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Big data for social good


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How Telefonica uses big data, machine learning and artificial intelligence to connect the unconnected

Published in: Technology

Big data for social good

  1. 1. Connect the unconnected: Internet para todos Patrick Lopez VP Networks Innovation at Telefonica
  2. 2. 3 programme to connect the unconnected
  3. 3. 4 100 million people live in Latin America without access to the internet because of… geography, orography, economic conditions, density y population dispersion, … …current technologies are insuficient Big data & Connect the Unconnected We are using Big Data, Machine Learning and AI to : • Localize and identify the unconnected, • Optimize our transport network • Optimize our network operations
  4. 4. 5 With AI we pinpoint the actual demand… + Data: satellite images model: Neural network Training: census data Result: actual population distribution map …and we compare it with the network map… = Data: geolocalized mobile sessions Model: coverage polygons Training: Telefónica coverage and regulatory data Result: Real coverage map … we then deduce the unconnected population Result: clasification y clusterization of the uncovered population Where are the unconnected?
  5. 5. 6 2o Neural network literally identify every building 3o 4o 1o Super HD digital satellite images Houses are grouped and compared with census data RESULT: HD population distribution model Of the population localized with <3% false positives95 % With AI we pinpoint the actual demand…
  6. 6. 7 1o 2o 3o 4o Geolocalized mobile sesión and network data Towers location and estimation of the coverage Calibration based on reported coverage and Telefonica data RESULT: actual network coverage Is the median error for tower location240m …and we compare it with the network map…
  7. 7. 8 Transport networks are the most expensive part of deploying connectivity to remote areas. Optimizing transport route has a huge impact on the sustainability of a network. Big data and graph theory enable us to analyze and compute the optimal transport deployments. AI to optimize the transport network
  8. 8. 9 We integrate the infrastructure information… …we then generate weighted graphs projecting the opportunity.. … we then compute the optimal deployment + = Data: detailed infrastructure Model: geolocalized data Result: infratructure map of twoers and roads Data: clustered opportunity Model: graph generation Result: Graph with population weighted transport options Model: Graph analysis (Shortest path, Steiner tree) Result: population cluster optimized transport routes AI to optimize the transport network
  9. 9. 10 To connect very remote zones, optimizing operations and minimizing maintenance and upgrade is key to a sustainable operational model. AI to optimize networks operation
  10. 10. 11 We identify the cells that have the most probability of failure Automated preventative error prediction We optimize and reduce network operations + = Data: network metrics Model: neural network Training: historical failure analysis Result: possible cells failure map Data: alarms and outages Model: task automation Result: automated supervisión and preventative outage prediction Result: supervisión is automated and less incidence of failure AI to optimize networks operation
  11. 11. 12 We capture in real time health data of network elements 1o 2o We determine the conditions of the most common failures We predict which cells could fail 3o We create a system that monitors alarms and evaluates the scenarios 4o Supervision is automated (Operations Bot) and we predict failures AI to identify and predict network outages
  12. 12. 13 So what does all of this has to do with climate change and natural disasters?
  13. 13. 14 El nino costero 2016 - Peru
  14. 14. 15 Emergency plan Peru NORTH: Piura/Catacaos CHIMBOTE: Pampacancha, Huarmey LIMA: Carretera Central Source: Telefonica Rural Planner
  15. 15. 16 altitude @20km 1st Operator in the world using Loon for emergency LTE High capacity transport >5.000km2 of coverage
  16. 16. Follow us online! 2018 © Telefónica Digital España, S.L.U. Todos los derechos reservados. La información contenida en el presente documento es propiedad de Telefónica Digital España, S.L.U. (“TDE”) y/o de cualquier otra entidad dentro del Grupo Telefónica o sus licenciantes. TDE y/o cualquier compañía del Grupo Telefónica o los licenciantes de TDE se reservan todos los derechos de propiedad industrial e intelectual (incluida cualquier patente o copyright) que se deriven o recaigan sobre este documento, incluidos los derechos de diseño, producción, reproducción, uso y venta del mismo, salvo en el supuesto de que dichos derechos sean expresamente conferidos a terceros por escrito. La información contenida en el presente documento podrá ser objeto de modificación en cualquier momento sin necesidad de previo aviso. La información contenida en el presente documento no podrá ser ni parcial ni totalmente copiada, distribuida, adaptada o reproducida en ningún soporte sin que medie el previo consentimiento por escrito por parte de TDE. El presente documento tiene como único objetivo servir de soporte a su lector en el uso del producto o servicio descrito en el mismo. El lector se compromete y queda obligado a usar la información contenida en el mismo para su propio uso y no para ningún otro. TDE no será responsable de ninguna pérdida o daño que se derive del uso de la información contenida en el presente documento o de cualquier error u omisión del documento o por el uso incorrecto del servicio o producto. El uso del producto o servicio descrito en el presente documento se regulará de acuerdo con lo establecido en los términos y condiciones aceptados por el usuario del mismo para su uso. TDE y sus marcas (así como cualquier marca perteneciente al Grupo Telefónica) son marcas registradas. TDE y sus filiales se reservan todo los derechos sobre las mismas.