1. User Profiling and Ambient UIs
WP3
Task 3.5
User Profiling and Ambient UIs

2. Environmental Conditions Related User Profiling
User Profiling Analysis Objectives - Steps
to monitor environmental conditions that reveal the comfort and discomfort preferences of the occupant’s. The environmental conditions will be available through the respective sensors (Temperature, Humidity, Luminance), to be installed within the INERTIA pilot area. These events are aligned with occupancy events in order to proceed with the integrated analysis
to monitor user control actions - reactions in specific environmental conditions, in order to seamlessly provide an effective and efficient learning scheme for the extraction of User Preferences
INERTIA user profiling mechanism will minimize or eventually eliminate required occupant interaction and thus overall occupant disturbance. The overall scope is the alignment of environmental conditions with user actions/reactions towards the extraction of preference/non preferences patterns
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Highlight main challenges
- elasticity is more a function of occupancy and user preferences than price
- the complexity problem due to dimensionality as well as dynamic nature of the contextual parameters (occupants some times change their behavior, also in certain spaces (and respective DER) new occupants/owners are introduced each day that must be captured by the system, new DER are introduced, new environmental conditions could be encountered that have not been part of the training data/period).
Therefore we need :
- a multidimensional contextual approach
- a continuously adaptive approach
- an approach that should quantify the relation between DER real time elasticity and user behavior
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3. T3.5 - User Profiling Approach
A high level overview of User Profiling algorithmic approach – Learning approach
Normalized data from raw data events are delivered in the State Estimator Normalization of data in 60 lux level for Luminance events & 0.5 oC for Temperature events.
State Estimator is a knowledge based components that defines the rules for the learning mechanism (Aggregation of events, decision about the learning period of the model, weighted values on control action events)
Learning Model Defines the Utility Function Parameters and User related statistics that further be stored in a database (in INERTIA: Local Hub IAM) for further evaluation
Business Services Component : Provides an API with information related to the learning model about User Preferences. The context information is useful for the control and optimization mechanism of the INERTIA Local Hub .
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The Evaluation – learning Cycle should be highlighted and provide hints for the re-inforcement learning technique.

4. T3.5 User Profiling Main Aspects (II)
User Profiling Dependencies
Utility Estimation Approach
INERTIA Holistic Flexibility Component.
Input : Occupancy Status, Environmental Conditions (Luminance, Temperature, Status of Device)
Output: Thermal or Visual User Comfort/ Discomfort level in a scale of [0…1]
INERTIA Information Access Module.
Input: Historical events (environmental conditions, occupancy details, Control actions delivered by the users) in order to provide a continuous learning operation
Output: Learning Model Parameters as defined by the learning mechanism
Providing the necessary input for the extraction of the Holistic Flexibility Models and therefore the optimal controlling of the DER units
Comments:
To examine different approaches
User profiling implemented by ALMENDE (HYPERTECH to provide the algorithmic approach)
User profiling as an engine – out of the MAS
User profiling implemented by HYPERTECH (Not possible)
User profiling dependencies. The relationship with external components of INERTIA Architecture.

5. User Profiling - INERTIA DERs
Different types of DERs in INERTIA Project:
Environmental Conditions related Devices (HVAC, Lighting). The estimation of the Utility function (User Preferences) is based on the environmental conditions and not the operational status of the devices. Thus, an (Environmental conditions  Comfort Performance) model is defined:
Input data: f(user_Id, from Date, environmental_aspectID)
<timestamp> T16:23: :00</timestamp>
<eventTypeId>1</eventTypeId> (1 environmental event, 2 control action event)
<environmentalConditionId>2</environmentalConditionId> (0 Control Action, 1 Luminance, 2 Temperature, 3 Humidity)
<status></status>
<value>150.0</value>
Output: f(user_Id, environmental_valuesID)
Any statistical analysis needed Data available through IAM
<environmentAspectId>1</ environmentAspectId >
<averageEnvironmentalComfortLevel>0.8</averageEnvironmentalComfortLevel>
<groupId>0</groupId>
<maxAcceptedLevel>250.0</maxAcceptedLevel>
<minAcceptedLevel>150.0</minAcceptedLevel>
<optimalLevel>200.0</optimalLevel>
<timestamp> T15:24: :00</timestamp>
<unitRef>lux</unitRef>
<userId>1</userId>

6. User Profiling - INERTIA DERs
Different types of DERs in INERTIA Project:
Operational Devices: Shiftable devices. The role of the User Profiling mechanism is to provide the operational patterns for the specific devices. This information could be handled by the Local Hub Control mechanism for the optimal management of the operational devices.
Operational Devices: EVS devices. The role of the User Profiling mechanism is to provide the operational patterns for the specific devices taking into account the actual SoC at the end of the process.
Types of events needed:
Thermal Aspects  Captured by Sensors/Actuators
Temperature Events (event based approach: every 0.4 C with a minimum of 2 minutes as inertia for stable state).
Humidity Events (event based approach: 10% scaling with a minimum of 2 minutes as inertia for stable state)
Control Events (event based approach with a minimum of 10 seconds of inertia for stable state)
Visual Aspects  Captured by Sensors/Actuators
Luminance Events (event based approach: every 40 lux with a minimum of 10 minutes as inertia for stable state).
Electric Vehicles  Captured by smart plugs/ Charging point???
SoC at the end of the charging process If possible to capture the SoC at the beginning of the charging process .
Shiftable Vehicles  Captured by smart plugs
Control actions delivered and aligned with the users_IDs
Delayed processes in order to define the User Preferences (Monitoring& Control Component to provide the relevant Info Delayed Process)

7. T3.5 - User Profiling Approach Overview
What we need - Summary
Utility function estimation for each occupant taking into account the real time context conditions  Occupancy data
Utility function totally dependent on the context (environmental impact, operational situations etc.) Context data (environmental conditions, control actions on DERs)
Different approaches to be examined in INERTIA Project:
Single occupant with ID. The estimation of the preferences is delivered in a personalized way. Initial settings of User preferences are provide through the Ambient UI.
Multiple Occupants in a specific zone  Group Profiling Main Aspects. To further examine the impact of different occupancy patterns and define additional group profiles if needed.
Flexibility estimation for each type of occupancy provided to Holistic Flexibility Model
getUtilityLevel(int occupantOrGroupId, int environmentalAspectId, ListofValues)
Critical: The aforementioned analysis takes into account the a-posteriori analysis of events and extraction of Utility function. Interface with ALMENDE have been discussed. To be provided within the next period.

8. T3.5 – Ambient UI - Overview
Ambient UI Objectives:
Thus, the development of the Ambient UI concept includes the implementation of different
types of interfaces:
for the occupants: different ways to visualize high-level information about the energy consumption of area, in order to increase occupants' awareness. Only monitoring functionalities are provided as the direct enrollment of the User in Demand Response Actions are out of the scope of the INERTIA project
for the manager of the building: visualization of real-time (aggregated and correlated) information on the energy consumption of the building, in order to have real-time information and apply suitable energy strategies. (Monitoring and control functionalities)
This slide defines the main objectives and the role of Ambient Interface.
You are pleased to refine or add more detail on the existing information.
You should further check the DoW (p.25 and p ) mentioning the role of INERTIA Ambient UI.

9. Allocation of work among partners
2nd project review Scenarios to be visualized
Mobile and Tablet All the /defined views (a limited number is addressed as non intrusive interface)
Log In process
Real time information (Energy Consumption, Temperature, Humidity, Luminance Level) Captured by Linksmart
Static Data related to User Preferences (Settings and Operational Preferences for Thermal, Visual, EVs) IAM (BIM related parameters)
Historical data (Energy Consumption and Temperature/Luminance [only for tablet view]) IAM
Calendar settings
Settings related to alignment of Devices with users  IAM (BIM related parameters)

10. Allocation of work among partners
2nd project review Scenarios to be visualized
Web Interfaces for Facility Managers A limited number of views to be provided:
Premises Schema (Static View) and real time information per space and overall  Link smart
Energy Consumption, Occupancy, Environmental Conditions
Overall Energy Consumption – Historical Analysis IAM
Cost of Energy Consumption – Historical Analysis IAM (Energy Consumption+ Tariffs)
Schedules (???)IAM
Operational Status  COMFORT MODE, ENERGY EFFICIENCY MODE, DEMAND RESPONSE
Devices Settings on available Devices (HVAC temperature &ON/OFF, Dimmers Level) Link smart

11. Common Services among Applications
Tablet and Web Interfaces - Common Services:
Real time capturing of aspects for spaces (temperature, humidity, occupancy, energy consumption) LinkSmart
Overall Energy Consumption –Historical Analysis IAM (Granularity per space/ DER Type)
Environmental Conditions – Historical Analysis IAM (Granularity per space)
Schedules Settings (???)IAM
Extra Services to be supported
Overall Cost of Energy – Historical Analysis IAM (Granularity per space/ DER Type)
Operational Mode (Configuration, Statistics) IAM  Simplified version of available mode settings
Devices Management  Remote management of DERs  Linksmart Interface

12. Deliverable Status Status of Deliverable
Work on the deliverable in progress Reporting the main scenarios and technical specs of the tool(M24)
Main scenarios addressed in the project for demo purposes visual and thermal aspects to be examined
Dummy data generated for demo purposes?
Contributions expected per partners
User Profiling  TUK, ALMENDE testing of integration
ALMENDE,CNET, ETC Ambient UI for FM
CERTH, ENG UIs for occupants and spaces
Planning for intermediate – peer review version
Scenarios to be addressed for review process (Visual and thermal preference in single occupancy room and grouped analysis)
Demo Interfaces with minimum functionality (as reported before views & respective partners)

13. Planning for next efforts
Planning of efforts for remaining period towards
Task completion/deliverables submitted on M24 (September)
Report on the main specs of the tool
Circulate the deliverable by mid-September
Addressing at least the scenarios mentioned before
What related to User Interfaces
Development of the UIs even in a prototype version
Dummy data available if need for an early deployment.