Abstract:
Systems and methods for providing broadcast data analysis. One embodiment of a method includes receiving broadcast related data for a discrete content segment from a plurality of vehicles at a plurality of different geographic locations, where the plurality of vehicles receives the discrete content segment at the respective geographic locations. Similarly, the method may include determining whether any of the broadcast related data may be filtered due to overlap of the plurality of different geographic locations, calculating a statistic based on the broadcast related data from the plurality of vehicles and providing information related to the content, based on a comparison of the discrete content segment and other discrete content segments.

Description:
TECHNICAL FIELD 
       [0001]    Embodiments described herein generally relate to systems and methods for providing broadcast data analysis and, more specifically, to embodiments for collecting broadcast data for subsequent use. 
       BACKGROUND 
       [0002]    Music consumers and other content consumers now desire the ability to receive custom content with limited commercial interruption. While Pandora™, iHeart Radio™, etc. may provide the ability to play content within limited commercials and some customization, current solutions cannot combine broadcast content with user specific playlists. 
         [0003]    Accordingly, a need exists for the ability to compile data regarding content that is being broadcast across the country (and world) on a plurality of mediums and utilize this data for automatically providing statistical data, content playlists, and the like. 
       SUMMARY 
       [0004]    Systems and methods for providing broadcast data analysis are described herein. One embodiment of a method includes receiving broadcast related data for a discrete content segment from a plurality of vehicles at a plurality of different geographic locations, where the plurality of vehicles receives the discrete content segment at the respective geographic locations. Similarly, the method may include determining whether any of the broadcast related data may be filtered due to overlap of the plurality of different geographic locations, calculating a statistic based on the broadcast related data from the plurality of vehicles, and providing information related to the statistic, based on a comparison of the discrete content segment and other discrete content segments. 
         [0005]    In another embodiment, a system for providing broadcast data analysis includes a first antenna for receiving a broadcast signal, the broadcast signal including content, a first tuner to tune to a plurality of different frequencies to receive the content on a plurality of different channels, and a vehicle computing device that includes a processor and a memory component. The memory component may store logic that, when executed by the processor, causes the system to determine an identity of the content, determine a location of the vehicle computing device at a time when the broadcast signal was received, and determine a timestamp when the broadcast signal was received. In some embodiments the logic further causes the system to provide the identity of the content, the location, and the timestamp to a remote computing device, where the remote computing device receives similar information from a plurality of different vehicle computing devices to determine popularity data of the content that is broadcast in a plurality of different geographic locations. 
         [0006]    In yet another embodiment, a system for providing broadcast data analysis includes logic that causes the system to receive broadcast related data for a discrete content segment from a plurality of vehicles, where the plurality of vehicles receives the discrete content segment via an antenna and a tuner. In some embodiments, the logic causes the system to determine a location of the plurality of vehicles when the discrete content segment was received, calculate a first statistic based on the broadcast related data received from the plurality of vehicles and filtering out data from vehicles with overlapping geographic locations. In some embodiments, the logic causes the system to provide information related to the statistic, based on a comparison of the discrete content segment and other discrete content segments. 
         [0007]    These and additional features provided by the embodiments of the present disclosure will be more fully understood in view of the following detailed description, in conjunction with the drawings. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0008]    The embodiments set forth in the drawings are illustrative and exemplary in nature and not intended to limit the disclosure. The following detailed description of the illustrative embodiments can be understood when read in conjunction with the following drawings, where like structure is indicated with like reference numerals and in which: 
           [0009]      FIG. 1  schematically depicts a computing environment for providing broadcast data analysis, according to embodiments disclosed herein; 
           [0010]      FIG. 2  schematically depicts a vehicle interior for providing broadcast data analysis, according to embodiments disclosed herein; 
           [0011]      FIG. 3  depicts a flowchart providing content information, according to embodiments disclosed herein; 
           [0012]      FIG. 4  depicts a flowchart for sending broadcast related data to a remote computing device, according to embodiments disclosed herein; 
           [0013]      FIG. 5  depicts a flowchart for compiling a playlist based on statistical data, according to embodiments disclosed herein; and 
           [0014]      FIG. 6  depicts a computing device for providing broadcast data analysis, according to embodiments disclosed herein. 
       
    
    
     DETAILED DESCRIPTION 
       [0015]    Embodiments disclosed herein include systems and methods for providing broadcast data analysis. Some embodiments include hardware and/or software to continuously collect and analyze broadcast data (e.g., AM/FM/HD radio, television signals, etc.) throughout a fleet of vehicles. As an example, an automobile manufacturer may have a vast distribution of radios throughout the world and can coordinate a global network of radio receivers to create a database of all broadcast music encountered by the vehicles. The system may leverage the data collected about the broadcasters with a timestamp and/or and geo-caching data tag to identify the most played content and provide users an on-demand playlist of songs from any given station, songs from a particular genre, songs from a particular geographic region, trending songs, frequently played songs, infrequently played songs, etc. to be viewed by a playlist viewer. 
         [0016]    Accordingly, embodiments disclosed herein may provide a mechanism to create playlists from and/or otherwise provide content that was previously broadcast on AM, FM, satellite, etc. With crowd sourcing of broadcast data from the fleet of vehicles, the work of collecting broadcast data may be performed without user interaction. Analytics may also be provided. 
         [0017]    Some of the vehicles may be equipped with a single tuner, while other vehicles may be equipped with a plurality of tuners. Single tuner probes may report the content that was received by that tuner and thus viewed by the user. Vehicles with a plurality of tuners may have a first tuner that is tuned to a user-defined frequency, while the second tuner, third tuner, etc. may scan a plurality of different channels, a plurality of different frequencies, and/or a plurality of different sources (e.g., iPod, mobile phone, compact disc, etc.) automatically and may collect information from those sources without the user viewing that content. 
         [0018]    More specifically, multiple tuner vehicles (e.g., with two or more tuners) may utilize a first tuner and a second tuner, as well as logic to facilitate collection of data when the tuner is not in “radio mode” or otherwise in an advanced reception scheme (such as phase diversity). In such embodiments, the first tuner may be manually tuned to a station by a user. The second tuner may automatically scan frequencies to identify broadcast related data from at least one channel. 
         [0019]    Additionally, for reliable metadata, embodiments may be configured to specifically identify only a predetermined content type metadata in the AM/FM/HD radio power spectral density (PSD) digital sideband by filtering out program type (PTY) genre codes. This significantly reduces the likelihood that undesirable stations or content (including a discrete content segment, such as a song, program, etc.) would affect quality of music (or other) data collected. 
         [0020]    When transmitting data about a received song (or other content) to the database, embodiments may be configured to incorporate such information as time and location based on the received positioning data of the vehicle. Global coordinates and map data cross-referencing to cities may be performed by the vehicle (if equipped with a navigation system) and/or performed by a remote computing device or other computing device. 
         [0021]    Depending on the embodiment, the handling of multiple transmissions of the same content on the same frequency within a given time frame and geo-fenced area may be given specific consideration as to not count duplicate songs for certain purposes (e.g., two cars on the highway tuned to 88.7 at 3:00 PM in Detroit only count once for overall play counts, but may be counted twice for other metrics, such as user preference). Similarly, some embodiments may be utilized to capture duplicative data to determine which content viewers are actually viewing. 
         [0022]    Depending on the particular embodiment, playlists returned may be used as seed stations for internet based radio stations and/or may be used for actual content playback to a playlist viewer. Similarly, embodiments may be configured for implementation on a variety of deployment scales. Specifically, some embodiments may be limited to a single vehicle that only stores the data collected within its reception range. The system may be configured for collecting reception data during the time when the vehicle is on or could incorporate a time division multiplexing scheme with limited power operation to scan the FM spectrum when the vehicle is not in operation. 
         [0023]    Referring now to the drawings,  FIG. 1  schematically depicts a computing environment for broadcast data analysis, according to embodiments disclosed herein. As illustrated, a network  100  may be coupled to a vehicle  102 , such as vehicles  102   a ,  102   b . The vehicles  102   a ,  102   b  may include a computing device, such as vehicle computing devices  104   a ,  104   b  respectively. Additionally, the vehicles  102   a ,  102   b  may each include one or more radio receivers with one or more tuners for tuning to radio frequencies and thus for receiving broadcast content over such broadcast types as AM, FM, XM, HD Radio, etc. Accordingly, the vehicles  102   a ,  102   b  may include one or more antennas (such as a first antenna and a second antenna), speakers, a display device (such as display device  240  from  FIG. 2 ), and/or other hardware for receiving and providing broadcast content. Also coupled to the network  100  are a user computing device  104   c , a content receiving device  104   d , and a remote computing device  106 , which includes a memory component  134  that may store data compiling logic  144   a  and analysis logic  144   b.    
         [0024]    The network  100  may include a wide area network, such as the internet, a cellular network (such as 3G, 4G, 4G LTE, WiMax, etc.), a content broadcast network (such as AM, FM, satellite radio, television, etc.). Similarly, the network  100  may include a local area network, such as a wireless fidelity (WiFi) network, a Bluetooth network, a near field communication network, hardwire, etc. 
         [0025]    The vehicle computing devices  104   a ,  104   b  may be configured as an integrated computing device and/or may be configured as a discrete computing device (such as a mobile phone) that is configured for receiving data from a respective vehicle  102  to provide the functionality described herein. Accordingly, the vehicle computing devices  104   a ,  104   b  may include a positioning system (such as a global positioning system), radio receiver, display device, and/or other components for providing the functionality described herein. In some embodiments, hardware and/or software for providing the described functionality may be included, but are separate from the vehicle computing device  104   a ,  104   b.    
         [0026]    Similarly, the user computing device  104   c  may be configured as a personal computer, laptop, mobile phone, a tablet, and/or other device for performing the functionality described herein. The user computing device  108  may be utilized for receiving and/or providing broadcast content, as well as playlists created as described herein. The content receiving device  104   d  may be configured for similar functionality, and may include at least one radio tuner, a television tuner, a computing device, and/or other hardware and software for receiving and providing the content described herein. 
         [0027]    Also depicted in  FIG. 1  is the remote computing device  106  that includes a memory component  134 . The memory component  134  may store logic, such as data compiling logic  144   a  and analysis logic  144   b . The data compiling logic  144   a  may be executed by a processor (such as processor  632  from  FIG. 6 ) of the remote computing device  106  to cause the remote computing device  130  to detect receive a broadcast signal (such as radio signals and/or metadata) for determining the identity of the received content. The analysis logic  144   b  may cause the remote computing device  106  to utilize the received data to create playlists and/or determine statistics (such as a first statistic and a second statistic) related to the broadcast content. The statistics may include one or more of: most played content, most played content for a predetermined geographic location, most played content for a predetermined content type, content from a predetermined broadcast station, trending content, infrequently broadcast content, etc. Other components of the vehicle computing device  104   a  may be provided in  FIG. 6 , described in more detail, below. 
         [0028]      FIG. 2  schematically depicts a vehicle interior for providing broadcast data analysis, according to embodiments disclosed herein. As illustrated, the vehicle  102   a  includes the vehicle computing device  104   a , which includes a memory component  234  that stores content determining logic  236   a  and communication logic  236   b . The content determining logic  236   a  may be utilized to receive metadata and/or otherwise determine the identity and/or other information regarding received content. The communication logic  236   b  may be utilized for facilitating communication with the remote computing device  106 . A processor  238  is also included for executing the logic. Also included is a display device  240  for providing one or more user interfaces related to receipt of content, playback of content, identification of content, and/or for other purposes described herein. 
         [0029]    Accordingly, the vehicle  102   a  may receive broadcast content, such as a radio broadcast, television broadcast, etc. The vehicle computing device  104   a  may determine a timestamp and/or timestamp data for receiving the broadcast content, and may identify the broadcast content that was received (such as a song title, a program title, an episode title, an album title, etc.). The vehicle computing device  104   a  may additionally receive a geo-position of the vehicle  102  when the content was received. This information may be sent to the remote computing device  106 . The remote computing device  106  may receive this data from the vehicle  102   a , the vehicle  102   b , and/or other vehicles with this functionality. The remote computing device  106  may utilize the received data to determine statistical information regarding broadcast content over one or more geographic locations. 
         [0030]    As an example, the remote computing device  106  may utilize the received data to determine the content that is most played. Identifications regarding content type (such as rock, country, classical, talk, etc.) may be determined and determinations may be made with regard to these content types. The remote computing device  106  may additionally create playlists of the most heavily broadcast content and may provide this information for use in additional broadcasts and/or for playback using services such as Pandora™, iHeart Radio™, Spotify™, etc. 
         [0031]    Similarly, some embodiments may be configured to determine the content that users are actually tuned to identify not only popularity of content (e.g., most played content) by the broadcasters, but popularity among users. This information may be utilized for similar purposes described above. Depending on the particular embodiment, this determination may be made by the vehicle computing device  104   a . If the vehicle  102   a  only includes a single tuner, the vehicle computing device  104   a  may determine that the received data is being listened and/or viewed by the user. If the vehicle  102   a  includes a plurality of tuners, a determination may be made regarding which tuner is being actively utilized. Other tuners in the vehicle  102  may be utilized to scan channels for determining broadcast content that is not being played to the user. As the second (or other) tuners detect content, the vehicle computing device  104   a  may determine an identity of the content, a timestamp, a geo-location, etc. that may be sent to the remote computing device  106 . 
         [0032]      FIG. 3  depicts a flowchart providing content information, according to embodiments disclosed herein. As illustrated in block  350 , broadcast data may be received from a plurality of vehicles. The broadcast data may include information identifying content that has been broadcast from one or more geographic locations, as well as other information described above. In block  352 , a determination of the geographical locations of the vehicles that sent data to the remote computing device  106  may be made and data from vehicles with overlapping geographic locations may be filtered out. 
         [0033]    The plurality of different geographic locations of the plurality of different vehicle computing devices  104  may be determined by the respective vehicle computing device  104   a  via from a positioning system and/or by determining a location of the broadcast system that is broadcasting the content (such as using audio detection functionality to determine the broadcast station and thus an approximate location of the vehicle). In block  354 , the filtered broadcast data may be utilized to determine a statistic with regard to broadcast content. As described above, the statistic may be related to content that is most broadcast and/or viewed by users. In block  356 , information related to the statistic may be provided. This may include providing one or more playlists to one or more users, providing the statistical data to a third party for advertising, broadcast, etc. 
         [0034]      FIG. 4  depicts a flowchart for sending broadcast related data to a remote computing device  106 , according to embodiments disclosed herein. As illustrated in block  450 , a vehicle  102  may tune to a currently local station (e.g., a broadcast station that is local to a current location of the vehicle  102 ). In block  452 , the location of the vehicle  102  and/or tuner may be determined. In block  454 , content may be received from the local station. In block  456 , a determination may be made regarding whether the received content is a preferred content type. In some embodiments, the preferred content type may be musical content and non-preferred content type may include talk radio. Similarly, some embodiments may identify rock music as a preferred content type and classical as non-preferred. Regardless of the actual classification of preferred content types, if the received content is not a preferred content type, the flowchart returns to block  450 . If the received content is classified as the preferred content type, the flowchart may proceed to block  458  to determine the content title and/or other identifier. In block  460 , the content title, location and/or other data may be sent to the remote computing device  106  for utilization described above. 
         [0035]      FIG. 5  depicts a flowchart for compiling a playlist based on statistical data, according to embodiments disclosed herein. As illustrated in block  550 , content and geographical information may be received. In block  552 , a characteristic of the content may be determined. The characteristic may include a content type and/or other characteristic. In block  554 , a determination may be made regarding whether the received content is the preferred content type. In block  556 , a statistic may be determined based on the characteristic of the content. In block  558 , a playlist may be compiled based on the static from the geographical location and a plurality of other geographical locations. The playlist may be sent to a content provider and/or provided to one or more users. 
         [0036]      FIG. 6  depicts a remote computing device  106  for providing broadcast data analysis, according to embodiments disclosed herein. The remote computing device  106  includes a processor  632 , input/output hardware  638 , network interface hardware  650 , a data storage component  652  (which stores location data  654   a , content data  654   b , and/or other data), and the memory component  134 . The memory component  134  may be configured as volatile and/or nonvolatile memory and as such, may include random access memory (including SRAM, DRAM, and/or other types of RAM), flash memory, secure digital (SD) memory, registers, compact discs (CD), digital versatile discs (DVD), and/or other types of non-transitory computer-readable mediums. Depending on the particular embodiment, these non-transitory computer-readable mediums may reside within the remote computing device  106  and/or external to the remote computing device  106 . 
         [0037]    The memory component  140  may store operating logic  642 , the data compiling logic  144   a  and the analysis logic  144   b . The data compiling logic  144   a  and the analysis logic  144   b  may each include a plurality of different pieces of logic, each of which may be embodied as a computer program, firmware, and/or hardware, as an example. A local interface  656  is also included in  FIG. 6  and may be implemented as a bus or other communication interface to facilitate communication among the components of the remote computing device  106 . 
         [0038]    The processor  632  may include any processing component operable to receive and execute instructions (such as from a data storage component  652  and/or the memory component  134 ). As described above, the input/output hardware  638  may include and/or be configured to interface with the components of  FIG. 6 . 
         [0039]    The network interface hardware  650  may include and/or be configured for communicating with any wired or wireless networking hardware, including an antenna, a modem, a LAN port, wireless fidelity (Wi-Fi) card, WiMax card, mobile communications hardware, and/or other hardware for communicating with other networks and/or devices. From this connection, communication may be facilitated between the remote computing device  106  and other computing devices, such as those depicted in  FIG. 1 . 
         [0040]    The operating logic  642  may include an operating system and/or other software for managing components of the remote computing device  106 . As discussed above, the data compiling logic  144   a  may reside in the memory component  134  and may be configured to cause the processor  632  to compile information from a plurality of vehicles and/or content display devices (such as radios, televisions, computing devices, etc.). Similarly, the analysis logic  144   b  may be utilized to analyze the information related to the content to determine statistics, arrange playlists, etc. 
         [0041]    It should be understood that while the components in  FIG. 6  are illustrated as residing within the remote computing device  106 , this is merely an example. In some embodiments, one or more of the components may reside external to the remote computing device  106 . It should also be understood that, while the remote computing device  106  is illustrated as a single device, this is also merely an example. In some embodiments, the data compiling logic  144   a  and the analysis logic  144   b  may reside on different computing devices. As an example, one or more of the functionalities and/or components described herein may be provided by the vehicle computing devices  104   a ,  104   b , the user computing device  104   c  and/or the content receiving device  104   d , which may be coupled to the vehicle  102  via the network  100 . These computing devices may also include hardware and/or software for performing the functionality described herein. 
         [0042]    Additionally, while the remote computing device  106  is illustrated with the data compiling logic  144   a  and the analysis logic  144   b  as separate logical components, this is also an example. In some embodiments, a single piece of logic may cause the vehicle computing device  104   a  to provide the described functionality. 
         [0043]    As illustrated above, various embodiments of providing broadcast data analysis are disclosed. These embodiments allow for crowd sourcing data compilation of broadcast content. Specifically, a plurality of radio and/or television receivers may receive the broadcast data, determine an identity of the broadcast data, a location, and/or other information for data analysis, playlist compilation, etc. 
         [0044]    While particular embodiments and aspects of the present disclosure have been illustrated and described herein, various other changes and modifications can be made without departing from the spirit and scope of the disclosure. Moreover, although various aspects have been described herein, such aspects need not be utilized in combination. Accordingly, it is therefore intended that the appended claims cover all such changes and modifications that are within the scope of the embodiments shown and described herein. 
         [0045]    It should now be understood that embodiments disclosed herein includes systems, methods, and non-transitory computer-readable mediums for broadcast data analysis. It should also be understood that these embodiments are merely exemplary and are not intended to limit the scope of this disclosure.