1. WP2 INERTIA Distributed Multi-Agent Based Framework
Task 2.3 – Occupancy Profiling & Activity Flow Modeling
CERTH/ITI

2. T2.3 Overview Task 2.3 “Occupancy Profiling & Activity Flow Modeling”
Duration: 10 Months (M3-M12)
Deliverable: contributes to D2.2 “Tertiary Local Control Hubs consumer flow modelling & profiling”
(Report, Restricted, M12 – Sep. 2014)
Leader: CERTH/ITI
CERTH/ITI
ENG
TECHALIA
CNet
INDESIT 7
ALMENDE
TUK
HYPERTECH
PPC
ENELSI 2 4

3. T2.3 Objectives
Thorough investigation of existing occupancy modeling methods and models (both from literature and other European projects)
Investigate the flow data related to human presence and movements in tertiary buildings
Define robust and credible tertiary building prosumer profiles, that will be later embodied into the holistic flexibility models of T2.5, through seamless and privacy-preserving analysis of user preferences, needs and habits
Provide the necessary implementation guidelines for the design and development of the real-time occupancy detection system in WP3 (T3.4)

4. Aim of the Occupancy Modeling Framework
The Occupancy Flow Modeling and Prediction Framework aims to deliver:
enriched individual and group-based flows models
adaptable to the real-time human activity detection, utilizing privacy-conserving sensors and techniques
analyze in real time and predicting human occupancy flows
take full advantage on the dynamic behavior of the buildings

5. Overview of previous relevant work / SotA
Literature (as described in the DoW):
Bourgeois et al, 2004: framework modeling whole-building human activity data taking into account the impact of short term occupancy variations and other environmental factors
Hutchins et al, 2007: probabilistic model that estimates the number of humans in a building using networks of occupancy sensors
Barbato et al, 2009: smart home, wireless sensor network used to monitor physical parameters (like light and temperature) and presence of users at home and in each of its rooms

6. Overview of previous relevant work / SotA
Projects (as described in the DoW):
AIM: household appliance management
accurate modeling of operational modes of appliances
wireless sensor network to predict user behavior
Deficiencies: it does not target dynamic demand side management
HESMOS: integrate advance energy-efficiency tools into design & facility management process. Develop new visualization tools for building energy-related performance
PEBBLE: real-time optimization and control ICT methodology in real-life buildings
intelligent shaping of demand to perform generation-consumption matching
occupant actions and activities directly influence the thermal behavior of the building and decision making
Deficiencies of HESMOS & PEBBLE: do not analyze overall occupancy flows, semantics and complexity of day-to-day human activity and movement

7. Overview of previous relevant work / SotA
Projects (as described in the DoW):
S4EeB: audio-based building energy management
monitoring and processing of sounds and noises to determine occupancy
audio and occupancy sensors in adaptable and scalable network architecture
Deficiencies: it does not exploit evidences of scheduled events or other occupancy flows related to the dynamic behavior of the building
Adapt4EE: provisional creation of occupancy models related to business processes in buildings. Aims to:
analyze human presence and movement in various enterprise buildings
exploit evidences of scheduled events or other occupancy flows that may be lead to the delivery of energy-efficient modelling of the dynamic behaviour of the building
deliver a set of occupancy models for simulation purposes, assisting Designer & Engineers in the early phases of energy-efficient building design
Deficiencies: not targeting the dynamic demand side management occupancy flow modelling. Not investigating thoroughly tertiary building environments.

8. Occupancy Detection & Modeling developed by CERTH
Occupancy Detection and Modeling
People counting & localisation
Analyze human activity and dynamically extract detailed occupancy models
Comprise patterns of human presence and movement based on information from two different combined depth image sensors using human detection algorithm
Occupancy models created based on spatio-temporal analysis
Uses a Virtual Camera for human detection based on the Foreground estimation
Several occupancy presence parameters can be extracted:
Average Occupancy (mean number of user for the total period)
Min and Max Occupancy (in terms of number of concurrent users in a building space/zone)
Occupancy Average Values per Zone (within the room)

9. Occupancy Detection & Modeling developed by CERTH
Human Detection Algorithm
A virtual camera is introduced, “placed” on top of the monitored area
The actual 2 different depth image cameras can be placed anywhere in the area
Utilizing 3D information - the virtual camera provides a top-view of the area
All processing is performed on depth images
Avoid noise due to lightning changes
3D information can be extracted
Color images are used only for visualization purposes (avoid privacy/ethical issues)
Background Estimation is done before detection
Rotation Estimation - calculated using 3 floor point

10. Occupancy Detection & Modeling developed by CERTH
Color images only for visualization – not used for detection
Current Status – Occupancy Tracking Output
Real-time foreground detection based on depth images
labeled positions of detected occupants in monitored area projected on 3D virtual camera
Tracked occupancy flows on 3D virtual camera

11. INERTIA Occupancy Flow Modeling & Prediction Framework
Part of the multi-agent-based system
To allow optimal, reliable and effective coordination of the local demand side management activities

12. INERTIA Occupancy Flow Modeling & Prediction Framework
Novel multi-sensorial framework for analyzing occupancy flows
Analyze in real-time the sensors’ data, retrieve the most appropriate occupancy profile from Open Reference models and adapt it
Provide occupancy flow prediction
Allow optimal, reliable and effective coordination of the local demand

13. T2.3 Next efforts
Extensive SotA analysis on Occupancy Profiling & Activity Flow Modeling, focusing on:
real-time occupancy detection and modeling methods
multi-sensor systems used in commercial and tertiary buildings
energy-footprinting in commercial buildings
Recommendations for the development of the occupancy profiling and models within INERTIA
Occupancy Profiling & Activity Flow Modeling Specifications
Selection of occupancy sensors and their specifications for various building zones and types that will be used in the project and during the pilot installation at CERTH premises
Prepare draft version of deliverable D2.2 “Tertiary Local Control Hubs consumer flow modelling & profiling” by end of M6