MLchartDataset catalogue

Patent · US9363008B2 · B2 · US

Deployment criteria for unmanned aerial vehicles to improve cellular phone communications

(11) Publication number
US9363008B2
(21) Application number
14/337,598
(22) Filing date
2014-07-22
(30) Priority date
2014-07-22
(43) Publication date
2016-06-07
(45) Date of grant
2016-06-07
(51) IPC
H04B 7/185; H04M 15/00; H04W 16/26; H04W 24/08; H04W 64/00; H04W 16/00; H04W 4/00; H04W 40/00; H04W 84/06
(52) CPC
  • H04B Transmission: 7/18504, 7/2606
  • G06Q Information and communication technology [ICT] specially adapted for administrative, commercial, financial, managerial or supervisory purposes; systems or methods specially adapted for administrative, commercial, financial, managerial or supervisory purposes, not otherwise provided for: 30/0201
  • H04M Telephonic communication: 15/68, 15/8038
  • H04W Wireless communication networks: 16/00, 16/18, 16/26, 24/02, 24/08, 64/006, 84/005, 84/06
(73) Assignee
International Business Machines Corp
(72) Inventors
Gregory J. Boss; II Rick A. Hamilton; Maharaj Mukherjee; Monimala Mukherjee
(54) Title
Deployment criteria for unmanned aerial vehicles to improve cellular phone communications
(57) Abstract

System, method and computer program product for extending mobile device cellular carrier network coverage using unmanned aerial vehicles (UAVs) equipped with telecommunications devices to act as temporary mobile device cellular network towers. The system and method extends cellular phone coverage of a land-based cellular phone network by: receiving information for determining a predicted or actual increase in aggregate cellular phone usage demand in an area at a determined time; identifying, based on an the predicted or actual increased aggregate cellular phone usage demand for the area, whether there exists a mismatch of existing usage coverage compared with the determined increased aggregate demand for that area; determining, based on an identified mismatch, a plan for sending signals to and deploying one or more mobile cellular unmanned aerial vehicles (UAV) having telecommunications equipment configured to extend cellular phone network coverage of an existing land-based cellular phone network at the mismatched area.

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Claims (19)

  1. A system for extending cellular phone coverage of a land-based cellular phone network comprising: a memory storage device; a computing device implementing a hardware processor coupled to said memory storage device and configured to: receive information to determine a predicted or actual increase in aggregate cellular phone usage demand in an area at a determined time, said received information comprising data indicating a convergence or migration of a plurality of mobile phone users to the area; predict clustering of said plurality of mobile phone users based on said information indicating a convergence or migration; generate a usage demand map indicating the predictive clustering of said plurality of mobile phone users movement at the area, identify, using said usage demand map, a predicted or actual increased aggregate cellular phone usage demand for said area; and determine whether there exists a mismatch of existing coverage compared with said predicted or actual increased aggregate cellular phone usage demand for said area such that additional coverage is needed at the determined time; wherein to predict clustering, said hardware processor is configured to: detect a destination of people movement; or detect a directional aspect of people movement; and said hardware processor is configured to: generate, based on a determined mismatch and in response to a destination or directional aspect detection, a plan for deploying said one or more mobile cellular unmanned aerial vehicles (UAVs) having telecommunications equipment configured to extend cellular phone network coverage of an existing land-based cellular phone network to a roaming pattern to accommodate said destination or directional aspect; and send signals to a facility configured to deploy and dispatch said one or more mobile cellular UAVs according to said plan, wherein, responsive to said signal, two or more mobile cellular UAVs are deployed to said determined area to connect with said existing land-based cellular phone network and extend cellular phone usage coverage at said area, and said hardware processor is further configured to: detect a merging of two or more mobile phone users group movements that provides a composite load to an area; determine whether two or more mobile cellular UAVs approach that area, and one of: share increased mobile cellular phone coverage by the two or more mobile cellular UAVs, or determine whether one deployed mobile cellular UAV may handle the composite load.
  2. The system as claimed in claim 1, wherein to determine said predicted or actual increase in aggregate cellular phone usage demand, said hardware processor is configured to: detect one or more of: incoming signal strengths from mobile phone users received at a fixed land-based cellular phone tower associated with said area, or a number of dropped call events detected of from a fixed land-based mobile cellular tower to other fixed land-based mobile cellular towers.
  3. The system as claimed in claim 1, wherein to determine said predicted or actual increase in aggregate cellular phone usage demand, said hardware processor is configured to: monitor said cellular phone network land-based fixed cellular phone tower bandwidth, and calculate a metric using said monitored fixed cellular phone tower bandwidth divided by a number of registered users.
  4. The system as claimed in claim 1, wherein said information indicating a convergence or migration includes one or more customer requests for increased coverage at said area for a specific time duration, wherein to identify said area, said hardware processor is configured to: detect customer requests from one or more of: high profile users, very important customers or customers having a contract with a cellular phone network carrier, emergency responders, personal calendar events shared voluntarily with the cellular phone network carrier.
  5. The system as claimed in claim 1, wherein said data indicating a convergence or migration is based on received transportation information including one or more of: data representing hired vehicle destination pick-up and drop-off locations, data representing current use of public transportation vehicles, data representing subway tickets sold to mobile phone users, wherein to determine from said information indicating a convergence or migration, said hardware processor is configured to: analyze from said received transportation information a location where people are going and a rate of change to that location; and detect if a rate of change compared to threshold is achieved that indicates a significant number of people will move in that same direction.
  6. The system as claimed in claim 1, wherein said data indicating a convergence or migration of many mobile phone users is based on financial transactions information, said financial transactions data including one or more types of: credit, debit, cash, ATM withdrawals transactions, wherein to determine, said hardware processor is further configured to one or more of: monitor for occurrence of an increased number of financial transactions of a particular transaction type; determine if it is a type of transaction that implies said physical convergence or migration; and determine for a trends or changes in velocity or rate of change of said as compared to a baseline measure; and in response to a determined trend or change, generate a plan for deploying said one or more mobile cellular UAVs to a roaming pattern to accommodate said destination or directional aspect.
  7. The system as claimed in 1, wherein said data indicating a convergence or migration of many mobile phone users is based on received social media information or conventional media information implying said convergence or migration, said social media network information data including: data from geo-tagged tweets or social media network messages from said user mobile devices, said clustering of group movement prediction being based on said geo-tagged tweets or said social media network messages.
  8. The system as claimed in claim 1, wherein to determine a plan to deploy a mobile cellular unmanned aerial vehicle, said hardware processor is configured to: configure an autonomic network of mobile cellular UAVs and sending signals to deploy one or more clusters of said mobile cellular UAVs network in a vicinity of or at the area; detect one or more events indicating a need for new or additional requirements; update said usage demand map based on said detected events; and autonomically redeploy or regroup one or more mobile cellular UAVs of a cluster to self correct said autonomic network based on said updated usage demand map.
  9. The system as claimed in claim 8, wherein to autonomically redeploy or regroup one or more mobile cellular UAVs of a cluster, said hardware processor is further configured to: establish communication among each mobile cellular UAV and a designated leader in the cluster, each said UAV's communicating data according to said updated usage demand map; monitor that one or more mobile cellular UAVs of said cluster support a particular cell phone usage demand in said area or vicinity according to said updated usage demand map, and self-correct a capacity of said cluster according to said updated usage demand map.
  10. A method for extending cellular phone coverage of a land-based cellular phone network comprising: receiving, at a hardware processor of a computing device, information to determine a predicted or actual increase in aggregate cellular phone usage demand in an area at a determined time, said received information comprising data indicating a convergence or migration of a plurality of mobile phone users to the area; predicting, using the hardware processor of a computing device, a clustering of said plurality of mobile phone users based on said information indicating a convergence or migration; generating, by the hardware processor of a computing device, a usage demand map indicating the predictive clustering of said plurality of mobile phone users movement at the area; identifying, using said usage demand map, a predicted or actual increased aggregate cellular phone usage demand for said area; determining whether there exists a mismatch of existing coverage compared with said predicted or actual increased aggregate cellular phone usage demand for said area such that additional coverage is needed at the determined time; wherein for predicting a clustering: detecting, using said hardware processor, a destination of people movement; or detecting, using said hardware processor, a directional aspect of people movement; and generating, based on a determined mismatch and in response to a destination or directional aspect detection, a plan for deploying said one or more mobile cellular unmanned aerial vehicles (UAVs) having telecommunications equipment configured to extend cellular phone network coverage of an existing land-based cellular phone network to a roaming pattern to accommodate said destination or directional aspect; and sending signals to a facility configured to deploy and dispatch said one or more mobile cellular UAVs according to said plan, wherein, responsive to said signal, two or more mobile cellular UAVs are deployed to said determined area to connect with said existing land-based cellular phone network and extend cellular phone usage coverage at said area, and said method further comprising: detecting, using said hardware processor, a merging of two or more mobile phone users group movements that provides a composite load to an area; determining, using said hardware processor, whether two or more mobile cellular UAVs approach that area, and one of: sharing increased mobile cellular phone coverage by the two or more mobile cellular UAVs, or determining whether one deployed mobile cellular UAV may handle the composite load.
  11. The method as claimed in claim 10, wherein said determining said predicted or actual increase in aggregate cellular phone usage demand includes: detecting one or more of: incoming signal strengths from mobile phone users received at a fixed land-based cellular phone tower associated with said area, or a number of dropped call events detected from a fixed land-based mobile cellular tower to other fixed land-based mobile cellular towers.
  12. The method as claimed in claim 10, wherein said determining said predicted or actual increase in aggregate cellular phone usage demand includes: monitoring said cellular phone network land-based fixed cellular phone tower bandwidth and calculating a metric using said monitored fixed cellular phone tower bandwidth divided by a number of registered users.
  13. The method as claimed in claim 10, wherein said information includes data indicating a convergence or migration of many mobile phone users to said identified area at a current or future time, said data including one or more customer requests for increased coverage at said area for a specific time duration, wherein said identifying said area comprises detecting customer requests from one or more of: high profile users, very important customers or customers having a contract with a cellular phone network carrier, emergency responders, or personal calendar events shared voluntarily with a cellular phone network carrier.
  14. The method as claimed in claim 10, wherein said information includes data indicating a convergence or migration of many mobile phone users to said identified area at a current or future time, said data comprising: transportation information including one or more of: data representing hired vehicle destination pick-up and drop-off locations, data representing current use of public transportation vehicles; data representing subway tickets sold to mobile phone users, wherein said determining said predicted or actual increase in aggregate cellular phone usage demand further comprises: analyzing from said received transportation information a location where people are going and a rate of change to that location; and detecting if a rate of change compared to threshold is achieved that indicates a significant number of people will move in that same direction.
  15. The method as claimed in claim 10, wherein said data indicating a convergence or migration of many mobile phone users is based on received transportation information including one or more of: data representing received financial transaction information, said financial transactions data including one or more types of: credit, debit, cash, ATM withdrawals transactions, wherein to determine, said hardware processor is further configured to one or more of: monitor for occurrence of an increased number of financial transactions of a particular transaction type; determine if it is a type of transaction that implies said physical convergence or migration; and determine for a trends or changes in velocity or rate of change of said as compared to a baseline measure; and in response to a determined trend or change, generate a plan for deploying said one or more mobile cellular UAVs to a roaming pattern to accommodate said destination or directional aspect.
  16. The method as claimed in 10, wherein said information includes data indicating a convergence or migration of many mobile phone users to said identified area at a current or future time, said data indicating a convergence or migration of many mobile phone users is based on received social media information or conventional media information implying said convergence or migration, said social media network information data including: data from geo-tagged tweets or social media network messages from said user mobile devices, said predictive clustering of group movement being based on said geo-tagged tweets or said social media network messages.
  17. The method as claimed in 10, wherein said deploying according to said generated plan comprises: configuring an autonomic network of mobile cellular UAVs and sending signals to deploy one or more clusters of said mobile cellular UAVs network in a vicinity of or at the area; detecting one or more events indicating a need for new or additional requirements; updating said usage demand map based on said detected events; and autonomically redeploying or regrouping one or more mobile cellular UAVs of a cluster to self correct said autonomic network based on said updated usage demand map.
  18. The method as claimed in claim 17, wherein said autonomically redeploying or regrouping one or more mobile cellular UAVs of a cluster comprises: establishing communication among each mobile cellular UAV and a designated leader in the cluster, each said UAV's communicating data according to said updated usage demand map; monitoring that one or more mobile cellular UAVs of said cluster support a particular cell phone usage demand in said area or vicinity, and self-correct a capacity of said cluster according to said updated usage demand map.
  19. A computer program product for extending cellular phone coverage of a land-based cellular phone network, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, the program instructions readable by a processing circuit to cause the processing circuit to perform a method to: receive information to determine a predicted or actual increase in aggregate cellular phone usage demand in an area at a determined time, said received information comprising data indicating a convergence or migration of a plurality of mobile phone users to the area; predict clustering of said plurality of mobile phone users based on said information indicating a convergence or migration; generate a usage demand map indicating the predictive clustering of said plurality of mobile phone users movement at the area, identify, using said usage demand map, a predicted or actual increased aggregate cellular phone usage demand for said area; and determine whether there exists a mismatch of existing coverage compared with said predicted or actual increased aggregate cellular phone usage demand for said area such that additional coverage is needed at the determined time; wherein to predict clustering, said program instructions cause the processing circuit to: detect a destination of people movement; or detect a directional aspect of people movement; and said program instructions further causing the processing circuit to: generate, based on a determined mismatch and in response to a destination or directional aspect detection, a plan for deploying said one or more mobile cellular unmanned aerial vehicles (UAVs) having telecommunications equipment configured to extend cellular phone network coverage of an existing land-based cellular phone network to a roaming pattern to accommodate said destination or directional aspect; and send signals to a facility configured to deploy and dispatch said one or more mobile cellular UAVs according to said plan, wherein, responsive to said signal, two or more mobile cellular UAVs are deployed to said determined area to connect with said existing land-based cellular phone network and extend cellular phone usage coverage at said area, and said program instructions further causing the processing circuit to: detect a merging of two or more mobile phone users group movements that provides a composite load to an area; determine whether two or more mobile cellular UAVs approach that area, and one of: share increased mobile cellular phone coverage by the two or more mobile cellular UAVs, or determine whether one deployed mobile cellular UAV may handle the composite load.

Description

The present invention relates generally systems and methods for evaluating and determining the capacity of cellular networks ground based stations, and the tactical deployment and use of telecommunications-equipped unmanned aerial vehicles (UAV) or “drones” to augment the capacities and capabilities of land-based cellular network base stations.

Inadequate mobile device cellular phone coverage is the subject of much frustration for many users of cellular/mobile phones. When customers lack sufficient mobile signal strength, customers incur costs in the form of cellular roaming, as well as dissatisfaction with low sound quality and dropped calls. Some technologies, such as CDMA, have the ability to expand and contract cellular coverage area from a fixed tower. The number of customers registered to a particular cell affects tower range, and the signal strength of a customer can vary dramatically when sampled from the same location at different times/days. Other factors can seriously degrade signal strength, including other RF interference, and multi-path interference created by physical obstacles. Zoning laws can create difficulty in building cellular towers, and even when zoning laws are favorable, availing appropriate space at financially advantageous terms can be difficult and time consuming. In other cases, signal strength may be good but capacity remains low. In these situations, customers appear to have good signal strength, but the throughput for data/voice can be limited because of saturation at the cellular tower's back haul link.

Citations (10)

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  • US20080242301A1
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Record as JSON
{
  "publication_number": "US9363008B2",
  "country": "US",
  "kind": "B2",
  "title": "Deployment criteria for unmanned aerial vehicles to improve cellular phone communications",
  "abstract": "System, method and computer program product for extending mobile device cellular carrier network coverage using unmanned aerial vehicles (UAVs) equipped with telecommunications devices to act as temporary mobile device cellular network towers. The system and method extends cellular phone coverage of a land-based cellular phone network by: receiving information for determining a predicted or actual increase in aggregate cellular phone usage demand in an area at a determined time; identifying, based on an the predicted or actual increased aggregate cellular phone usage demand for the area, whether there exists a mismatch of existing usage coverage compared with the determined increased aggregate demand for that area; determining, based on an identified mismatch, a plan for sending signals to and deploying one or more mobile cellular unmanned aerial vehicles (UAV) having telecommunications equipment configured to extend cellular phone network coverage of an existing land-based cellular phone network at the mismatched area.",
  "claims": [
    "1. A system for extending cellular phone coverage of a land-based cellular phone network comprising: a memory storage device; a computing device implementing a hardware processor coupled to said memory storage device and configured to: receive information to determine a predicted or actual increase in aggregate cellular phone usage demand in an area at a determined time, said received information comprising data indicating a convergence or migration of a plurality of mobile phone users to the area; predict clustering of said plurality of mobile phone users based on said information indicating a convergence or migration; generate a usage demand map indicating the predictive clustering of said plurality of mobile phone users movement at the area, identify, using said usage demand map, a predicted or actual increased aggregate cellular phone usage demand for said area; and determine whether there exists a mismatch of existing coverage compared with said predicted or actual increased aggregate cellular phone usage demand for said area such that additional coverage is needed at the determined time; wherein to predict clustering, said hardware processor is configured to: detect a destination of people movement; or detect a directional aspect of people movement; and said hardware processor is configured to: generate, based on a determined mismatch and in response to a destination or directional aspect detection, a plan for deploying said one or more mobile cellular unmanned aerial vehicles (UAVs) having telecommunications equipment configured to extend cellular phone network coverage of an existing land-based cellular phone network to a roaming pattern to accommodate said destination or directional aspect; and send signals to a facility configured to deploy and dispatch said one or more mobile cellular UAVs according to said plan, wherein, responsive to said signal, two or more mobile cellular UAVs are deployed to said determined area to connect with said existing land-based cellular phone network and extend cellular phone usage coverage at said area, and said hardware processor is further configured to: detect a merging of two or more mobile phone users group movements that provides a composite load to an area; determine whether two or more mobile cellular UAVs approach that area, and one of: share increased mobile cellular phone coverage by the two or more mobile cellular UAVs, or determine whether one deployed mobile cellular UAV may handle the composite load.",
    "2. The system as claimed in claim 1, wherein to determine said predicted or actual increase in aggregate cellular phone usage demand, said hardware processor is configured to: detect one or more of: incoming signal strengths from mobile phone users received at a fixed land-based cellular phone tower associated with said area, or a number of dropped call events detected of from a fixed land-based mobile cellular tower to other fixed land-based mobile cellular towers.",
    "3. The system as claimed in claim 1, wherein to determine said predicted or actual increase in aggregate cellular phone usage demand, said hardware processor is configured to: monitor said cellular phone network land-based fixed cellular phone tower bandwidth, and calculate a metric using said monitored fixed cellular phone tower bandwidth divided by a number of registered users.",
    "4. The system as claimed in claim 1, wherein said information indicating a convergence or migration includes one or more customer requests for increased coverage at said area for a specific time duration, wherein to identify said area, said hardware processor is configured to: detect customer requests from one or more of: high profile users, very important customers or customers having a contract with a cellular phone network carrier, emergency responders, personal calendar events shared voluntarily with the cellular phone network carrier.",
    "5. The system as claimed in claim 1, wherein said data indicating a convergence or migration is based on received transportation information including one or more of: data representing hired vehicle destination pick-up and drop-off locations, data representing current use of public transportation vehicles, data representing subway tickets sold to mobile phone users, wherein to determine from said information indicating a convergence or migration, said hardware processor is configured to: analyze from said received transportation information a location where people are going and a rate of change to that location; and detect if a rate of change compared to threshold is achieved that indicates a significant number of people will move in that same direction.",
    "6. The system as claimed in claim 1, wherein said data indicating a convergence or migration of many mobile phone users is based on financial transactions information, said financial transactions data including one or more types of: credit, debit, cash, ATM withdrawals transactions, wherein to determine, said hardware processor is further configured to one or more of: monitor for occurrence of an increased number of financial transactions of a particular transaction type; determine if it is a type of transaction that implies said physical convergence or migration; and determine for a trends or changes in velocity or rate of change of said as compared to a baseline measure; and in response to a determined trend or change, generate a plan for deploying said one or more mobile cellular UAVs to a roaming pattern to accommodate said destination or directional aspect.",
    "7. The system as claimed in 1, wherein said data indicating a convergence or migration of many mobile phone users is based on received social media information or conventional media information implying said convergence or migration, said social media network information data including: data from geo-tagged tweets or social media network messages from said user mobile devices, said clustering of group movement prediction being based on said geo-tagged tweets or said social media network messages.",
    "8. The system as claimed in claim 1, wherein to determine a plan to deploy a mobile cellular unmanned aerial vehicle, said hardware processor is configured to: configure an autonomic network of mobile cellular UAVs and sending signals to deploy one or more clusters of said mobile cellular UAVs network in a vicinity of or at the area; detect one or more events indicating a need for new or additional requirements; update said usage demand map based on said detected events; and autonomically redeploy or regroup one or more mobile cellular UAVs of a cluster to self correct said autonomic network based on said updated usage demand map.",
    "9. The system as claimed in claim 8, wherein to autonomically redeploy or regroup one or more mobile cellular UAVs of a cluster, said hardware processor is further configured to: establish communication among each mobile cellular UAV and a designated leader in the cluster, each said UAV's communicating data according to said updated usage demand map; monitor that one or more mobile cellular UAVs of said cluster support a particular cell phone usage demand in said area or vicinity according to said updated usage demand map, and self-correct a capacity of said cluster according to said updated usage demand map.",
    "10. A method for extending cellular phone coverage of a land-based cellular phone network comprising: receiving, at a hardware processor of a computing device, information to determine a predicted or actual increase in aggregate cellular phone usage demand in an area at a determined time, said received information comprising data indicating a convergence or migration of a plurality of mobile phone users to the area; predicting, using the hardware processor of a computing device, a clustering of said plurality of mobile phone users based on said information indicating a convergence or migration; generating, by the hardware processor of a computing device, a usage demand map indicating the predictive clustering of said plurality of mobile phone users movement at the area; identifying, using said usage demand map, a predicted or actual increased aggregate cellular phone usage demand for said area; determining whether there exists a mismatch of existing coverage compared with said predicted or actual increased aggregate cellular phone usage demand for said area such that additional coverage is needed at the determined time; wherein for predicting a clustering: detecting, using said hardware processor, a destination of people movement; or detecting, using said hardware processor, a directional aspect of people movement; and generating, based on a determined mismatch and in response to a destination or directional aspect detection, a plan for deploying said one or more mobile cellular unmanned aerial vehicles (UAVs) having telecommunications equipment configured to extend cellular phone network coverage of an existing land-based cellular phone network to a roaming pattern to accommodate said destination or directional aspect; and sending signals to a facility configured to deploy and dispatch said one or more mobile cellular UAVs according to said plan, wherein, responsive to said signal, two or more mobile cellular UAVs are deployed to said determined area to connect with said existing land-based cellular phone network and extend cellular phone usage coverage at said area, and said method further comprising: detecting, using said hardware processor, a merging of two or more mobile phone users group movements that provides a composite load to an area; determining, using said hardware processor, whether two or more mobile cellular UAVs approach that area, and one of: sharing increased mobile cellular phone coverage by the two or more mobile cellular UAVs, or determining whether one deployed mobile cellular UAV may handle the composite load.",
    "11. The method as claimed in claim 10, wherein said determining said predicted or actual increase in aggregate cellular phone usage demand includes: detecting one or more of: incoming signal strengths from mobile phone users received at a fixed land-based cellular phone tower associated with said area, or a number of dropped call events detected from a fixed land-based mobile cellular tower to other fixed land-based mobile cellular towers.",
    "12. The method as claimed in claim 10, wherein said determining said predicted or actual increase in aggregate cellular phone usage demand includes: monitoring said cellular phone network land-based fixed cellular phone tower bandwidth and calculating a metric using said monitored fixed cellular phone tower bandwidth divided by a number of registered users.",
    "13. The method as claimed in claim 10, wherein said information includes data indicating a convergence or migration of many mobile phone users to said identified area at a current or future time, said data including one or more customer requests for increased coverage at said area for a specific time duration, wherein said identifying said area comprises detecting customer requests from one or more of: high profile users, very important customers or customers having a contract with a cellular phone network carrier, emergency responders, or personal calendar events shared voluntarily with a cellular phone network carrier.",
    "14. The method as claimed in claim 10, wherein said information includes data indicating a convergence or migration of many mobile phone users to said identified area at a current or future time, said data comprising: transportation information including one or more of: data representing hired vehicle destination pick-up and drop-off locations, data representing current use of public transportation vehicles; data representing subway tickets sold to mobile phone users, wherein said determining said predicted or actual increase in aggregate cellular phone usage demand further comprises: analyzing from said received transportation information a location where people are going and a rate of change to that location; and detecting if a rate of change compared to threshold is achieved that indicates a significant number of people will move in that same direction.",
    "15. The method as claimed in claim 10, wherein said data indicating a convergence or migration of many mobile phone users is based on received transportation information including one or more of: data representing received financial transaction information, said financial transactions data including one or more types of: credit, debit, cash, ATM withdrawals transactions, wherein to determine, said hardware processor is further configured to one or more of: monitor for occurrence of an increased number of financial transactions of a particular transaction type; determine if it is a type of transaction that implies said physical convergence or migration; and determine for a trends or changes in velocity or rate of change of said as compared to a baseline measure; and in response to a determined trend or change, generate a plan for deploying said one or more mobile cellular UAVs to a roaming pattern to accommodate said destination or directional aspect.",
    "16. The method as claimed in 10, wherein said information includes data indicating a convergence or migration of many mobile phone users to said identified area at a current or future time, said data indicating a convergence or migration of many mobile phone users is based on received social media information or conventional media information implying said convergence or migration, said social media network information data including: data from geo-tagged tweets or social media network messages from said user mobile devices, said predictive clustering of group movement being based on said geo-tagged tweets or said social media network messages.",
    "17. The method as claimed in 10, wherein said deploying according to said generated plan comprises: configuring an autonomic network of mobile cellular UAVs and sending signals to deploy one or more clusters of said mobile cellular UAVs network in a vicinity of or at the area; detecting one or more events indicating a need for new or additional requirements; updating said usage demand map based on said detected events; and autonomically redeploying or regrouping one or more mobile cellular UAVs of a cluster to self correct said autonomic network based on said updated usage demand map.",
    "18. The method as claimed in claim 17, wherein said autonomically redeploying or regrouping one or more mobile cellular UAVs of a cluster comprises: establishing communication among each mobile cellular UAV and a designated leader in the cluster, each said UAV's communicating data according to said updated usage demand map; monitoring that one or more mobile cellular UAVs of said cluster support a particular cell phone usage demand in said area or vicinity, and self-correct a capacity of said cluster according to said updated usage demand map.",
    "19. A computer program product for extending cellular phone coverage of a land-based cellular phone network, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, the program instructions readable by a processing circuit to cause the processing circuit to perform a method to: receive information to determine a predicted or actual increase in aggregate cellular phone usage demand in an area at a determined time, said received information comprising data indicating a convergence or migration of a plurality of mobile phone users to the area; predict clustering of said plurality of mobile phone users based on said information indicating a convergence or migration; generate a usage demand map indicating the predictive clustering of said plurality of mobile phone users movement at the area, identify, using said usage demand map, a predicted or actual increased aggregate cellular phone usage demand for said area; and determine whether there exists a mismatch of existing coverage compared with said predicted or actual increased aggregate cellular phone usage demand for said area such that additional coverage is needed at the determined time; wherein to predict clustering, said program instructions cause the processing circuit to: detect a destination of people movement; or detect a directional aspect of people movement; and said program instructions further causing the processing circuit to: generate, based on a determined mismatch and in response to a destination or directional aspect detection, a plan for deploying said one or more mobile cellular unmanned aerial vehicles (UAVs) having telecommunications equipment configured to extend cellular phone network coverage of an existing land-based cellular phone network to a roaming pattern to accommodate said destination or directional aspect; and send signals to a facility configured to deploy and dispatch said one or more mobile cellular UAVs according to said plan, wherein, responsive to said signal, two or more mobile cellular UAVs are deployed to said determined area to connect with said existing land-based cellular phone network and extend cellular phone usage coverage at said area, and said program instructions further causing the processing circuit to: detect a merging of two or more mobile phone users group movements that provides a composite load to an area; determine whether two or more mobile cellular UAVs approach that area, and one of: share increased mobile cellular phone coverage by the two or more mobile cellular UAVs, or determine whether one deployed mobile cellular UAV may handle the composite load."
  ],
  "description_excerpt": "The present invention relates generally systems and methods for evaluating and determining the capacity of cellular networks ground based stations, and the tactical deployment and use of telecommunications-equipped unmanned aerial vehicles (UAV) or “drones” to augment the capacities and capabilities of land-based cellular network base stations.\n\nInadequate mobile device cellular phone coverage is the subject of much frustration for many users of cellular/mobile phones. When customers lack sufficient mobile signal strength, customers incur costs in the form of cellular roaming, as well as dissatisfaction with low sound quality and dropped calls. Some technologies, such as CDMA, have the ability to expand and contract cellular coverage area from a fixed tower. The number of customers registered to a particular cell affects tower range, and the signal strength of a customer can vary dramatically when sampled from the same location at different times/days. Other factors can seriously degrade signal strength, including other RF interference, and multi-path interference created by physical obstacles. Zoning laws can create difficulty in building cellular towers, and even when zoning laws are favorable, availing appropriate space at financially advantageous terms can be difficult and time consuming. In other cases, signal strength may be good but capacity remains low. In these situations, customers appear to have good signal strength, but the throughput for data/voice can be limited because of saturation at the cellular tower's back haul link.",
  "cpc": [
    "H04B 7/18504",
    "G06Q 30/0201",
    "H04B 7/2606",
    "H04M 15/68",
    "H04M 15/8038",
    "H04W 16/00",
    "H04W 16/18",
    "H04W 16/26",
    "H04W 24/02",
    "H04W 24/08",
    "H04W 64/006",
    "H04W 84/005",
    "H04W 84/06"
  ],
  "ipc": [
    "H04B 7/185",
    "H04M 15/00",
    "H04W 16/26",
    "H04W 24/08",
    "H04W 64/00",
    "H04W 16/00",
    "H04W 4/00",
    "H04W 40/00",
    "H04W 84/06"
  ],
  "assignees": [
    "International Business Machines Corp"
  ],
  "inventors": [
    "Gregory J. Boss",
    "II Rick A. Hamilton",
    "Maharaj Mukherjee",
    "Monimala Mukherjee"
  ],
  "filing_date": "2014-07-22",
  "publication_date": "2016-06-07",
  "grant_date": "2016-06-07",
  "priority_date": "2014-07-22",
  "application_number": "US-201414337598-A",
  "family_id": "55162559",
  "cited_by_count": 65,
  "citations": [
    "US7142868B1",
    "US7328363B2",
    "US20070178930A1",
    "US20080242301A1",
    "US20100273493A1",
    "US20090319654A1",
    "US20100273504A1",
    "US20120023223A1",
    "WO2013030834A1",
    "US20130303218A1"
  ]
}

Record 4,784 of 8,000 in Patents full text (MLC-0201). Request the full dataset.