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How Internet of Things, Artificial Intelligence and Autonomous Machines are disrupting utilities

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September 2018 at CTTC, Barcelona: discussing how progress in IOT, AI and Autonomous Machine is changing the operations in utilities.

It starts with better efficiency, and ends with disruption of incumbents.

Published in: Technology
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How Internet of Things, Artificial Intelligence and Autonomous Machines are disrupting utilities

  1. 1. Alain Staron Innovation Catalyst, Amborella Board Member, ETSI Former Senior VP Digital, Veolia CTTC Workshop September 21st , Sitges Barcelona Harvey Wiley Corbett's 'City of the Future' 1913 For New York Sidewalk Labs’ Alphabet futuristic city 2018 forToronto
  2. 2. Water Networks Utilities: some specificities Plants Networks Endpoints
  3. 3. Orders of magnitude 1 M Inhabitants 500 000 Meters 8 000 km of pipes 500 km²
  4. 4. At Stake
  5. 5. At Stake
  6. 6. Water availability (in 000’s m3 per person per year) <1.0 = Scarcity 1.1 - 2 = Stress 2.1 - 5 = Vulnerability 5.1 - 10 = Medium 10.1 - 20 = OK >20 = No problem At Stake
  7. 7. São Paulo, in 2015, the main reservoir fell below 4% capacity At the height of the crisis, the city of over 21.7 million inhabitants had less than 20 days of water supply and police had to escort water trucks to stop looting Bangalore city loses over half of its drinking water to waste. In-depth inventory of the city's lakes found that 85% had water that could only be used for irrigation and industrial cooling Beijing In 2014, each of the more than 20 million inhabitants of Beijing had only 145 cubic metres (water scarcity as when people in a determined location receive less than 1,000 cubic metres of fresh water per person a year.) Cairo The UN estimates critical shortages in the country by 2025 Jakarta Less than half of the city's 10 million residents have access to piped water. Aquifers are not being replenished despite heavy rain because the prevalence of concrete and asphalt means that open fields cannot absorb rainfall. Moscow Official regulatory bodies admit that 35% to 60% of total drinking water reserves in Russia do not meet sanitary standards. One-quarter of the world's fresh water reserves are in Russia Istanbul The city's reservoir levels declined to less than 30 percent of capacity at the beginning of 2014. Mexico City One in five get just a few hours from their taps a week and another 20% have running water for just part of the day London With an average annual rainfall of about 600mm (less than the Paris average and only about half that of New York), London draws 80% of its water from rivers (the Thames and Lea). The city is pushing close to capacity and is likely to have supply problems by 2025 and "serious shortages" by 2040. London has a water waste rate of 25%. Tokyo Miami Melbourne … At Stake
  8. 8. Leakage At Stake
  9. 9. Pollution At Stake
  10. 10. Flood At Stake
  11. 11. Consumption At Stake
  12. 12. Operations
  13. 13. Operations
  14. 14. Operations
  15. 15. Operations
  16. 16. Operations VEDIF 149 municipalities Waiting time for a appointement from 7 down to 2 days Shanghai 3.6 million inhabitants service x 2 Employees -20% Prague 4,279 km Time to solve an incident down by 30% Lyon 1.3 million customers 12 million m3 Decrease of water losses by contract SMARTENING THE WHOLE WATER CYCLE
  17. 17. Operations Metering Scada Gutermann Veolink Kruger - - - Hypervision systems for water networks
  18. 18. Operations Hypervision systems Sensors map Data Alerts S.O.P. Predictive
  19. 19. Operations Technologies Sensors map Data Alerts S.O.P. Predictive IoT The Internet of Things C2C Consumer Platforms AI Artificial Intelligence AM Autonomous Machines
  20. 20. Operations The big picture boosting CITY’s DIGITAL TRANSFORMATION Urban X Digital Products Urbanlake Urbannamics Urbanboard UrbanbotsUrbanpulse
  21. 21. Operations The big picture Ecosystems connections Performance of Infrastructures Infrastructures for Inhabitants Engaged Inhabitants
  22. 22. Operations The big picture Joint Solution Architecture by Veolia and Huawei NB-IoT devices Telecommunications layer Applications Global rendering engines Ecosystem of partners WASTENAMICS BUILDINGSNAMICS WATERNAMICS HEATNAMICS ENERGYNAMICS NB-IoT Devices NB-IoT Devices NB-IoT Devices NB-IoT Devices NB-IoT Devices NB-IoT Devices HuaweiSafeCity E2Esolution
  23. 23. Next move ?
  24. 24. The Gardener Dilemna
  25. 25. Autonomous Infrastructures Devices to embed Services
  26. 26. Challenges
  27. 27. Local coverage Deep meters Nationwide coverage Ground level detection Nationwide coverage Deep meters Regulated licenses Worldwide standard Cost efficiency Other proprietary technologies Prioprietary business case (for wealthy customers) Huge fundraising (100M€…) for 1000’s antennas 10 000’s high points already available Low cost upgrade of mobile networks Fix radio networks Cellular IoT 2016 Challenges Standard
  28. 28. Local coverage Deep meters Nationwide coverage Ground level detection Nationwide coverage Deep meters Regulated licenses Worldwide standard Cost efficiency Other proprietary technologies Prioprietary business case (for wealthy customers) Huge fundraising (100M€…) for 1000’s antennas 10 000’s high points already available Low cost upgrade of mobile networks Fix radio networks Cellular IoT 2016 Challenges Standard
  29. 29. Local coverage Deep meters Nationwide coverage Ground level detection Nationwide coverage Deep meters Regulated licenses Worldwide standard Cost efficiency Other proprietary technologies Prioprietary business case (for wealthy customers) Huge fundraising (100M€…) for 1000’s antennas 10 000’s high points already available Low cost upgrade of mobile networks Fix radio networks Cellular IoT 2016 Challenges Standard !
  30. 30. Challenges Power 15 years life time – 2 messages 1kO /day – 3$ battery 1 µA sleeping current – light protocol
  31. 31. Challenges Privacy Split principle: Storage + Process <> Encryption
  32. 32. Challenges Privacy Data Production >> Data Transfer capacity Data errors correction with temporal + spatial correlations
  33. 33. Challenges Swarms
  34. 34. Challenges Multitude Efficiency Governance Usage
  35. 35. Vision
  36. 36. Homo Urbanus
  37. 37. Autonomous Cities
  38. 38. Market Places
  39. 39. Homo Urbanus
  40. 40. AlainStaron Thank you  ! Patents Industry Business • Use Cases • Technologies

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