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Smau Milano 2015 - Cisco

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Internet delle Cose e Trasformazione del Business: Smart Manufacturing e Smart Business

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Smau Milano 2015 - Cisco

  1. 1. Internet delle Cose e Trasformazione del Business: Smart Manufacturing e Smart Business Diego Zucca dzucca@cisco.com @dzucca
  2. 2. Internet of Everything (IoE) Source: “The Internet of Everything: A $19 Trillion Opportunity,” Cisco Consulting Services, 2014 Leveraging Data into More Useful Information for Decision Making Data Delivering the Right Information to the Right Person (or Machine) at the Right Time Process Connecting People in More Relevant, Valuable Ways People Physical Devices and Objects Connected to the Internet and Each Other for Intelligent Decision Making (IoT) Things
  3. 3. IoE is driving exponential change By 2020, there will be approximately 50 billion objects connected to the Internet IOE accelera +250 progetti presentati all’evento IoT WF $23B sensori venduti nel 2014 (x2 rispetto al 2013) 4x Google Search e 5x copertura stampa su IoT nel 2014 300,000 sviluppatori IOT nel 2014 (+50% rispetto al 2013)Proiezione investimenti VC in IoT per il 2014: $1.6B (+45% YoY ; 10% del totale) Il fatturato IOT cresce 4 volte più velocemente rispetto a quello dell’IT $4.1B Connessioni M2M Source: Factiva, IMS, Intel, Google, cbinsights, Cisco, E&Y, IOT WF
  4. 4. .. and even more By 2020, there will be approximately 26 objects connected per single person  250 Billion objects connected to Internet
  5. 5. How many microprocessors are used today for the electronics? 1 out 10 It will be 1 out 1000
  6. 6. The Opportunity $19.0* Trillion Value at Stake $14.4T Private Sector Includes both industry-specific and horizontal use cases. • Customer Experience • Innovation • Employee Productivity • Supply Chain • Asset Utilization • Increased Revenue • Reduced Cost • Employee Productivity • Connected Militarized Defense • Citizen Experience $4.6T Public Sector Includes cities, agencies, and verticals such as healthcare, education, defense. * 2013-2022 Estimate is based on bottom-up analysis of 61 use cases, including 21 for private sector and 40 in public sector
  7. 7. The Opportunity The Internet of Things represents an opportunity to grow aggregate global corporate profits approximately 21% by 2022. Between 2013–2022 Fueled By: Supply Chain/Logistics $2.7T Innovation $3.0T Customer Experience $3.7T Employee Productivity $2.5T Asset Utilization $2.5T Source: Cisco Internet Business Solutions Group, 2013
  8. 8. IoE Consists of M2M, M2P, and P2P Connections Machine-to-Machine (M2M) • Data sent/received from one machine (thing) to another • Often called the “Internet of Things” $7.4 Trillion Machine-to-Person (M2P) • Data sent/received from a machine (thing) to a person • Often called “data and analytics” $4.6 Trillion Person-to-Person (P2P) • Data sent/received from one person to another • Often called “collaboration” $7.0 Trillion IoE Value (2013-2022)Connection Type
  9. 9. • www.cisco.com/go/vni • Growth of Mobile traffic will be 3x than growth of fixed traffic • More mobile users, More connection, More speed, More video • … but M2M contribution will be crucial (smart metering, maintenance, asset management, building automation, automotive, healthcare and wearable electronics)  from 495M to 3B Bottom-Up Analysis Visual Networking Index (VNI)
  10. 10. • IT & Networks • Security & Public Safety • Retail • Transportation • Industrial • Healthcare & Life Science • Consumer & Home • Energy • Buildings
  11. 11. Cisco Confidential© 2010 Cisco and/or its affiliates. All rights reserved. 11 PROCESS MANUFACTURING ENERGY TRANSPORTATION CITIES RETAIL
  12. 12. M2M, M2P, P2P and Combined Connections Machine-to-Machine (M2M) Connections (IoT) Machine-to-Person (M2P) Connections (Data and Analytics) Person-to-Person (P2P) Connections (Collaboration) Highest-Value IoE Business Models and Innovations IoE
  13. 13. Using M2M Connections to Monitor Assets Business Problems Solved • Value from lighting up “dark” assets? • What’s their location? • What’s their condition? • Are they secure? IoE Asset Monitoring M2M (IoT) P2P (Collaboration) M2P (Data and Analytics)
  14. 14. Asset Monitoring IoE M2M (IoT) P2P (Collaboration) M2P (Data and Analytics) Challenge • Long tire assembly search times by operators increased cycle times, decreased labor optimization, and noncompliance with production schedules. High scrap rate associated with lost carriers. • Increase production and efficiency in manufacturing plants Solution • Use Wi-Fi sensors to make handlers/truckers/managers to monitor production and to integrate with inventory tracking system and search for components by ID, tread number, …and alert low inventory on plant floor • Enabled by Cisco’s Unified Wireless Network, wireless endpoints • AeroScout; Wi-Fi tags and MobileView software • Global Data Sciences: Material Inventory Tracking Sytstem (MITS) software Business Value • Increased tire production by 13% • Cut wasted tire components by 20% • Payback n 6 months
  15. 15. Combining Connections (M2M + P2P) IoE Challenge • Productivity: Improve production without increasing headcount or other resources • Optimize Business Process: Create greater visibility and intelligence in underground operations Solution • Wi-Fi network combined with sensors on personnel and equipment, instant video collaboration among miners and engineers underground, on-site supervisors, and Toronto-based experts  Wired and Wireless Networking, UC, DC and Security Business Value • 400% improvement in mine’s production, improved safety https://www.youtube.com/watch?v=SGxJLUS7h QQ M2M (IoT) P2P (Collaboration) M2P (Data and Analytics) + Business Transformation in Action Changing the dynamics of how the business is run: Operational Excellence and Productivity
  16. 16. Combining Connections (M2M + M2P) IoE Challenge • Management and monitoring of distributed healthcare lab systems and solutions • Speed and efficiency of interventions • Visibility and intelligence in the operations Solution • Machine-to-machine (M2M) applications able to use 3G wireless WAN secure network services to extend the management and monitoring capabilities to remotely dispersed platform Business Value • Reduction of on-site interventions and related costs • Predictive modeling/analysis for maintenance • Improved visibility M2M (IoT) P2P (Collaboration) M2P (Data and Analytics) + Business Transformation in Action Changing the dynamics of how the business is run: Operational Excellence
  17. 17. Combining Connections (M2M + M2P +P2P) IoE Challenge • Full Paper Only-Local (expert) Visibility of the Machine Operations • Very slow understanding of production dis-alignment in speed or quality • Speed and efficiency in team and different organizations collaboration Solution • Full IT/OT integration through Industrial Ethernet capabilities to achieve the operational Machine paperless real-time information anytime/anywhere/anydevice Machine-to-machine (M2M) applications (state of the machines, on/off, production information that can define the vision of the current state for rapid business decisions) • Full P2P Collaboration (cross team and remote diagnostics) Business Value • Productivity • Visibility, Speed of Resolution, Reduction of on-site non- real-time interventions and related costs • New business processes: assistance production machines remotely over the network Business Transformation in Action Changing the dynamics of how the business is run: Operational Excellence and Competitive Differentiation + + M2M (IoT) P2P (Collaboration) M2P (Data and Analytics)
  18. 18. Maximizing the Value with Multiple Connections Business Problems • How can I differentiate myself from competitors? • How can I create compelling products, services, and experiences at a lower cost? Challenges and Business Value • Attract Customers • Energy/Cost Savings • New Services • Visibility • … IoE Business Transformation + + Business Transformation in Action Changing the dynamics of how the business is run: Competitive Differentiation and New Business Models Highest-Value IoE Business Models and Innovations Highest-Value IoE Business Models and Innovations Business Transformation in Action The Network is where connections are combined M2M (IoT) P2P (Collaboration) M2P (Data and Analytics)
  19. 19. • Shelf sensors • Parking-space sensors • IR motion sensors • Weight mats • Environmental (light, temp) sensors • Door sensors • Mobile payments • Energy meters Value of Combined ConnectionsImpacts M2M Connections Flexible Payment Options Automated Ordering Process Inventory Visibility Energy Efficiency • Converged IP factory network • Sensors (vibration, HVAC, lighting) • Actuators • Sensor-to-ERP connectivity • I/O machines • Process operation controls • Product packaging Predictive Maintenance Flexible Production Remote Asset Monitoring • Smart buildings and campuses • Smart lighting • Smart payments • Intelligent public transit • Smart grid Citizen/Employee /Student Experience Improved Asset Utilization New Revenue Streams Energy Optimization • Car sensors • Appliance sensors • RFID • Digital billboards • Unused inventory • Office facilities • Trucks Intelligent Diagnostics M2M CommerceRemote Site Monitoring Service Targeted Advertising
  20. 20. Benefits and RoI
  21. 21. Ecosystem/Partner/Cisco Roles Ecosystem/ Partner IP Connectivity App Enablement PartnerElectric Metering Train Control Street Parking Environmental Monitoring Access Technologies Access Technologies Manufacturing Plantwide Ethernet, Intelligent Transportation, Smart Cities, S&C Refinery, Smart Connected Vehicle, Smart Grid Energy-UtilityMining Oil and Gas Transportation City Defense SP/M2M Domain Specific and/or Proprietary Devices and Protocols Domain Specific Applications IE 2000 IE 3000 CGS2000 Industrial Switching IP67 IE 4000 IE 5000 Industrial Routing CGR 2000 ASR 903 Industrial Wireless Field AP - 1552 Field AP - IW 3700 802.11ac Field Network CGR 1000 819H 809H IR910 IR 509 829H Embedded Networks 5900 ESR, ESS 2020 Switches 5921 ESR Software Router Connected Safety & Security Video Surveillance Manager and IP Cameras Physical Access Manager
  22. 22. IoT Requires Distributed Computing TRADITIONAL COMPUTING MODEL (TERMINAL-MAINFRAME, CLIENT-SERVER, WEB) ENDPOINT DATACENTER/CLOUD
  23. 23. IoT COMPUTING MODEL (DATA VOLUME, SECURITY, RESILIENCY, LATENCY) DEVICE DATACENTER/CLOUD FOG IoT Requires Distributed Computing
  24. 24. Data Usage • Mine (fetch) • Analyze • ReportUsage Data ! Generate an Actionable Event that is sent to the Policy System, Management System, etc. to allow immediate consumption Next Generation Analytics Applies predicates, aggregations, and joins with metadata tables and contextual data to identify and match trends. Querybase Waiting for Data Store raw data or filtered data for further mining. Database Waiting for Queries Store raw data for further mining. Traditional Analytics Model Store first, and query later. Usage Data • Mine (fetch) • Analyze • Report Real time decisions Low Latency Data Reduction
  25. 25. La Comunicazione fra noi ed il mondo non e’ qualcosa che ci distingue dal resto della natura. Le cose del mondo interagiscono in continuazione l’una con l’altra e, nel fare cio’, lo stato di ciascuna porta traccia dello stato delle altre con cui ha interagito. In questo senso esse si scambiano di continuo informazione le una sulle altre Carlo Rovelli (fisico e filosofo della scienza contemporaneo) “ ” Internet of InterActions
  26. 26. Grazie

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