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  • Παπαδόπουλος Άρης Πρόεδρος & ΔΣ [email protected]

    Building efficiency services & ICT environment

  • Building Efficiency Services and ICT


  • The building efficiency imperative

    41% buildings’ share of global emissions

    CO2 31% industry

    28% mobility

    Up to

    80% of building costs come from operations

    30% maintenance

    40% energy

    Meeting the new types of competitive disruption demands new cost efficiencies and a greener market image

    Volatile energy prices drive new requirements in strategic energy procurement

    Increasing cost pressures demand optimized energy procurement, energy efficiency and consumption control

    Increasing environmental and non - financial reporting regulations demand new capabilities in energy efficiency and carbon management

    Real estate is often

    the 2nd largest expense on organizations’ income statement

    500 climate laws passed in 66 of the world’s largest emitting countries

    50% of the energy consumed by buildings is wasted

    3Building efficiency services & ICT environment

  • They consume

    40% of all energy

    They use

    25% of all water

    Sources: CommScope/IDC Energy Insights, Business Strategy: Global Smart Building Technology Spending 2015 – 2019 Forecast Intel, Smarter Building & Homes With the Internet of Things

    They emit

    33% of all green-house gases


    The global impact of buildings

    4Building efficiency services & ICT environment

  • Growing reliance on OPEX for infrastructure upgrades

    Demanding employee expectations of workplace

    Emerging technologies becoming viable quickly

    Sustainability targets are expanding

    Evolving safety and cyber-security needs

    Aging in-house workforces and skill set gaps

    The evolution of business expectations

    5Building efficiency services & ICT environment

  • How can we better manage our operational costs?

    How can we minimize our energy spending?

    How can we share our results with building occupants?

    Unrestricted © Siemens Switzerland Ltd 2018 July 2018 Author/DepartmentPage 6 6Building efficiency services & ICT environment

  • Data Connectivity

    Building efficiency services & ICT environment

  • IEEE : Institute of Electrical and Electronics Engineers 8Building efficiency services & ICT environment

  • How Artificial Intelligence puts the ‘smart’ in smart buildings

    Building efficiency services & ICT environment


    Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. The primary aim is to allow the computers learn automatically without human intervention or assistance and adjust actions accordingly.

    • 2. DEEP LEARNING Deep learning is a type of machine learning that trains a computer to perform human-like tasks, such as recognizing speech, identifying images or making predictions. Instead of organizing data to run through predefined equations, deep learning sets up basic parameters about the data and trains the computer to learn on its own by recognizing patterns using many layers of processing.

    • 3. NATURAL LANGUAGE PROCESSING Natural Language Processing (NLP) is a key building block that will help computers learn, analyze, and understand human language

    • 4. NATURAL LANGUAGE GENERATION Natural language generation (NLG) is the use of artificial intelligence (AI) programming to produce written or spoken narrative from a dataset 5. VISUAL RECOGNITION Image recognition is used to perform a large number of machine-based visual tasks, such as labeling the content of images with meta-tags, performing image content search and guiding autonomous robots, self-driving cars and accident avoidance systems.

    Building efficiency services & ICT environment

  • OSI (Open Systems Interconnection) 11Building efficiency services & ICT environment

  • 12Building efficiency services & ICT environment

  • • Energy management services • Reporting, alarms, self learning, analytics • Smart energy services

    Service Layer

    • Sensors configuration • Real time measurement • Control

    Control Layer

    • Data aggregation G/W • ZigBee, • Mobile & Fixed BB • m2m modules

    Communication Layer

    • Smart plugs, smart electricity submeters, thermostats, cameras, motion detectors, door/window sensors

    • Smoke detectors, CO sensors, flood sensors, etc

    Smart Sensors Layer

    13Building efficiency services & ICT environment

  • Data Connectivity Technologies

    Field Device Level (Meters, sensors, actuators, IoT Devices, etc.)

    Subsystem and Automation Level

    Management Level

    Data Flow to/From the cloud

    Cloud Level Secure communication


    Data Services App


    BacNET Monitor

    Software Proxy

    PX Meter Box

    Mind Connect Nano

    14Building efficiency services & ICT environment

  • 15Building efficiency services & ICT environment

    NBIoT Energy metering Example 1

  • • Continuous Improvement • Proactive Maintenance • Occupant Comfort • Real-Time Alerts

    16Building efficiency services & ICT environment

    Cloud-Based Building Management System Example 2

  • 17Building efficiency services & ICT environment

  • 18Building efficiency services & ICT environment

  • 19Building efficiency services & ICT environment

  • 20

    2015 ASHRAE HANDBOOK: HVAC Applications

    Building efficiency services & ICT environment

  • CloudFIMs Facility Improvement


    Building efficiency services & ICT environment

  • 100%



    Why is Energy and Asset Efficiency important?

    Energy efficiency 40% Up to 40%

    of total costs of operations are related to energy

    Up to 30% of total costs of operations are related to


    30 %

    Asset efficiency

    Total cost of operation

    22Building efficiency services & ICT environment

  • 23

    2015 ASHRAE HANDBOOK: HVAC Applications

    Building efficiency services & ICT environment

    AFDD is an automatic process by which faulty operation, degraded performance, and failed components are detected and understood. The primary objective is early detection of fault and diagnosis of their causes, enabling correction of the faults before additional damage to the system, loss of service, or excessive energy use and cost result. This is accomplished by continuously monitoring the operation of a system, using AFDD processes to detect and diagnose abnormal conditions and the faults associated with them, then evaluating the significance of the detected faults and deciding how to respond. For example, the temperature of the supply air provided by air-handing unit (AHU) might be observed to be chronically higher than its set point during hot weather. This conclusion might be drawn by a trained analyst visually inspecting a time series plot of the supply air temperature .Alternatively , a computer algorithm could process there data continuously ,reach this same conclusion, and report the condition to operators or interact directly with a computer-based maintained management system(CMMS) to automatically schedule maintenance or repair services.


  • 24

    2015 ASHRAE HANDBOOK: HVAC Applications

    Building efficiency services & ICT environment

  • Results ü Remote Operational


    ü Proactive Analytics ü Performance Analysis

    ü Energy Savings ü Low Cost Data

    Driven Solution

    ü Targeted Maintenance ü Outcome Based

    Program Reporting

    CloudFIMs – Remote Analytics and Services that Drive Results

    Services Provided § Remote Corrective

    Actions – Monthly § Targeted Equipment

    Deficiency List § Quarterly Program ReviewFault Detection and Diagnostics

    3 Air Handling Units

    1 Boiler System

    1 Chiller System

    25Building efficiency services & ICT environment

  • CloudFIMs –Easily identify issues that make a difference Outside air temp sensor deviation Determines downstream HVAC systems operation and schedule High energy saving depending on severity and system configuration

    Supply air static pressure reset deviation Demand based system management

    Simultaneous Heating and Cooling Elimination Prevention of reheating and re- cooling the air simultaneously

    Boiler Reset Schedule Deviation Often changed manually or not implemented

    Supply air temperature reset schedule deviation Most commonly manually overridden parameter

    Over Ventilation Prevention Prevent heating cold o