Siemens The Connected Building - Amazon Web Servicesaws-de-media.s3. new new Planning tools Simulation

  • View
    0

  • Download
    0

Embed Size (px)

Text of Siemens The Connected Building - Amazon Web Servicesaws-de-media.s3. new new Planning tools...

  • Siemens

    The Connected Building

    AWS Summit Berlin 2018

    siemens.com Unrestricted © Siemens AG 2018

  • Premium office Data centers Industrial

    Hotels Universities

    Schools Hospitals Life science

    Corporate

    real estate

    Airports

    Malls

    Museums

    Unrestricted © Siemens AG 2018

    June 2018 Page 2 Markus Winterholer / Siemens Building Technologies

  • 41% of energy worldwide

    is consumed by

    buildings

    80% of total lifecycle

    cost of a building

    occur in the

    operation phase

    50% of workforce

    will be millennials

    by 2020

    30% of corporate real

    estate portfolios will

    consist of flexible

    office space

    Unrestricted © Siemens AG 2018

    June 2018 Page 3 Markus Winterholer / Siemens Building Technologies

  • Unrestricted © Siemens AG 2018

    June 2018 Page 4 Markus Winterholer / Siemens Building Technologies

    There are different types of customers and stakeholders

    in the building technologies sector …

    … with very different requirements

    Architects/

    Developers

    Owners Operators Tenants Visitors Construction

    companies

    Unrestricted © Siemens AG 2018

    June 2018 Page 4 Markus Winterholer / Siemens Building Technologies

  • Unrestricted © Siemens AG 2018

    June 2018 Page 5 Markus Winterholer / Siemens Building Technologies

    Why the construction industry needs IoT

    Productivity increase in the Construction industry1 Customers know – Digitization will affect every process2

    Source: 1 McKinsey Global Institute “Reinventing Construction”; February 2017 | 2 Siemens customer survey, 2014, 2015

    of customers want visualization of data 80%

    of customers expect an improved service process 69%

    of customers location- independent access to their data 65%

    of customers expect new digital services and business models 50%

  • Unrestricted © Siemens AG 2018

    June 2018 Page 6 Markus Winterholer / Siemens Building Technologies

    Building IoT Data Market

    Building in transformation1 Big data analytics2

    Outcome economy3 Connected World4

    Source: 1 Memoori Report 2016 | 2 World Economic Forum 2016 | 3 Memoori Report 2016 | 4 World Economic Forum 2016

    60% annual growth in data collected form smart buildings year over year, volume doubles every two years

    50% of the world’s data, in the history of mankind, was created in less than the last year

    Building IoT Market will grow from US$23.5 bn in 2015 to

    US$75.5 bn in 2021 with 20.7% CAGR 8 billion devices connected to the Internet today; by 2030 it is forecast that there will be 1 Trillion

  • Unrestricted © Siemens AG 2018

    June 2018 Page 7 Markus Winterholer / Siemens Building Technologies

    Building Data

    Example Office Building

    ~200 Gigabytes static data

    ~60 Sensor types

    ~2,000 Datapoints

    >500 MB data per day or ~200 GB per year

    Siemens Requirements

    500,000 commercial buildings  100 Petabytes per year

    ~30 years operation phase  3 Exabytes

    Availability in 4 regions, 160 countries

    Access for 12,000 service engineers and millions of users

  • Unrestricted © Siemens AG 2018

    June 2018 Page 8 Markus Winterholer / Siemens Building Technologies

    Let’s turn this data into knowledge in order to enhancing building performance and improve user experience

    and generating data

    Unrestricted © Siemens AG 2018

    June 2018 Page 8 Markus Winterholer / Siemens Building Technologies

  • Unrestricted © Siemens AG 2018

    June 2018 Page 9 Markus Winterholer / Siemens Building Technologies

    Creating perfect places based on Services – User Centric

    focus as a holistic approach to the modern workplace …

    Customer Interest Relevant KPI’s

    Cost per space unit

    Employee satisfaction

    CO2 emissions

    Employee productivity

    Optimizing CAPEX and OPEX

    Energy and

    asset efficiency

    Space

    efficiency

    Individual efficiency

    and comfort

    Workplace Utilization

    Revenue per space unit

    Vacancy Rate

    Asset Performance/Useful Life

  • Unrestricted © Siemens AG 2018

    June 2018 Page 10 Markus Winterholer / Siemens Building Technologies

    Enhancing building performance through the power of data

    Holistic approach to digitalization

    Unrestricted © Siemens AG 2018

    June 2018 Page 10 Markus Winterholer / Siemens Building Technologies

  • Unrestricted © Siemens AG 2018

    June 2018 Page 11 Markus Winterholer / Siemens Building Technologies

    “Charter of Trust” as basis for joint development

    of digitalization and cyber security

  • Unrestricted © Siemens AG 2018

    June 2018 Page 12 Markus Winterholer / Siemens Building Technologies

    Digital Twin – Bringing Construction Plans and IoT together

    CO2

    WHAT is going on WHERE?

    Digital Twin

    http://www.google.de/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&ved=0ahUKEwjd25CY6JnYAhVM6xQKHaE3ASIQjRwIBw&url=http://africabook.info/buildings-floor-plan.html&psig=AOvVaw0EKejJvuCvRpuCd9YWb5K-&ust=1513901316228621

  • Unrestricted © Siemens AG 2018

    June 2018 Page 13 Markus Winterholer / Siemens Building Technologies

    BT Digital Twin – Four steps from isolated data silos to an

    integrated building knowledge base

    Technology Benefits

    Digital Twin

    APIs

    Data

    Federation

    Rules and

    Predictions

    Knowledge

    Graph

    4

    3

    2

    1 Access

    Link

    Enhance

    Provide

    • Rules and constraints

    • Machine learning

    • Graph databases

    • Semantic data models

    • Virtual or physical data integration

    • Query rewriting

    • (Micro) Services

    • Automated completion and validation of

    integrated building knowledge base

    • Flexible semantic data model

    • Link objects across data sources

    • Intuitive query formulation for users

    • Easy integration of new data sources

    • Support for heterogeneous interfaces

    and data formats

    • Contextualized data access

    • Continuous development

  • Unrestricted © Siemens AG 2018

    June 2018 Page 14 Markus Winterholer / Siemens Building Technologies

    A semantic data model enables flexible linking and an

    integrated, intuitive API for applications

    Semantic Data Model 2

    3

    1

    new new

    Planning

    tools

    Simulation

    tool

    Building

    Operations

    Security aaS Building

    Performance

    Service Portal Location Ba-

    sed Services

    Novel BT

    Services

    3rd party

    Services

    Connect

    to data

    Drive

    applications

    BT Knowledge

    Graph

    ETL or

    Virtual Integration Customer Data

    Weather Data

    Public Energy Data

    MindSphere Building Structure

    (e.g. BIM IFC)

    Product Data

    www

    4

    Data API IFC import/

    GraphicsAPI Product API

  • Unrestricted © Siemens AG 2018

    June 2018 Page 15 Markus Winterholer / Siemens Building Technologies

    Bu

    AWS IoT

    Amazon Elasticsearch Service

    Amazon Kinesis

    Amazon Kinesis

    Firehose Sensors

    Building

    Amazon S3 Amazon

    SageMaker

    Kibana Dashboard

    MindSphere

    Time Series Data from Sensors

    IoT Connectivity

  • Unrestricted © Siemens AG 2018

    June 2018 Page 16 Markus Winterholer / Siemens Building Technologies

    Visualizing Timeseries Sensor Data

  • Unrestricted © Siemens AG 2018

    June 2018 Page 17 Markus Winterholer / Siemens Building Technologies

    MindSphere

  • Unrestricted © Siemens AG 2018

    June 2018 Page 18 Markus Winterholer / Siemens Building Technologies

    Amazon Neptune Graph Database maintains the logical data

    model and links to other data sources

    Load Property Graph and RDF Data Store billions of relationships Fast graph queries

    https://aws.amazon.com/de/neptune

    Amazon S3

    Property Graph

    CSV

    Resource Description

    Framework (RDF)

    Turtle

    N-Triples

    N-Quads

    RDF/XML

    Bulk

    Load API

    SPARQL

    Endpoint

    Gremlin

    Server

  • Unrestricted © Siemens AG 2018

    June 2018 Page 19 Markus Winterholer / Siemens Building Technologies

    Amazon Neptune IFC Ontology Meta-Model

  • Unrestricted © Siemens AG 2018

    June 2018 Page 20 Markus Winterholer / Siemens Building Technologies

    Building Model Visualization