patent application Ser. No. 13/686,894; filed Nov. 27, 2012 by the same assignee as the present application. This present patent application draws priority from the referenced patent application. The entire disclosure of the referenced patent application is considered part of the disclosure of the present application and is hereby incorporated by reference herein in its entirety. 
    
    
     TECHNICAL FIELD 
     This patent document pertains generally to tools (systems, apparatuses, methodologies, computer program products, etc.) for processing geographical location data, and more particularly, but not by way of limitation, to a system and method for obtaining geographical location data from multiple sources and aggregating the geographical location data. 
     BACKGROUND 
     An increasing number of vehicles are being equipped with one or more independent computer and electronic processing systems. Certain of the processing systems are provided for vehicle operation or efficiency. For example, many vehicles are now equipped with computer systems for controlling engine parameters, brake systems, tire pressure and other vehicle operating characteristics. Other in-vehicle processing systems provide location-based services, such as navigation and proximity alerting. In support of these location-based services, many vehicles are being equipped with one or more global positioning system (GPS) devices. GPS devices use a well-known technology for receiving data and timing from satellites to determine a geographical location or geo-location. GPS receivers can provide location and time information in all weather, anywhere on or near the Earth, where there is an unobstructed line of sight to four or more GPS satellites. However, an unobstructed line of sight to four or more GPS satellites in a moving vehicle is not always practical. For example, tunnels, canyons, mountains, tall buildings, and the like can interfere with GPS signal reception. As a result, reliable geo-location data from in-vehicle GPS receivers can be intermittent, inaccurate, or lost altogether. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The various embodiments is illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings in which: 
         FIG. 1  illustrates a block diagram of an example vehicle data abstraction and communication system in which embodiments described herein may be implemented; 
         FIG. 2  illustrates an example embodiment of a cloud-based vehicle information and control ecosystem; 
         FIG. 3  illustrates the geo-location aggregation engine of an example embodiment; 
         FIG. 4  is a processing flow chart illustrating an example embodiment of systems and methods for providing a cloud-based vehicle information and control ecosystem; and 
         FIG. 5  shows a diagrammatic representation of machine in the example form of a computer system within which a set of instructions when executed may cause the machine to perform any one or more of the methodologies discussed herein. 
     
    
    
     DETAILED DESCRIPTION 
     In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the various embodiments. It will be evident, however, to one of ordinary skill in the art that the various embodiments may be practiced without these specific details. 
     As described in various example embodiments, a system and method for obtaining geographical location data from multiple sources and aggregating the geographical location data are described herein. In one particular embodiment, a geographical location aggregation system is provided in the context of a cloud-based vehicle information and control ecosystem configured and used like the ecosystem illustrated in  FIG. 2 . However, it will be apparent to those of ordinary skill in the art that the geographical location aggregation system described and claimed herein can be implemented, configured, and used in a variety of other applications and systems. 
     Particular example embodiments relate to the communication of signals and information and the activation of procedures and/or services between network resources, mobile devices, and Controller Area Network (CAN) buses in a vehicle. Embodiments disclosed herein generally can use the signals communicated between electronic control units (ECUs) of a vehicle, a controller platform, network-based mobile devices, such as mobile phones or mobile computing platforms, and network resources, such as server computers. Data signals communicated from the ECUs to the mobile devices or network resources may include information about the state of one or more of the components of the vehicle, including a geo-location fix or timing information from one or more GPS receivers installed in the vehicle. In particular, in some embodiments the data signals, which are communicated from the ECUs to the CAN bus, are abstracted by an automotive data abstraction and communication device (abstraction device). The abstraction device connects directly to an On Board Diagnostics (OBD) connector that enables access to the CAN bus. The abstraction device converts the data signals from a vehicle-specific format to a mobile device format defined by an Application Programming Interface (API). The abstraction device then wirelessly and securely transmits the data signals to the mobile device and/or a network resource. By converting the data signals to the mobile device format, the mobile device may use the data signals without knowing the vehicle-specific or GPS-specific format. Additionally, the mobile device format defined by the API exposes the data signals, ECUs and other vehicle hardware and software in a standardized way, thereby enabling multiple vendors or software developers to create mobile device applications that process the data signals. In the same way, the API can expose the data signals, ECUs and other vehicle hardware and software in a standardized way for the network resources. 
     Additionally, a user of the mobile device and/or a network resource can send a write or control signal from the mobile device and/or network resource through the abstraction device to the CAN bus. The write/control signal enables the user of the mobile device and/or network resource to alter the state of one or more components included in the vehicle. The write signal is formatted in the mobile device format defined by the API and wirelessly transmitted to the abstraction device. The abstraction device converts the write/control signal to the vehicle-specific format and communicates the write signal to the vehicle. By converting the write signal from the mobile device format defined by the API to the vehicle-specific format or GPS receiver-specific format, the abstraction device may interface with multiple vehicles. Additionally, the mobile device format defined by the API acts as a common programming language enabling multiple vendors to write mobile device and/or network resource applications that may communicate read and write signals to multiple types of vehicles independent of the model or manufacturer. In this manner, a mobile device, a network resource, or other vehicle subsystems can have access to geo-location data generated by an in-vehicle GPS receiver, by an in-vehicle dead reckoning subsystem, by a mobile device geo-location subsystem, or by a network resource geo-location subsystem. In the various example embodiments described in more detail below, the geo-location data generated by a variety of sources can be shared with a variety of other subsystems in the cloud-based vehicle information and control ecosystem. As a result, a more accurate geo-location can be determined based on an aggregate of the geo-location information obtained from a plurality of sources. 
     As used herein, the term “CAN bus,” refers to any bus used in a vehicle for communicating signals between ECUs or components, including automotive standards or other standards like MOST, LIN, I2C and Ethernet. The CAN bus may be a bus that operates according to versions of the CAN specification, but is not limited thereto. The term “CAN bus” can therefore refer to buses that operate according to other specifications, including those that might be developed in the future. 
     As used herein and unless specified otherwise, the term “mobile device” extends to any device that can communicate with the abstraction devices described herein to obtain read or write access to messages or data signals communicated on a CAN bus or via any other mode of inter-process data communications. In many cases, the mobile device is a handheld, portable device, such as a smart phone, mobile phone, cellular telephone, tablet computer, laptop computer, display pager, radio frequency (RF) device, infrared (IR) device, global positioning system (GPS) device, Personal Digital Assistants (PDAs), handheld computers, wearable computer, portable game console, other mobile communication and/or computing device, or an integrated device combining one or more of the preceding devices, and the like. Additionally, the mobile device can be a computing device, personal computer (PC), multiprocessor system, microprocessor-based or programmable consumer electronic device, network PC, diagnostics equipment, a system operated by a vehicle manufacturer or service technician, and the like, and is not limited to portable devices. The mobile device can receive and process data in any of a variety of data formats. The data format may include or be configured to operate with any programming format, protocol, operating system, or language including, but not limited to, JavaScript, C++, iOS, Android, etc. 
     As used herein and unless specified otherwise, the term “network resource” extends to any device, system, or service that can communicate with the abstraction devices described herein to obtain read or write access to messages or data signals communicated on a CAN bus or via any other mode of inter-process or networked data communications. In many cases, the network resource is a data network accessible computing platform, including client or server computers, websites, mobile devices, peer-to-peer (P2P) network nodes, and the like. Additionally, the network resource can be a web appliance, a network router, switch, bridge, gateway, diagnostics equipment, a system operated by a vehicle manufacturer or service technician, or any machine capable of executing a set of instructions (sequential or otherwise) that specify actions to be taken by that machine. Further, while only a single machine is illustrated, the term “machine” can also be taken to include any collection of machines that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein. The network resource may include any of a variety of providers or processors of network transportable digital content. Typically, the file format that is employed is Extensible Markup Language (XML), however, the various embodiments are not so limited, and other file formats may be used. For example, data formats other than Hypertext Markup Language (HTML)/XML or formats other than open/standard data formats can be supported by various embodiments. Any electronic file format, such as Portable Document Format (PDF), audio (e.g., Motion Picture Experts Group Audio Layer 3—MP3, and the like), video (e.g., MP4, and the like), and any proprietary interchange format defined by specific content sites can be supported by the various embodiments described herein. 
     The data network (also denoted the network cloud) used with the network resources can be configured to couple one computing or communication device with another computing or communication device. The network may be enabled to employ any form of computer readable data or media for communicating information from one electronic device to another. The network can include the Internet in addition to other wide area networks (WANs), metro-area networks, local area networks (LANs), other packet-switched networks, circuit-switched networks, direct data connections, such as through a universal serial bus (USB) or Ethernet port, other forms of computer-readable media, or any combination thereof. On an interconnected set of networks, including those based on differing architectures and protocols, a router or gateway can act as a link between networks, enabling messages to be sent between computing devices on different networks. Also, communication links within networks can typically include twisted wire pair cabling, USB, Firewire, Ethernet, or coaxial cable, while communication links between networks may utilize analog or digital telephone lines, full or fractional dedicated digital lines including T1, T2, T3, and T4, Integrated Services Digital Networks (ISDNs), Digital User Lines (DSLs), wireless links including satellite links, cellular telephone links, or other communication links known to those of ordinary skill in the art. Furthermore, remote computers and other related electronic devices can be remotely connected to the network via a modem and temporary telephone link. 
     The network may further include any of a variety of wireless sub-networks that may further overlay stand-alone ad-hoc networks, and the like, to provide an infrastructure-oriented connection. Such sub-networks may include mesh networks, Wireless LAN (WLAN) networks, cellular networks, and the like. The network may also include an autonomous system of terminals, gateways, routers, and the like connected by wireless radio links or wireless transceivers. These connectors may be configured to move freely and randomly and organize themselves arbitrarily, such that the topology of the network may change rapidly. 
     The network may further employ a plurality of access technologies including 2nd (2G), 2.5, 3rd (3G), 4th (4G) generation radio access for cellular systems, WLAN, Wireless Router (WR) mesh, and the like. Access technologies such as 2G, 3G, 4G, and future access networks may enable wide area coverage for mobile devices, such as one or more of client devices, with various degrees of mobility. For example, the network may enable a radio connection through a radio network access, such as Global System for Mobile communication (GSM), General Packet Radio Services (GPRS), Enhanced Data GSM Environment (EDGE), Wideband Code Division Multiple Access (WCDMA), CDMA2000, and the like. The network may also be constructed for use with various other wired and wireless communication protocols, including TCP/IP, UDP, SIP, SMS, RTP, WAP, CDMA, TDMA, EDGE, UMTS, GPRS, GSM, UWB, WiMax, IEEE 802.11x, and the like. In essence, the network may include virtually any wired and/or wireless communication mechanisms by which information may travel between one computing device and another computing device, network, and the like. 
     In a particular embodiment, a platform system and/or a mobile device with network access may act as a client device enabling a user to access and use the cloud-based vehicle information and control system via the network. These client devices may include virtually any computing device that is configured to send and receive information over a network, such as network ecosystem as described herein. Such client devices may include mobile devices, such as cellular telephones, smart phones, tablet computers, display pagers, radio frequency (RF) devices, infrared (IR) devices, global positioning devices (GPS), Personal Digital Assistants (PDAs), handheld computers, wearable computers, game consoles, integrated devices combining one or more of the preceding devices, and the like. The client devices may also include other computing devices, such as personal computers (PCs), multiprocessor systems, microprocessor-based or programmable consumer electronics, network PC&#39;s, and the like. As such, client devices may range widely in terms of capabilities and features. For example, a client device configured as a cell phone may have a numeric keypad and a few lines of monochrome LCD display on which only text may be displayed. In another example, a web-enabled client device may have a touch sensitive screen, a stylus, and a color LCD display screen in which both text and graphics may be displayed. Moreover, the web-enabled client device may include a browser application enabled to receive and to send wireless application protocol messages (WAP), and/or wired application messages, and the like. In one embodiment, the browser application is enabled to employ HyperText Markup Language (HTML), Dynamic HTML, Handheld Device Markup Language (HDML), Wireless Markup Language (WML), WMLScript, JavaScript, EXtensible HTML (xHTML), Compact HTML (CHTML), and the like, to display and send a message with relevant information. 
     The client devices may also include at least one client application that is configured to receive content or messages from another computing device via a network transmission. The client application may include a capability to provide and receive textual content, graphical content, video content, audio content, alerts, messages, notifications, and the like. Moreover, the client devices may be further configured to communicate and/or receive a message, such as through a Short Message Service (SMS), direct messaging (e.g., Twitter), email, Multimedia Message Service (MMS), instant messaging (IM), internet relay chat (IRC), mIRC, Jabber, Enhanced Messaging Service (EMS), text messaging, Smart Messaging, Over the Air (OTA) messaging, or the like, between another computing device, and the like. The client devices may also include a wireless application device on which a client application is configured to enable a user of the device to send and receive information to/from network resources wirelessly via the network. 
       FIG. 1  illustrates a block diagram of an example vehicle data abstraction and communication system  100  in which components of the embodiments described herein may be implemented.  FIG. 1  depicts an example of an operating environment for the vehicle data abstraction and communication systems described herein.  FIG. 1  also illustrates an example embodiment in which a mobile device  102  is identified as having an authentication level that permits the mobile device  102  to have access to higher-level events mapped from CAN messages, as opposed to being given direct access to raw CAN messages. 
     In  FIG. 1 , the system  100  includes a vehicle  104 , an abstraction device  122 , and a mobile device  102 . Generally,  FIG. 1  depicts the communication of data signals from the vehicle  104  to the abstraction device  122  and to the mobile device  102 . Some of the data signals can be produced at the vehicle  104 , the format of the data signals are converted at the abstraction device  122 , and the data signals are processed at the mobile device  102 . 
       FIG. 1  depicts a system  100  that includes the vehicle  104 . The systems and methods described herein can be used with substantially any mechanized system that uses a CAN bus as defined herein, including, but not limited to, industrial equipment, boats, trucks, or automobiles; thus, the term “vehicle” extends to any such mechanized systems. The systems and methods described herein can also be adapted for use with other devices that have accessible data, such as medical equipment. The systems and methods described herein can also be used with any systems employing some form of network data communications. 
     In a particular embodiment related to a cloud-based vehicle information and control ecosystem, vehicle  104  may include multiple automotive components  118 A- 118 N (generally, a component  118  or components  118 ). The components  118  include the individual apparatuses, systems, subsystems, mechanisms, etc. that are included in the vehicle  104 . The components  118  may include, but are not limited to, windows, door locks, oxygen sensors, an ignition system, windshield wipers, brakes, engines, GPS and navigation systems, a tachometer, etc. 
     The vehicle  104  may additionally include one or more electronic control units  120 A- 120 N (an ECU  120  or ECUs  120 ). The ECUs  120  are associated with the components  118 . As used with respect to the relationship between the ECUs  120  and the components  118 , the term “associated with” may refer to the component  118  including an ECU  120 , the component  118  being coupled to an ECU  120  for monitoring a state of the component  118 , the ECU  120  controlling the component  118 , or some combination thereof. As illustrated in  FIG. 1 , one ECU  120  is associated with one component  118 . However, this depiction is not meant to be limiting. In some embodiments, one ECU  120  may be associated with multiple components  118 . Additionally or alternatively, multiple ECUs  120  may be associated with a single component  118 . Additionally or alternatively, some embodiments include ECUs  120  associated with some subset of ECUs  120 , etc. 
     In  FIG. 1 , a first component  118 A is associated with a first ECU  120 A, a second component  118 B is associated with a second ECU  120 B, and an Nth component  118 N is associated with an Nth ECU  120 N. The inclusion of the Nth component  118 N, the Nth ECU  120 N, and the ellipses is meant to indicate that the number of components  118  and/or ECUs  120  are not limited. That is, the vehicle  104  may include hundreds or thousands of components  118  and/or ECUs  120 , for instance. 
     In the particular embodiment shown in  FIG. 1 , the first ECU  120 A associated with the first component  118  may monitor the first component  118 . The ECU  120 A may communicate a state or a condition of the first component as a data signal to the CAN bus  116 . For example, if the first component  118 A was the steering wheel, the first ECU  120 A may communicate the radial position of the steering wheel in real time to the CAN bus  116 . For another example, if the first component  118 A was an in-vehicle GPS device, the first ECU  120 A may communicate the geo-location of the vehicle in real time to the CAN bus  116 . Similarly, the second ECU  120 B and the Nth ECU  120 N may communicate the data signals to the CAN bus  116  regarding the state or the condition of the second component  118 B and the Nth component  120 N, respectively. Accordingly, the data signals may include, but are not limited to, the geo-location of the vehicle based on data reported from a GPS device, the speed of the vehicle, the distance traveled by the vehicle since engine start, the direction of travel of the vehicle, the current vehicle heading, the direction information reported by an in-vehicle compass, positions of the vehicle windows, positions of the vehicle door locks, oxygen levels measured in the oxygen sensors, ignition timing, state of the windshield wipers, a position of the steering wheel, RPM of the engine, and the like. 
     The data signals may be formatted in a vehicle-specific format—i.e., specific to a vehicle make and model. The vehicle-specific format generally refers to the format of the data signals for the vehicle  104 . That is, the vehicle  104  may be manufactured by a first manufacturer that may have a vehicle-specific format for all its vehicles. Alternatively, the first manufacturer may have a vehicle-specific format for different models, years, option packages, etc. Generally, the vehicle-specific formats of different vehicles  104  are not the same. Thus, a vehicle manufactured by the first manufacturer typically has a different vehicle-specific format that a second vehicle manufactured by a second manufacture. Additionally or alternatively, in some embodiments, the data signals may be differential signals. 
     The CAN bus  116  receives the data signals from the ECUs  120 . Additionally, the CAN bus  116  may enable the components  118  or some subset thereof to internally communicate without an additional computer system. Thus, data signals received at the CAN bus  116  may be available for download, may be internally communicated within the vehicle  104 , or may be dropped. 
     In some embodiments, the CAN bus  116  may be coupled to a bus connector  126  that enables access to the CAN bus  116 . For example, in this and other embodiments, the vehicle  104  may include an On Board Diagnostics (OBD) connector. The bus connector may be configured according to an OBD II specification, for instance. In embodiments with multiple CAN buses  116 , the vehicle  104  may include multiple bus connectors  126  and/or alternative bus connectors that enable access to one or more CAN buses  116 . In most modern vehicles, the CAN bus  116  includes the bus connector  126  located under the hood or accessible through the removal of a panel in the cabin of the vehicle  104 . However, embodiments described herein can be implemented by using connector  124  that connects with CAN bus  116  in any available way. 
     The data signals or some subset thereof may be communicated to the abstraction device  122 . In some embodiments, the abstraction device  122  is a discrete unit that can be adapted for use with one or more existing or new vehicles  104 . For example, as explained herein, the abstraction device  122  can be embodied in a discrete unit that can be installed in an existing or new vehicle  104  by connecting it to the bus connector  126  (e.g., an OBD II connector) associated with CAN bus  116 . In this way, the methods and systems described herein can be easily used with substantially any new or existing vehicle  104  that includes a CAN bus  116 . 
     In other embodiments, the abstraction device  122  or elements thereof may be integrated into new vehicles or retrofitted into an existing vehicle. Under this approach, the elements of the abstraction device  122  are a substantially permanent system of vehicle  104 . In this case, abstraction device  122  can replace or supplement the bus connector  126  that may otherwise be present in the vehicle  104 . In these embodiments, the abstraction device  122  may be a platform within a larger apparatus or system or may be an integrated circuit with controllers and/or microcontrollers that manage or dictate the function of the abstraction device  122 . 
     The abstraction device  122  couples with the bus connector  126  associated with the CAN bus  116  via a connector  124 . For example, the CAN bus  116  may have a bus connector  126  (e.g., an OBD II connector) that is adapted to connect with the connector  124  or the abstraction device  122  may include the connector adapted to interface with the bus connector  126 . Generally, the interface between the connector  124  and the bus connector  126  includes a physical connection as well as an electrical interface such that the data signals communicated to the CAN bus  116  may be further communicated to the abstraction device  122 . 
     When connected to the CAN bus  116 , the connector  124  may communicate the data signals to mapping platform  112 . Generally, the mapping platform  112  may be configured to convert a data signal from the vehicle-specific format into a mobile device format and/or a network resource format defined by an Application Programming Interface (API). Additionally, in some embodiments, the API included in the mapping platform  112  may enable the conversion of data signals from multiple vehicle-specific formats to the mobile device format and/or a network resource format. Thus, the mapping platform  112  may not be specific to the vehicle  104 . Some additional details of the mapping platform  112  and the API are discussed with reference to  FIG. 3 . 
     Alternatively, in some embodiments, the abstraction device  122  may include one or more controllers  114  that may be configured to receive one or more data signals from the CAN bus  116 . The controller  114  may then communicate the data signals to the mapping platform  112 . 
     In the example embodiment of  FIG. 1 , the abstraction device  122  may include a certification module  108  configured to limit access to the data signal converted to the mobile device format by the mapping platform  112 . In the example of  FIG. 1 , the certification module  108  determines that mobile device  102  is authenticated at a level that permits the mobile device  102  to access events mapped from the CAN messages by the mapping platform  112 . In this way, mobile device  102 , in this example, is prevented from having full access to the raw CAN messages, thereby substantially limiting the ability of mobile device  102  to perform action that might damage the vehicle  104  or put the passengers in danger. 
     As shown in  FIG. 1 , the transceiver  110  (“Tx/Rx” in  FIG. 1 ) may receive an identification signal from the mobile device  102  and/or a mobile device application  106  on the mobile device  102 . The communication of the identification signal is indicated by the arrow  128  in  FIG. 1 . The identification signal  128  may include one or more privileges possessed by the mobile device  102  and/or the mobile device application  106 . For example, the mobile device  102  may be owned or operated by a mechanic who may have a specific privilege without authentication of the specific mobile device application  106  or the specific mobile device application  106  may include a privilege. Some examples of privileges may include one or more read privileges and/or one or more write privileges. The identification signal  128  may be communicated from the transceiver  110  to the certification module  108 . The certification module  108  may verify or authenticate whether the mobile device  102  and/or the mobile device application  106  includes a specific privilege. 
     Abstraction device  122  can be implemented using systems that enhance the security of the execution environment, thereby improving security and reducing the possibility that the abstraction device  122  and the related services could be compromised by viruses or malware. For example, abstraction device  122  can be implemented using a Trusted Execution Environment, which can ensure that sensitive data is stored, processed, and communicated in a secure way. 
     As stated above, the transceiver  110  may receive data signals that have been converted to the mobile device format and/or a network resource format defined by the API. The transceiver  110  may then communicate the data signals formatted in the mobile device format to the mobile device  102 . In  FIG. 1 , the communication of the data signal to the mobile device  102  is represented by arrow  130 A. More specifically, in this and other embodiments, the transceiver  110  may be configured to wirelessly communicate the data signal in the mobile device format to the mobile device  102 . The transceiver  110  may include several configurations. In this and other embodiments, the transceiver  110  may include: a wireless receiver to receive identification signals and/or write signals from the mobile device  102 ; another receiver to receive the data signals from the mapping platform  112 ; a wireless transmitter to communicate the data signals in the API to the mobile device  102 ; and another transmitter that communicates identification signals to the communication module  108  and/or write signals to the mapping platform  112 . In some embodiments, the transceiver  110  includes a Bluetooth transceiver. 
     Additionally in some embodiments, the transceiver  110  may establish a secure channel between the abstraction device  122  and the mobile device  102 . In addition to or alternative to the secure channel, the abstraction device  122  may encrypt the data signals formatted in the mobile device format. The mobile device  102  may decrypt the data signals. The inclusion of the secure channel and/or encryption may enhance security of the data signals communicated to the mobile device  102 . 
     The mobile device  102  receives the data signals communicated from the abstraction device  122 . In embodiments in which the transceiver  110  wirelessly communicates the data signals to the mobile device  102 , the mobile device  102  can include wireless capabilities such as Bluetooth, Wi-Fi, 3G, 4G, LTE, etc. For example, if the transceiver  110  includes a Bluetooth transceiver, the mobile device  102  includes Bluetooth capabilities. Generally, the mobile device  102  includes one or more mobile device applications  106  that process the data signals. The mobile device application  106  may be loaded, downloaded, or installed on the mobile device  102 . Alternatively, the mobile device  102  may access the mobile device application  106  via a network cloud or internet browser, for example. The mobile device application  106  may also be accessed and used as a Software as a Service (SaaS) application. The mobile device application  106  may be written or created to process data signals in the mobile device format rather than the vehicle-specific format. Accordingly, the mobile device application  106  may be vehicle-agnostic. That is, the mobile device application  106  may process data signals from any vehicle  104  once the data signals formatted in the vehicle-specific format are converted by the mapping platform  112 . 
     In some embodiments, the mobile device application  106  includes an ability to perform an API call. The API call is represented in  FIG. 1  by arrow  132 A. The API call  132 A may be an integrated portion of the mobile device application  106  and may allow a user of the mobile device  102  to request data signals from the vehicle  104 . The API call  132 A may be communicated to the transceiver  110 , which then relays the content of the API call  132 A through the mapping platform  112 , which converts the requested data signals to the mobile device format. The requested data signals are transmitted to the mobile device  102 . In other embodiments, a remote procedure call (RPC) can be used to request data or invoke a function using an inter-process communication that allows a mobile device application  106 , for example, to cause a sub-process or procedure to execute in a vehicle component  118  or the abstraction device  122 . 
     By processing the data signals, the mobile device application  106  may function better than a mobile device application without the data signals or may be able to provide functionality not possible without the data signals. For example, the mobile device applications  106  may include a navigation application. The navigation application may receive GPS signals as well as data signals related to a radial position of the steering wheel, an angle of the tires, a speed, etc. of the vehicle  104 . The navigation application may process the GPS signals as well as the data signals from the vehicle  104 . Thus, the navigation application may output more accurate navigation data than another navigation application that only processes GPS signals. 
     Additionally or alternatively, the mobile device application  106  may enable abstraction of data signals for aggregate uses. For some aggregate uses, the mobile device application  106  may sync with one or more secondary systems (not shown). For example, the mobile device  102  may abstract data signals related to states of the windshield wipers. The mobile device  102  may communicate with a secondary system that determines weather patterns based on the state of windshield wipers in multiple vehicles in a given location at a given time. 
     Examples of the mobile device applications  106  are not limited to the above examples. The mobile device application  106  may include any application that processes, abstracts, or evaluates data signals from the vehicle  104  or transmits write/control signals to the vehicle  104 . 
     Referring now to  FIG. 2 , a cloud-based vehicle information and control ecosystem  201  is illustrated. In an example embodiment, the communication path between a mobile device and the subsystems of a vehicle as described above can be expanded into a cloud-based vehicle information and control ecosystem that brings the full power of the Web to bear on enhancing the driving experience. In the particular example embodiment shown in  FIG. 2 , the ecosystem  201  can be partitioned into three layers: an application layer (first layer), a framework layer (second layer), and a platform layer (third layer). The application layer represents the most abstract and broad level of the vehicle information and control system. The application layer can include a vehicle information and control system  210 , which can provide several subsystems including a map or geo-location-based support subsystem  212 , a user or people/communication-based support subsystem  214 , a media (e.g., audio or video) support subsystem  216 , and a vehicle subsystem  218 . These subsystems provide support for a variety of vehicle, driver, passenger, and 3 rd  party applications, such as geo-navigation, in-vehicle control of media, hands-free communication, monitoring and control of various vehicle systems and components, convergence of social communities with vehicle operation, mining of vehicle and/or driving related data from a single vehicle or thousands of vehicles. The application layer can be in data communication with content sources  240  via the network cloud  205  directly or via one or more apps (software application modules)  242  configured to process and serve data and services from a particular content source  240 . The network cloud  205  represents one or more of the various types of data networks described above, such as the Internet, cellular telephone networks, or other conventional data networks and related network protocols. The content sources  240  represent a type of the network resources (e.g., server computers, websites, etc.) described above. In an example embodiment, the application layer is configured to provide information access and control to users from a variety of user devices via local or remote data communications. 
     Additionally, the application layer can provide a user interface server  220  to support human interaction with the various applications of the application layer. In a particular embodiment, the user interface server  220  can include: a map or geo-location-based support subsystem interface  222 , a user or people/communication-based support subsystem interface  224 , a media (e.g., audio or video) support subsystem interface  226 , and a vehicle subsystem interface  228 . The user interface server  220  can be in data communication with the vehicle information and control system  210  via the network cloud  205 . The user interface server  220  can also be in data communication with content sources  240  via the network cloud  205 . 
     In an example embodiment, the map or geo-location-based support subsystem  212  and its related interface  222  provides information and services to support in-vehicle navigation, mapping, routing, location searching, proximity alerting, and a variety of functions related to geo-location. One of the components  118  of the vehicle  104  can include a global positioning system (GPS) device that can produce a geo-coordinate position of the vehicle  104  at any point in time. Alternatively or in addition, a GPS device can be available in a mobile device that is accessible to one of the components  118  of the vehicle  104 . The data from these one or more GPS devices is accessible to the geo-location-based support subsystem  212  using the data transfer mechanisms described above. The geo-location-based support subsystem  212  can use this geo-coordinate position of the vehicle  104  to correlate the locations of points of interest in proximity to the location of the vehicle. The locations of these points of interest can be obtained from a locally maintained database or from any of the network resources accessible via the network cloud  205 . The geo-location-based support subsystem interface  222  can present these points of interest to an occupant of the vehicle  104  using the data transfer mechanisms described above. The occupant of the vehicle can select one or more points of interest and the geo-location-based support subsystem  212  can generate mapping, navigation, and routing information related to the selected points of interest. The geo-location-based support subsystem interface  222  can also generate alerts to notify the vehicle occupant of the proximity of a point of interest. 
     In an example embodiment, the user or people/communication-based support subsystem  214  and its related interface  224  provides information and services to support interactions and communications between people. These interactions and communications can include in-vehicle wireless telephone communications, messaging, texting, social network updates (e.g., Facebook, Twitter, etc.), contact list management, conferencing, and the like. The user or people/communication-based support subsystem  214  can also coordinate with the geo-location-based support subsystem  212  to correlate the geo-locations of people of interest and generate corresponding alerts. The people of interest can be determined or user-specified based on contact lists, social network profiles, network resource searches, and the like. 
     In an example embodiment, the media (e.g., audio or video) support subsystem  216  and its related interface  226  provides information and services to support the search, selection, purchase, and playing of audio, video, or other media selections in the vehicle. One of the components  118  of the vehicle  104  can include a media player, which can receive content for playback from a traditional antennae source, an optical disc source (e.g., compact disc—CD), magnetic tape, or the like. Additionally, the media player can include a dock or physical interface for receiving a portable MP3 player, cellular telephone, or other mobile device. The media player can be configured to play or record media content from these mobile devices. Moreover, the media player can include an interface for search, selection, purchase, and playing of audio, video, or other media selections from a network resource. In this manner, any media content available in the network cloud  205  can be streamed or downloaded to a media player and played or recorded in the vehicle. 
     In an example embodiment, the vehicle subsystem  218  and its related interface  228  provides information and services to support the monitoring, configuration, and control of vehicle subsystems. As described above, the components  118  of the vehicle  104  can include a variety of vehicle subsystems and related ECUs. The status of these vehicle subsystems can be communicated through the abstraction layers shown in  FIG. 2  as described above. The vehicle subsystem  218  can receive these vehicle subsystem status signals and process these signals in a variety of ways. Similarly, vehicle control signals generated by the vehicle subsystem  218  and its related interface  228  can be communicated through the abstraction layers shown in  FIG. 2  as described above. These control signals can be used by one or more components  118  of the vehicle  104  to configure and control the operation of the one or more components  118 . 
     Referring still to  FIG. 2 , the framework layer represents a set of interfaces and control subsystems supporting the application layer and platform layer to which the framework layer is connected. The framework layer provides a lower level of abstraction for servicing a particular type of device, such as a mobile device  102  and the mobile apps  160  therein. The framework layer can provide a user interface server  250  to support human interaction with the various applications of the application layer via a map or location-based support subsystem interface  252 , a user or people/communication-based support subsystem interface  254 , a media support subsystem interface  256 , and a vehicle subsystem interface  258 . In one embodiment, the user interface server  250  at the framework layer can substantially mirror the functionality provided by the user interface server  220  at the application layer, except the user interface server  250  can be implemented in a smaller footprint (e.g., requires less memory and less processing power). As a result, the user interface server  250  may have less robust functionality or a reduced level of functionality with respect to subsystems of the user interface server  250  and corresponding subsystems of user interface server  220 . However, the user interface server  250  can still provide support (albeit a reduced level of functionality) for vehicle and/or driver applications even when connection with the network cloud  205  is interrupted, intermittent, or temporarily lost. Thus, the framework layer is well-suited, though not exclusively suited, to a mobile environment where uninterrupted access to the network cloud  205  cannot always be assured. When access to the network cloud  205  is available, the full support of the vehicle and/or driver applications can be provided by the components of the application layer. When access to the network cloud  205  is not available or not reliable, a somewhat reduced level of support of the vehicle and/or driver applications can still be provided by the components of the framework layer without network cloud  205  connectivity. As shown in  FIG. 2 , the user interface server  250  can provide a user interface for the mobile apps executing on a mobile device  102 . Because the user interface server  250  is in data communications with the components  118  of the vehicle  104  via the platform system  270  (described below), the user interface server  250  can provide any data or vehicle status signals needed by a mobile device app  106 . Similarly, the user interface server  250  can communicate any control signals or configuration parameters from the mobile device app  106  to a corresponding component  118  via the platform system  270 . 
     The platform layer represents a variety of components designed to reside on or with a platform system  270 , which is typically installed on or in a vehicle, such as the vehicle  104  described above. As shown in  FIG. 2 , the platform system  270 , of an example embodiment, can include a cloudcast subsystem  272 , a carlink subsystem  274 , a platform operating system  276 , and a virtualization module  278 . The platform operating system  276  can provide an execution environment for the platform system  270  components and interfaces to low-level hardware. The platform operating system  276  can execute platform apps  105  to process platform system  270  data and/or data captured from the ECUs of the vehicle. The virtualization module  278  can provide a logical abstraction or virtualization of the resources (hardware or software functional components) installed with or accessible to the platform system  270 . The cloudcast subsystem  272  provides a variety of technologies and/or interfaces with which the platform system  270  can, for example, decode data and/or a media stream for presentation to vehicle occupants. In a particular embodiment, the platform system  270  can be implemented as the abstraction device  122  shown in  FIG. 1  and described above. 
     Geo-Location Data Collection and Aggregation 
     Conventional technologies provide a process for mixing the signals produced by a GPS receiver and signals produced by dead reckoning subsystems. Dead reckoning subsystems refer to vehicle subsystems, such as speed sensors, distance measuring systems, gyroscopes, inertial navigation systems, and the like. For example, an article by Georg zur Bonsen, Daniel Ammann, Michael Ammann, Etienne Favey, and Pascal Flammant, titled, “Combining GPS with Sensor-Based Dead Reckoning”, GPS World, Apr. 1, 2005 describes computing a weighted mix of GPS data and dead reckoning data. The algorithmic approach can be embedded into an enhanced Kalman filter. This approach eliminates multipath effects, position jumps, and distortions from jamming sources. Depending on the quality of the GPS signal (indicated, for example, by the number and distribution of visible satellites, dilution-of-precision value, etc.) and on the confidence level of the dead reckoning signal (that is, how well the sensors are calibrated at the moment), a weighted mix of both GPS and dead reckoning can be chosen to generate better results. In practice, this approach can provide uninterrupted, reliable navigation results in the most challenging urban environments including New York, Hong Kong, and Tokyo. However, for accurate dead reckoning, calibration is required for the odometer pulses and the gyroscope. Different vehicle models provide signals with different wheel pulses per unit distance. The dead reckoning software must match the wheel pulses with the distance traveled as measured with some reference, such as GPS. Calibration must be an ongoing process to account for small variations, such as those due to changing tires. In regard to the gyroscope, two parameters need to be calibrated: voltage offset and volts per degrees per second. Furthermore, the gyroscope exhibits temperature-dependent characteristics and aging effects. The on-going calibration process during normal operation must compensate for the aging effects. Thus, for a number of reasons, dead reckoning can be subject to inaccuracies. Even when signals produced by a GPS receiver and signals produced by dead reckoning subsystems are mixed, the errors persist, particularly when the GPS data becomes intermittent, interrupted, or unreliable. 
     The various embodiments described herein provide a system and method for obtaining geographical location data from multiple sources and aggregating the geographical location data to produce a more accurate geo-location fix. As described above, the geo-location data from one or more in-vehicle device subsystems can be obtained by one or more corresponding ECU(s) and communicated up the layers of the cloud-based vehicle information and control ecosystem  201 . These in-vehicle device subsystems can include GPS receivers, dead reckoning subsystems, and other subsystems from which geo-location data can be extracted. 
     Furthermore, as described in more detail below, the layers of the cloud-based vehicle information and control ecosystem  201  can also provide access to GPS receivers, other geo-location sensing devices, or other geo-location data sources that may be available in the mobile devices of the occupants of the vehicle or available from network-based geo-location data sources. As described above and shown in  FIG. 2 , the framework layer, and the user interface server  250  therein, provides wireless access to a mobile device  102 , which can include a GPS receiver from which GPS data can be extracted. Clearly, the GPS data obtained from the mobile device  102  is generated by a different GPS receiver than the GPS data obtained from an in-vehicle GPS receiver via a corresponding ECU. Moreover, and separate from the mobile device resident GPS receiver, mobile devices can be used for determining geo-location using other techniques. For example, cell tower triangulation can be used to determine the location of a cellular telephone merely based on the location of the cell towers that are receiving a wireless signal from the cellular telephone at any point in time. Similarly, many modern mobile devices are enabled for WiFi wireless network access. These mobile devices emit WiFi signals, which can be received and processed by a wireless router or other WiFi access point (WAP), if the router or WAP is within the range of the mobile device&#39;s WiFi signals. The router or WAP can be used by the WiFi-enabled mobile device to connect to a wide area network, such as the Internet. The location of the router or WAP can also be used to determine the geo-location of the mobile device, if the mobile device is within range of the router or WAP. Techniques for determining the location of a mobile device based on a mobile device resident GPS receiver, cell tower triangulation, or WiFi WAP proximity are well-known to those of ordinary skill in the art. As shown in  FIG. 2 , the framework layer, and the user interface server  250  therein, provides wireless access to a mobile device  102  and can use these various techniques for determining the location of a mobile device  102 . As described in more detail herein, the location of a mobile device  102  can be shared with other layers and other subsystems for comparing and cross-checking location information obtained from other sources. 
     The application layer of the cloud-based vehicle information and control ecosystem  201 , the vehicle information and control system  210 , and user interface server  220  provide access to a variety of content sources  240  via network  205 , which can represent network-based geo-location data sources. The network  205  can include the Internet. These network-based geo-location sources can provide a variety of geo-location data and reliability data, which can be used to reference or calibrate the geo-location fix received from a different source, particularly a source in a vehicle. For example, network-based geo-location sources, such as servers, websites, network nodes, and the like, can provide map data. The map data can be used to locate checkpoints at known geo-location fixes. These checkpoints and their corresponding geo-location fixes can be used to compare with the GPS data produced by a GPS receiver positioned at the checkpoint. Additionally, other checkpoints or locations with a known geo-location can be used as geo-location reference points. For example, a gas station, a city landmark, or a WiFi hotspot with a known geo-location can be used as a reference checkpoint. Thus, in an example embodiment, a variety of sources of geo-location data can be accessed and used in the various layers of the cloud-based vehicle information and control ecosystem  201 . 
     Referring now to  FIG. 3 , the diagram illustrates the geo-location aggregation engine  350  of an example embodiment. The geo-location aggregation engine  350  receives input from a plurality of geo-location data collectors  310 . The geo-location data collectors  310  are configured to collect geo-location data from a variety of geo-location data sources in the various layers of the cloud-based vehicle information and control ecosystem  201 . For example, a first data collector  311  is configured to obtain geo-location data from one or more GPS receivers installed in a vehicle. Using the platform layer and the platform system  270  described above, the first data collector  311  can access an ECU  120  corresponding to the in-vehicle GPS receiver via the CAN bus  116  and retrieve GPS and timing data generated therein. The first data collector  311  can be configured to periodically retrieve the in-vehicle GPS data and process and/or store the retrieved data. The first data collector  311 , and each of data collectors  310 , can be implemented as a software or firmware module with processing logic embedded therein for performing the retrieval of the GPS and timing data (or other geo-location data or reliability data) from one or more GPS receivers or other geo-location devices installed in a vehicle. 
     Referring again to  FIG. 2  and  FIG. 3 , the geo-location data collectors  310  can be implemented at any layer of the cloud-based vehicle information and control ecosystem  201 . For example, the first data collector  311  can be implemented as an integrated component of platform system  270  or as part of an in-vehicle platform application  105  to collect GPS data from an in-vehicle GPS receiver. The first data collector  311  can also collect reliability data from the in-vehicle GPS receiver. Reliability data refers to data indicative of the reliability of the GPS data, such as signal strength, error counts, type of GPS receiver, and the like. The collected GPS data and reliability data can be provided or made available to any other component or subsystem at the platform layer. A second data collector  312  can be implemented as an integrated component of platform system  270  or as part of an in-vehicle platform application  105  to collect dead reckoning data and related reliability data from in-vehicle sensors and/or in-vehicle dead reckoning data subsystems. The collected dead reckoning data and reliability data can also be provided or made available to any other component or subsystem at the platform layer. 
     Similarly, the first data collector  311  and/or the second data collector  312  can be implemented as an integrated component of map subsystem  252  of the user interface server  250  at the framework layer of the cloud-based vehicle information and control ecosystem  201 . The first data collector  311  and/or the second data collector  312  can also be implemented in the framework layer as a part of a mobile device application  106 . The first data collector  311  and/or the second data collector  312  can be implemented in the framework layer to collect GPS data and/or dead reckoning data and related reliability data from an in-vehicle GPS receiver or in-vehicle dead reckoning subsystem. Data communications, as described above, can be used to transfer the data between the platform and framework layers. The collected GPS data and/or dead reckoning data and related reliability data can be provided or made available to any other component or subsystem at the framework layer. In this manner, the user interface server  250  and/or a mobile device app  106  in the framework layer can get access to GPS data and/or dead reckoning data and related reliability data generated by an in-vehicle GPS receiver, in-vehicle sensors, and/or dead reckoning data subsystems. 
     Moreover, the first data collector  311  and/or the second data collector  312  can also be implemented as an integrated component of map subsystem  212  of the vehicle information and control system  210  or an integrated component of map subsystem  222  of the user interface server  220  at the application layer of the cloud-based vehicle information and control ecosystem  201 . The first data collector  311  and/or the second data collector  312  can also be implemented in the application layer as a part of a content source application  242 . The first data collector  311  and/or the second data collector  312  can be implemented in the application layer to collect GPS data and/or dead reckoning data and related reliability data from an in-vehicle GPS receiver or in-vehicle dead reckoning subsystem. Data communications, as described above, can be used to transfer the data between the platform, framework, and application layers. The collected GPS data and/or dead reckoning data and related reliability data can be provided or made available to any other component or subsystem at the application layer. In this manner, the vehicle information and control system  210 , the user interface server  220 , and/or content sources  240  in the application layer can get access to GPS data and/or dead reckoning data and related reliability data generated by an in-vehicle GPS receiver, in-vehicle sensors, and/or dead reckoning data subsystems. 
     In an example embodiment, the GPS receiver (either in-vehicle or in a nearby mobile device) and the in-vehicle dead reckoning data subsystems can periodically collect time-tagged position data points for tracking the vehicle&#39;s position, direction of travel (heading), speed, and route. The heading can be established by collecting the vehicle&#39;s position data points over time and extrapolating the current heading of the vehicle from two or more position data points. Additionally, the heading of the vehicle can be established by receiving directional information from the vehicle&#39;s onboard compass, and/or by receiving directional data from the compass of a mobile device that is proximate to and in data communication with the vehicle as described herein. The in-vehicle dead reckoning data subsystem can receive the directional data from the compass (either in-vehicle or in a nearby mobile device) and determine the current heading of the vehicle therefrom. The current heading of the vehicle can thus be determined at any point in time and saved for a subsequent routing. 
     Conventional GPS navigation systems cannot determine a vehicle&#39;s heading until the vehicle moves and at least two different positional data points are recorded. As a result, when a driver first activates the conventional GPS navigation system, the system cannot give the driver routing instructions until the vehicle is moved. This can be frustrating for a driver who may not know the best direction to begin the route. 
     The embodiments described herein provide a solution to this problem. Because the example embodiments described herein can determine and retain the current vehicle heading at any point in time using any of the above-described techniques, the navigation subsystem of an example embodiment can generate accurate and precise driving instructions immediately when the navigation subsystem is initially activated and before the vehicle is moved. As such, the current vehicle heading can be used by the navigation subsystem to generate accurate and precise driving instructions while the vehicle is still parked. For example, if a desired initial routing is in an opposite direction of the current vehicle heading, the navigation subsystem of an example embodiment can instruct the driver to make a U-turn, while the vehicle is still parked, to join the route. Conventional GPS navigation systems cannot support this functionality. 
     Thus, as described herein, the first data collector  311  and/or the second data collector  312  can be implemented at any layer of the cloud-based vehicle information and control ecosystem  201  to enable any component or subsystem at any layer to obtain access to GPS data and/or dead reckoning data and related reliability data generated or obtained from an in-vehicle GPS receiver and/or in-vehicle dead reckoning subsystem. As described above, data communications between layers of the cloud-based vehicle information and control ecosystem  201  can be used to convey the GPS data and/or dead reckoning data and related reliability data to other components, subsystems, and/or layers of ecosystem  201 . 
     Similarly, a third data collector  313  can be implemented as an integrated component of map subsystem  252  of the user interface server  250  at the framework layer of the cloud-based vehicle information and control ecosystem  201 . The third data collector  313  can also be implemented in the framework layer as a part of a mobile device application  106 . The third data collector  313  can collect GPS data (or other geo-location information) and related reliability data from a GPS receiver (or other geo-location sensing device) resident in the mobile device  102 . The GPS data and related reliability data obtained from the mobile device  102  is generated by a different GPS receiver (or other geo-location sensing device) as compared to the GPS data obtained from an in-vehicle GPS receiver via a corresponding ECU. As such, the geo-location data and related reliability data generated or obtained by the third data collector  313  originates from a different source (i.e., a mobile device  102 ) than the data generated by the first data collector  311  (i.e., an in-vehicle GPS receiver connected to an ECU). The GPS data and reliability data collected by the third data collector  313  can be provided or made available to any other component or subsystem at the framework layer. 
     The third data collector  313  can also be implemented as an integrated component of platform system  270  or as part of an in-vehicle platform application  105  to collect GPS data and related reliability data from a GPS receiver (or other geo-location sensing device) resident in the mobile device  102 . Data communications, as described above, can be used to transfer the data between the platform and framework layers. The collected GPS data and related reliability data from the mobile device  102  can be provided or made available to any other component or subsystem at the framework or platform layers. In this manner, the platform system  270  in the platform layer can get access to GPS data and related reliability data generated by a mobile device  102  resident GPS receiver. 
     Moreover, the third data collector  313  can also be implemented as an integrated component of map subsystem  212  of the vehicle information and control system  210  or an integrated component of map subsystem  222  of the user interface server  220  at the application layer of the cloud-based vehicle information and control ecosystem  201 . The third data collector  313  can also be implemented in the application layer as a part of a content source application  242 . The third data collector  313  can be implemented in the application layer to collect GPS data and related reliability data from a mobile device  102  resident GPS receiver. Data communications, as described above, can be used to transfer the data between the platform, framework, and application layers. The collected GPS data and related reliability data can be provided or made available to any other component or subsystem at the application layer. In this manner, the vehicle information and control system  210 , the user interface server  220 , and/or content sources  240  in the application layer can get access to GPS data and related reliability data generated by a mobile device  102  resident GPS receiver. 
     Thus, as described herein, the third data collector  313  can be implemented at any layer of the cloud-based vehicle information and control ecosystem  201  to enable any component or subsystem at any layer to obtain access to GPS data and related reliability data generated or obtained from a mobile device  102  resident GPS receiver. As described above, data communications between layers of the cloud-based vehicle information and control ecosystem  201  can be used to convey the GPS data and related reliability data to other components or subsystems of ecosystem  201 . 
     Referring still to  FIGS. 2 and 3 , a fourth data collector  314  can be implemented as integrated component of map subsystem  212  of the vehicle information and control system  210  or an integrated component of map subsystem  222  of the user interface server  220  at the application layer of the cloud-based vehicle information and control ecosystem  201 . The fourth data collector  314  can also be implemented in the application layer as a part of a content source application  242 . The fourth data collector  314  can be configured to generate or obtain geo-location data and/or geo-location reliability data from one or more content sources  240  or other network-based geo-location data sources. For example, network-based geo-location data can include map data, GPS receiver reliability data, satellite status information, GPS service data, weather information, or a variety of other information that may bear on the accuracy or predictability of the geo-location fixes generated by other components in the ecosystem  201 . Additionally, network-based geo-location data sources can be deployed at various locations along roadways, on adjacent buildings, along railroad tracks, or other locations proximate to passing vehicles. In some cases, these network-based geo-location data sources can act as checkpoints to mark the passage or proximity of passing vehicles. Because the geo-location of the checkpoints can be precisely determined, the location of a particular vehicle can be precisely determined as the vehicle passes (or is proximate to) the checkpoint at a particular moment in time. The network-based geo-location data source can use network  205  to convey the vehicle location and timing (e.g., the vehicle geo-location based on a network-based geo-location data source) to other network-connected devices in the application layer. In this manner, the vehicle information and control system  210 , the user interface server  220 , and/or other content sources  240  can get access to GPS data and/or geo-location reliability data generated or obtained by a network-based geo-location data source via data communications within the application layer. Note that the vehicle geo-location fix based on a network-based geo-location data source may be different than either the geo-location of the vehicle based on an in-vehicle GPS receiver connected to an ECU or the geo-location of the vehicle based on a GPS receiver in a mobile device of an occupant of the vehicle. 
     The fourth data collector  314  can also be implemented as an integrated component of platform system  270  or as part of an in-vehicle platform application  105  to collect geo-location data and/or geo-location reliability data from one or more content sources  240  and/or other network-based geo-location data sources. Data communications, as described above, can be used to transfer the data between the platform, framework, and application layers. The collected GPS data and related reliability data from the network-based geo-location data sources can be provided or made available to any other component or subsystem at the application or platform layers. In this manner, the platform system  270  in the platform layer can get access to GPS data and related reliability data generated by network-based geo-location data sources. 
     Similarly, the fourth data collector  314  can be implemented as an integrated component of map subsystem  252  of the user interface server  250  at the framework layer of the cloud-based vehicle information and control ecosystem  201 . The fourth data collector  314  can also be implemented in the framework layer as a part of a mobile device application  106 . The fourth data collector  314  can be implemented in the framework layer to collect geo-location data and/or geo-location reliability data from one or more content sources  240  and/or other network-based geo-location data sources. Data communications, as described above, can be used to transfer the data between the application and framework layers. The collected geo-location data and/or geo-location reliability data can be provided or made available to any other component or subsystem at the framework layer. In this manner, the user interface server  250  and/or a mobile device app  106  in the framework layer can get access to GPS data and related reliability data generated by network-based geo-location data sources. 
     Finally, a fifth data collector  315  can be provided in a particular embodiment. Again, the fifth data collector  315  can be implemented in components of the platform, framework, or application layers as described above. The fifth data collector  315  can be implemented in any of the ecosystem  201  layers to collect explicitly provided geo-location information from a user. For example, a user operating a vehicle in which a platform system  270  includes a fifth data collector  315  can use provided user interfaces to explicitly specify a geo-location of the vehicle at a particular moment. Similarly, a user operating a vehicle in which an occupant has a mobile device  102  with a mobile app  106  that includes a fifth data collector  315  can use mobile app  106  provided user interfaces to explicitly specify a geo-location of the vehicle at a particular moment. A user in data connection with a content source  240  and/or other network-based geo-location data source that includes a fifth data collector  315  can use provided user interfaces to explicitly specify a geo-location of a vehicle at a particular moment. The fifth data collector  315  can be useful for explicitly calibrating or initializing a particular GPS device, geo-location sensing device, or network-based geo-location data source. Thus, as described above, various types of geo-location data collectors  310  can be implemented at any layer of the cloud-based vehicle information and control ecosystem  201 . Data communications between layers of the ecosystem  201  can be used to convey the GPS data (or other geo-location information) and related reliability data to other components or subsystems of ecosystem  201 . The GPS data (or other geo-location information) and related reliability data can thereby be conveyed as input to the geo-location aggregation engine  350  shown in  FIG. 3 . 
     It will be apparent to those of ordinary skill in the art that a variety of other geo-location data collectors  310  can be used to gather geo-location data in a variety of ways. For example, cell tower triangulation of signals from a mobile device  102  can be used to determine a geo-location of the mobile device  102 . If the mobile device  102  is with an occupant of a vehicle  104 , the geo-location of the mobile device  102  can also define the geo-location of the vehicle  104 . Cell tower triangulation of signals from a mobile device  102  can be performed or assisted by network resources that are accessible through the layers of the cloud-based vehicle information and control ecosystem  201  as described herein. Additionally, the other geo-location data collectors  310  can include a WiFi WAP proximity detector for using WiFi signals from a mobile device  102  to determine a geo-location of the mobile device  102  as described above. Again, the geo-location determination of the mobile device  102  based on WiFi proximity can be performed or assisted by network resources that are accessible through the layers of the cloud-based vehicle information and control ecosystem  201  as described herein. As described above, techniques for determining the location of a mobile device based on a mobile device resident GPS receiver, cell tower triangulation, or WiFi WAP proximity are well-known to those of ordinary skill in the art. Any of these techniques for determining a geo-location fix can be used and provided as a geo-location data collector  310 . 
     Referring again to  FIG. 3 , the geo-location aggregation engine  350  can receive geo-location data and related reliability data from a variety of geo-location data collectors  310  and, along with the map data set  320  and configuration data set  340 , produce a resulting geo-location fix based on aggregated geo-location data from a plurality of sources. For example, the geo-location aggregation engine  350  can receive a GPS geo-location fix for a particular vehicle at a particular moment in time from an in-vehicle GPS receiver connected to an ECU via a first data collector  311 . Similarly, the geo-location aggregation engine  350  can also receive dead reckoning data for the particular vehicle at the particular moment in time from a dead reckoning subsystem of the vehicle via a second data collector  312 . The geo-location aggregation engine  350  can also receive a GPS geo-location fix for the particular vehicle at the particular moment in time from GPS receiver in a mobile device of an occupant of the vehicle via a third data collector  313 . The geo-location aggregation engine  350  can also receive a geo-location fix for the particular vehicle based on cell tower triangulation or WiFi WAP proximity detection as described above. The geo-location aggregation engine  350  can also receive a GPS geo-location fix for the particular vehicle at the particular moment in time from a network-based geo-location data source via a fourth data collector  314 . Finally, the geo-location aggregation engine  350  can receive a GPS geo-location fix for the particular vehicle at the particular moment in time from an explicit user data entry via a fifth data collector  315 . As described in more detail below, the geo-location aggregation engine  350  can select the best geo-location fix or combine a plurality of geo-location fixes to produce a resulting geo-location fix. This geo-location fix can be rendered more accurately based on input from multiple sources and the connected intelligence of multiple resources at each of the layers of the cloud-based vehicle information and control ecosystem  201 . 
     As shown in  FIG. 3 , the geo-location aggregation engine  350  can receive input from a map data set  320 , a data collector reliability data set  330 , and a configuration data set  340 . The map data set  320  includes conventional map data, such as a scaled two-dimensional or three-dimensional arrangement of natural and man-made landmarks in a particular geographical location. Typically, the specific geo-location of landmarks and other objects on the map can be determined from the map data set  320 . Additionally, the map data can be augmented to include information related to regions or geographical locations where GPS service may be intermittent or unavailable. For example, locations of tunnels, deep canyons, mountains, tall buildings, etc. where GPS signals may be blocked can be identified in regional interference information of the map data set  320 . The data collector reliability data set  330  can include the reliability data obtained from each of the geo-location data sources as described above. This reliability data can be used to ascertain the reliability of geo-location data provided by a particular geo-location data source. The data collector reliability data set  330  can also include historical data that specifies the geo-location data and reliability data provided by a particular geo-location data source for a past period of time. The historical data can be used to identify trends over time in the data produced by a particular geo-location data source. The data collector reliability data set  330  can also include device data and service data that specify any interruptions or degradations that may be occurring with respect to particular geo-location data sources or system-wide geo-location service providers. The data collector reliability data set  330  can also include a set of weighted values that define a confidence level that a geo-location service provider can apply to particular geo-location data sources or system-wide geo-location service providers. The weighted values can be used to bias the geo-location aggregation engine  350  for or against particular geo-location data sources. Finally, the configuration data set  340  can be used to define configuration values to specify the manner in which a system operator wants the geo-location aggregation engine  350  to operate. For example, the configuration data set  340  can be used to configure the weighted values or to specify the type of geo-location action processor  360  the geo-location aggregation engine  350  should use for processing the geo-location collected by the geo-location data collectors  310 . 
     As described above, the geo-location aggregation engine  350  can receive geo-location data and related reliability data from a variety of geo-location data collectors  310 . As described, the geo-location aggregation engine  350  can receive: 1) a GPS geo-location fix for a particular vehicle at a particular moment in time from an in-vehicle GPS receiver connected to an ECU; 2) dead reckoning data for the particular vehicle at the particular moment in time from a dead reckoning subsystem of the vehicle; 3) a GPS geo-location fix for the particular vehicle at the particular moment in time from GPS receiver in a mobile device of an occupant of the vehicle; 4) a GPS geo-location fix for the particular vehicle at the particular moment in time from a network-based geo-location data source; and 5) a GPS geo-location fix for the particular vehicle at the particular moment in time from an explicit user data entry. Given this geo-location data and related reliability data, the geo-location aggregation engine  350  can perform a variety of configurable processing operations and related actions. For example, the geo-location aggregation engine  350  can use a first action processor  361  to identify a best geo-location fix from the geo-location data received from the geo-location data collectors  310 . The best geo-location fix can be a geo-location fix from one of the geo-location data collectors  310  that may have the highest related reliability data from the data collector reliability data set  330  or that may have a high level of accuracy based on map data set  320 . For example, the best geo-location fix can represent a geo-location fix from a geo-location data source that has reported no errors (or few errors), has a historical data trend that is not erratic or intermittent, is a type of geo-location data source known to be reliable, and has been weighted by a system operator in a manner indicating a high level of confidence in the geo-location data source. Additionally, the first action processor  361  can refer to the map data set  320  to determine if the geo-location fix being processed represents a location within a regional interference area. If so, the geo-location fix may be less accurate or less reliable as GPS receivers in the regional interference area may report errant or erratic geo-location data. In this case, the first action processor  361  can prioritize or re-prioritize the geo-location data collectors  310  to favor geo-location data collectors  310  that may be more accurate in the regional interference area and discount the data received from the geo-location data collectors  310  that may be sensitive to regional interference. As a result, the first action processor  361  can use map data to customize or modify the manner in which the best geo-location fix is calculated based on geographical features on the map. Similarly, the first action processor  361  can prioritize or re-prioritize the geo-location data collectors  310  to favor geo-location data collectors  310  that may be more accurate within particular timeframes. For example, some geo-location data collectors  310  may be more accurate at night or on weekends when there is less ambient interference. As a result, the first action processor  361  can use time and date data to customize or modify the manner in which the best geo-location fix is calculated based on temporal factors. Thus, using a variety of factors as described above, the first action processor  361  can identify and select a best geo-location fix from a plurality of geo-location fixes received from the geo-location data collectors  310 . The best geo-location fix represents a resulting geo-location fix produced by the geo-location aggregation engine  350 . 
     The first action processor  361 , and each of geo-location action processors  360 , can be implemented as a software or firmware module with processing logic embedded therein for performing processing operations on the GPS and timing data (or other geo-location data or reliability data) received from one or more GPS receivers or geo-location data sources. 
     Alternatively or in combination, the geo-location aggregation engine  350  can use a second action processor  362  to determine an average or composite geo-location fix from the geo-location data received from the geo-location data collectors  310 . The composite geo-location fix can be a combined geo-location fix from a plurality of the geo-location fixes provided by a plurality of the geo-location data collectors  310 . Instead of selecting a single best geo-location fix as the first action processor  361  does, the second action processor  362  produces a combination of the plurality of the geo-location fixes. For example, the second action processor  362  can compute an average or an interpolation of the input plurality of the geo-location fixes. In one embodiment, the best two or more geo-location fixes can be selected based on the reliability data as described above. Then, the selected best geo-location fixes can be interpolated to produce a composite geo-location fix. In another embodiment, the weighted values corresponding to each geo-location data source can be used in the interpolation to shift the composite geo-location fix toward the geo-location fixes with the highest weighted values, wherein the highest weighted values correspond to a higher level of confidence in the geo-location produced by a particular geo-location data source. As described above, the second action processor  362  can use map data to customize or modify the manner in which the composite geo-location fix is calculated based on geographical features on the map. Moreover, the second action processor  362  can use time and date data to customize or modify the manner in which the composite geo-location fix is calculated based on temporal factors. In this manner, the second action processor  362  can compute a composite geo-location fix from a plurality of geo-location fixes. The composite geo-location fix represents a resulting geo-location fix produced by the geo-location aggregation engine  350 . It will be apparent to those of ordinary skill in the art upon reading this disclosure that a variety of techniques can be used to compute a combined, averaged, or composite geo-location fix from a plurality of geo-location fixes. 
     Alternatively or in combination, the geo-location aggregation engine  350  can also use a third action processor  363  to report errors that may have been received in the geo-location data received from the geo-location data collectors  310 . For example, a geo-location fix received from a particular geo-location source may be significantly different (e.g., outside a configurable range) than the geo-location fix received from other geo-location sources. These geo-location differentials can be tracked over time using the historical data in reliability data set  330 . The third action processor  363 , operating under a configurable rule set, can determine that the particular geo-location source is producing errant or erratic geo-location data given the significantly different geo-location fix or a history of errant geo-location fixes provided by the particular geo-location source. In this case, the third action processor  363  can report the error to other processing components, subsystems, or layers of the ecosystem  201 . Additionally, the third action processor  363  can adjust the reliability data in the data collector reliability data set  330  to reflect the errant geo-location fixes provided by the particular geo-location source. 
     Alternatively or in combination, the geo-location aggregation engine  350  can also use a fourth action processor  364  to perform a re-calibration operation on a particular geo-location data source. As described above, the fourth action processor  364  can identify a particular geo-location source that is producing errant geo-location fixes. The fourth action processor  364  can also identify a particular geo-location source that is not producing data at all. In these cases, the fourth action processor  364  can cause data transmissions through ecosystem  201  to re-calibrate, re-configure, or reset the particular geo-location source. For example, techniques are well-known for re-calibrating a GPS receiver. Similar operations can be performed on other types of geo-location sources to induce the devices to start or continue producing accurate geo-location fixes. 
     As with the geo-location data collectors  310  described above, the geo-location aggregation engine  350  can be implemented at any layer of the cloud-based vehicle information and control ecosystem  201 . For example, the geo-location aggregation engine  350  can be implemented as an integrated component of platform system  270  or as part of an in-vehicle platform application  105  to aggregate geo-location data received from a plurality of geo-location data collectors  310 . Similarly, the geo-location aggregation engine  350  can be implemented as an integrated component of map subsystem  252  of the user interface server  250  or as a part of a mobile device application  106  at the framework layer of the cloud-based vehicle information and control ecosystem  201 . Moreover, the geo-location aggregation engine  350  can be implemented as an integrated component of map subsystem  212  of the vehicle information and control system  210  or an integrated component of map subsystem  222  of the user interface server  220  at the application layer of the cloud-based vehicle information and control ecosystem  201 . The geo-location aggregation engine  350  can also be implemented in the application layer as a part of a content source application  242 . Because the geo-location data collectors  310  described above can be implemented at any layer of the ecosystem  201 , the geo-location aggregation engine  350  can be implemented at any layer of the ecosystem  201  and can have access to the geo-location data provided by the geo-location data collectors  310  at any layer. Thus, a system and method for obtaining geographical location data from multiple sources and aggregating the geographical location data is disclosed. 
       FIG. 4  is a processing flow diagram illustrating an example embodiment of systems and methods for obtaining geographical location data from multiple sources and aggregating the geographical location data as described herein. The method  400  of an example embodiment includes: receiving geo-location data from a plurality of geo-location data collectors, at least one of the plurality of geo-location data collectors being in data communication with an in-vehicle geo-location data source, at least one of the plurality of geo-location data collectors being in data communication with a geo-location data source in a mobile device (processing block  410 ); collecting reliability data corresponding to one or more of a plurality of geo-location data sources corresponding to the plurality of geo-location data collectors (processing block  420 ); collecting map data including information related to geographical features associated with the geo-location data (processing block  430 ); and aggregating, by use of a data processor, the geo-location data from the plurality of geo-location data collectors based on the reliability data and the map data to produce a resulting geo-location fix (processing block  440 ). 
       FIG. 5  shows a diagrammatic representation of machine in the example form of a computer system  700  within which a set of instructions when executed may cause the machine to perform any one or more of the methodologies discussed herein. In alternative embodiments, the machine operates as a standalone device or may be connected (e.g., networked) to other machines. In a networked deployment, the machine may operate in the capacity of a server or a client machine in server-client network environment, or as a peer machine in a peer-to-peer (or distributed) network environment. The machine may be a personal computer (PC), a tablet PC, a set-top box (STB), a Personal Digital Assistant (PDA), a cellular telephone, a web appliance, a network router, switch or bridge, or any machine capable of executing a set of instructions (sequential or otherwise) that specify actions to be taken by that machine. Further, while only a single machine is illustrated, the term “machine” can also be taken to include any collection of machines that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein. 
     The example computer system  700  includes a data processor  702  (e.g., a central processing unit (CPU), a graphics processing unit (GPU), or both), a main memory  704  and a static memory  706 , which communicate with each other via a bus  708 . The computer system  700  may further include a video display unit  710  (e.g., a liquid crystal display (LCD) or a cathode ray tube (CRT)). The computer system  700  also includes an input device  712  (e.g., a keyboard), a cursor control device  714  (e.g., a mouse), a disk drive unit  716 , a signal generation device  718  (e.g., a speaker) and a network interface device  720 . 
     The disk drive unit  716  includes a non-transitory machine-readable medium  722  on which is stored one or more sets of instructions (e.g., software  724 ) embodying any one or more of the methodologies or functions described herein. The instructions  724  may also reside, completely or at least partially, within the main memory  704 , the static memory  706 , and/or within the processor  702  during execution thereof by the computer system  700 . The main memory  704  and the processor  702  also may constitute machine-readable media. The instructions  724  may further be transmitted or received over a network  726  via the network interface device  720 . While the machine-readable medium  722  is shown in an example embodiment to be a single medium, the term “machine-readable medium” should be taken to include a single non-transitory medium or multiple media (e.g., a centralized or distributed database, and/or associated caches and servers) that store the one or more sets of instructions. The term “machine-readable medium” can also be taken to include any non-transitory medium that is capable of storing, encoding or carrying a set of instructions for execution by the machine and that cause the machine to perform any one or more of the methodologies of the various embodiments, or that is capable of storing, encoding or carrying data structures utilized by or associated with such a set of instructions. The term “machine-readable medium” can accordingly be taken to include, but not be limited to, solid-state memories, optical media, and magnetic media. 
     The Abstract of the Disclosure is provided to comply with 37 C.F.R. §1.72(b), requiring an abstract that will allow the reader to quickly ascertain the nature of the technical disclosure. It is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims. In addition, in the foregoing Detailed Description, it can be seen that various features are grouped together in a single embodiment for the purpose of streamlining the disclosure. This method of disclosure is not to be interpreted as reflecting an intention that the claimed embodiments require more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive subject matter lies in less than all features of a single disclosed embodiment. Thus the following claims are hereby incorporated into the Detailed Description, with each claim standing on its own as a separate embodiment.