Smart Energy Efﬁcient Buildings

A Living Lab Approach

Marco Jahn

, Edoardo Patti

and Andrea Acquaviva

Fraunhofer Institute for Applied Information Technology, Schloss Birlinghoven, Sankt Augustin, Germany

Department of Control and Computer Science Engineering, Politecnico di Torino, Torino, Italy

Keywords:

Smart Buildings, Energy Efﬁciency, Middleware, Living Labs, User-centered Development.

Abstract:

In this paper we provide an overview of current research trends, challenges and issues in the domain of smart

energy efﬁcient buildings. Based on current research and literature we discuss topics like technology integra-

tion, semantic interoperability, automation, and the importance of considering user needs. Furthermore, we

introduce a living lab approach, which allows us to conduct research on these topics in a real smart building

environment. This living lab is a system for enabling smart energy efﬁcient building applications based on a

middleware approach. We describe the software design and the real-world deployment of this system in ten

rooms of a university and eight rooms of an ofﬁce building.

1 INTRODUCTION

Smart energy efﬁcient buildings are considered a sub-

stantial part of future smart cities. Oftentimes, when

talking about smart buildings, what is meant are

buildings which have a building management system

(BMS) installed. Such a BMS typically controls the

lighting and heating, ventilation and air conditioning

(HVAC) of larger buildings based on certain control

strategies. Furthermore, BMSs are usually propri-

etary, closed systems provided as whole-in-one solu-

tions by one vendor and normally are installed when

a building is designed from scratch.

In the age of Ubiquitous Computing (UbiComp),

new technologies are available at an affordable price

and can help making buildings smarter than they are

now. For example, wireless sensor networks (WSNs)

can contribute to a better understanding of a build-

ing’s behavior by monitoring environmental values.

Smart meters (and even sub-meters on device level)

can provide additional insights into a building’s en-

ergy consumption. Even wireless building manage-

ment systems (W-BMS) are available to retroﬁt exist-

ing buildings. Last but not least, in the vision of the

smart grid, buildings are supposed to perform a trans-

formation from energy consumers to prosumers, i.e.

producing and exchanging energy with other entities

of the smart grid.

From an ICT research perspective we argue that

buildings are gradually becoming places of Ambi-

ent Intelligence (AmI) where technology works in

the background and becomes invisible to the occu-

pants (Sadri, 2011). For example, adaptive control

strategies are being researched to improve the predic-

tion of occupant behavior for more accurate heating

and lighting control. The exploitation of an ever-

increasing amount of information that is becoming

available in smart buildings can surely contribute to

more efﬁcient automation and control. But, at the

same time, an increasing amount of data is captured

about occupant behavior and it is important to ﬁnd

the right balance between technology, data collec-

tion, automation and the occupants’ needs and privacy

concerns. A responsible development towards smart

energy efﬁcient buildings and cities has to consider

both, the technology- as well as the human dimension

(cf. (Nam and Pardo, 2011) who conceptualize smart

cities by identifying the different dimensions).

From the technology perspective, a major issue

is to achieve interoperability between systems and

technologies inside the smart buildings themselves.

This would be the basis for extensible smart build-

ings ready for future interaction with smart cities and

the smart grid. The second major issue that needs

more attention is the role of the end users in such

smart buildings (i.e. occupants, building managers,

etc.). Even with current BMSs there often is a lack

of acceptance from occupants due to a lack of trans-

parency of system behavior. If buildings are becom-

ing even smarter it is inevitable to consider the users

171

Jahn M., Patti E. and Acquaviva A..

Smart Energy Efﬁcient Buildings - A Living Lab Approach.

DOI: 10.5220/0004409001710176

In Proceedings of the 2nd International Conference on Smart Grids and Green IT Systems (SMARTGREENS-2013), pages 171-176

ISBN: 978-989-8565-55-6

 2013 SCITEPRESS (Science and Technology Publications, Lda.)

in the process of moving towards smart energy efﬁ-

cient buildings.

In the ﬁrst part of this paper we give an overview

of relevant research areas and important issues to be

considered when talking about future smart buildings.

The second part introduces our living lab approach

to gain insights into both, technical and user-related

challenges, opportunities, and problems. We present

our concept of a middleware-based smart building liv-

ing lab which we deploy in 18 rooms. Ten are lo-

cated in buildings of a university campus in Italy and

eight are in an ofﬁce building of a research institute

in Germany. The living lab deployment demonstrates

the integrated deployment of different subsystems. It

is designed to be an open, extensible system, that

will evolve into an integrated building energy man-

agement system, following an iterative, user-centered

living lab process. Thus, the ﬁndings of this research

cover two dimensions: The technology dimension in

the sense of the integrated BMS and the human di-

mension by following an explorative living lab ap-

proach. We would like to note that the term smart

building in the scope of this paper is limited to com-

mercial, ofﬁce, or (semi-)public buildings and does

not include smart homes.

2 SMART BUILDINGS

In the following we characterize some of the main

challenges we see for smart buildings. We mainly

consider two areas, which are of course heavily in-

tertwined: The technology dimension, mainly deal-

ing with integration and interoperability and the hu-

man dimension, considering the end users. As said

before, from the upcoming trend towards integrated

smart buildings arise a lot of challenges and concerns

that need to be considered when developing ICT sys-

tems for such buildings. Based on existing literature

and our own research experiences we discuss the dif-

ferent issues that need to be considered.

Technology Integration. Dealing with heteroge-

neous devices, technologies, and systems is a typical

issue for AmI systems and a problem that also exists

in the smart energy efﬁcient buildings domain. E.g.

BMSs from different vendors use different technolo-

gies and protocols; a lot of existing hardware is al-

ready installed and working; new hardware may be

installed with new communication protocols such as

wireless BMS like EnOcean

; experimental technol-

http://www.enocean.com

ogy like Arduino

allowing to develop custom sensor

networks may also be considered. To address these

problems of heterogeneity, systems need to be open

and extensible to new kinds of technologies. In the

domain of building management an approach to over-

come these problems is the OPC uniﬁed architecture

speciﬁcation

. Another approach from the research

domains of UbiComp and AmI is middleware. The

middleware concept is more general and not restricted

to building management, thus providing greater ﬂex-

ibility with regards to integration of other technolo-

gies (e.g. smart phones, WSNs) and extensibility. Of

course greater ﬂexibility does not come for free but

usually with greater complexity. Examples of rele-

vant middleware solutions are (Kirkham et al., 2008),

(Capone et al., 2009), and (Eisenhauer et al., 2009).

Monitoring, Control, and Automation. To in-

crease energy efﬁciency in buildings a basic require-

ment is to have access to environmental data, oth-

erwise it would be impossible to evaluate any kinds

of energy savings. Therefore, a monitoring infras-

tructure is necessary and of course if not already in-

stalled it should be cheap and easy to deploy. With

the rise of WSNs and smart metering, ﬁne-grained

monitoring of almost every kind of environmental in-

formation is possible. Of course, control strategies

for lighting and HVAC would beneﬁt from additional

data sources but it is not trivial to integrate new de-

vices into existing systems. It would be a major ad-

vantage if new data sources could be exploited seam-

lessly by an existing monitoring and control system.

This would give us the opportunity to develop really

ﬂexible and advanced control strategies. For example,

a simple WSN might signiﬁcantly increase occupancy

detection algorithms. Again, this example stresses the

need for open, integrated systems which allow for ex-

tensibility both, software- and hardware-wise.

Semantic Interoperability. While technology inte-

gration as described above refers to the term syntactic

interoperability, semantic interoperability resides on

a higher layer. Semantic interoperability should allow

developers to use different technologies transparently.

A semantic layer should abstract from any concrete

technology. The issue of semantic abstraction is often

tried to be solved by ontologies, which should help to

ﬁnd common concepts for different implementations.

There are several approaches that try to deﬁne seman-

tic knowledge for smart buildings (Wicaksono et al.,

2010), (Dibowski and Kabitzsch, 2011).

http://www.arduino.cc/

http://www.opcfoundation.org

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End Users. End users are an important, yet often

neglected factor contributing to the success of smart

buildings as they are heavily affected by any kind of

automated system. In the domain of building automa-

tion, standards and key ﬁgures to measure occupant

comfort exist (ANSI/ASHRAE, 2004). However, oc-

cupants are often unhappy with automated systems

for many reasons. Usually occupants don’t know why

an automated system behaves like it does. If people

need to start waving at sensors to make the light or

heating work, the system simply does not fulﬁll its

basic requirements of automation. Besides trying to

increase the accuracy of presence detection, another

option would be to give the people back some con-

trol over their environment. Studies have indicated

that occupants are happy with personal control over

lighting (Galasiu and Newsham, 2009) and current

research efforts of personal building controls for oc-

cupants indicate that this can be an opportunity (Kri-

oukov and Culler, 2012), (Krioukov et al., 2011). It is

still an open issue how to increase the occupants’ ac-

ceptance of automated systems and further research

in this direction is highly encouraged. User control

and/or transparency of system decisions might be pos-

sible ways to go. Besides the issue of acceptance, we

also believe that the opposite communication channel

needs further investigation: If occupants could pro-

vide feedback (to the building manager or the system

directly) about the system, its behavior, or their own

comfort, this might improve both, the system itself

and its acceptance.

Furthermore, researchers from the ﬁeld of Human

Computer Interaction and Psychology deal with ques-

tions of motivating energy efﬁcient behavior. They in-

vestigate different kinds of interventions ranging from

feedback on energy consumption (Darby, 2006) to en-

ergy saving competitions (e.g. (Brewer et al., 2011)).

(Froehlich et al., 2010) provides a good overview

of both research areas and analyses what they could

learn from each other to effectively foster energy efﬁ-

cient behavior. Although, most of the research in that

area tackles the domestic domain, we think it is worth

identifying promising approaches and transfer them

to the domain of ofﬁce and (semi-)public buildings.

Last but not least, occupants are not the only

stakeholders in a smart building and one major player

which should not be forgotten is the building man-

ager. When designing energy management systems,

building and/or energy managers and facility staff

need to be involved in the process because they are

the main expert users. Efforts to understand the needs

of building managers have already been undertaken

by (Lehrer and Vasudev, 2010) and should be contin-

ued, especially in real deployments and ﬁeld trials.

Security and Privacy. Another important issue

when talking about future smart buildings, integra-

tion, data collection, feedback, etc. is privacy. We

believe that the best smart building system will fail if

it is not able to deal with occupants’ privacy concerns.

Therefore, it is of the utmost importance to include all

relevant stakeholders right from the start.

3 LIVING LAB APPROACH

To gain deeper knowledge and develop solutions to

the challenges discussed above, we propose a living

lab approach to provide a real-world experimental en-

vironment. We hope to gain experiences from deploy-

ments and a user-centered development process that

go far beyond what is possible in a controlled lab en-

vironment or simulations. Our aim is to create a ﬂex-

ible software infrastructure for smart energy efﬁcient

buildings, allowing easy integration of different tech-

nologies and rapid development of applications, so we

can quickly react to user needs. To put it in a nutshell,

we develop a living lab to gain knowledge about smart

building technologies, deployment and user interac-

tion. This living lab relies on a middleware-based

software infrastructure and can be seen as a smart en-

ergy efﬁcient building system in the making. In the

following we describe the test sites, system design

and implementation, and the developed and planned

end user applications.

3.1 Test Sites

We currently have two ﬁeld deployments in a research

campus in Germany and a university campus in Italy.

The deployment in Germany is located in one ofﬁce

building and comprises 8 rooms on the same ﬂoor:

four single-person ofﬁces, two two-person ofﬁces and

two student labs with eight and four work places. The

two-person ofﬁces and two of the single-person of-

ﬁces are equipped with EnOcean technology for light-

ing and heating control and for monitoring of pres-

ence, temperature, window states, and energy con-

sumption of appliances and lights. Two of the single-

person ofﬁces are equipped with monitoring devices

only. In the student labs we have deployed an exper-

imental setup of Arduino sensors for measuring pres-

ence and window states and Plugwise

smart plugs for

measuring energy consumption of appliances.

The Italy deployment is spread over three differ-

ent buildings, each with different requirements for

integrated monitoring and control systems. This de-

ployment comprises 10 rooms in total with each two

http://www.plugwise.com

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rooms forming a test and reference room. A test

room is equipped with hardware to control lighting

and HVAC while a reference room only hosts moni-

toring devices. Each pair of test and reference rooms

are situated next to each other and share similar char-

acteristics with regards to size, number of maximum

occupants, orientation in the building, etc. This setup

has been chosen to achieve a high degree of com-

parability. Four rooms are located in a castle which

hosts several ofﬁces and secretariats. This castle was

built in the 17th century and thus has very strict re-

quirements regarding any kinds of refurbishments.

The ofﬁces and secretaries are two-person rooms.

Deployment-wise the castle has special requirements

with regards to BMS installation so it is not possible

to install anything wired in the walls because it is a

historic building. Consequently, a wireless monitor-

ing and control system based on EnOcean and Plug-

wise technologies has been installed. The remaining

6 rooms are located in two buildings of the main cam-

pus of the university. These rooms are two two-person

ofﬁces, two single-person ofﬁces and two student labs

with 20 workplaces. The buildings in that part of the

campus are partially equipped with a Siemens De-

sigo BMS. Furthermore, TelosB WSNs and Plugwise

smart plugs have been deployed in these rooms to

gather additional data about environmental conditions

and power consumption of devices.

3.2 Implementation

The implementation of the smart building living lab

is based on a middleware approach. We use mid-

dleware to integrate different technologies and make

use of an abstraction layer to allow uniﬁed access

to these technologies. To not reinvent the wheel

we employ the LinkSmart middleware

, which is an

open source middleware for developing AmI appli-

cations on top of heterogeneous technologies (Eisen-

hauer et al., 2009). It is available under LGPL license

and has been applied among others in the areas of en-

ergy efﬁcient smart homes (Jahn et al., 2010) and of-

ﬁce environments (Jahn et al., 2011).

3.2.1 LinkSmart Middleware

LinkSmart implements a service-oriented architecture

providing to software developers a set of components

(called managers) they can select from, depending on

their speciﬁc requirements. Each manager encapsu-

lates a set of operations and data that realize a well-

deﬁned functionality. Some of these managers are es-

sential (e.g. Network Manager) while others provide

http://sourceforge.net/projects/linksmart/

optional functionality (e.g. Event Manager). Each

manager has a clearly deﬁned role, offering a set of

services to be used by other managers or application

level components. The main features of the LinkS-

mart middleware with respect to the smart building

living lab are as follows:

Network Management. A LinkSmart Network is

formed by distributed Network Managers that take

care of the communication among devices and man-

agers. Every service can register itself at a Network

Manager and thus take advantage of communicating

inside the LinkSmart network. The Network Manager

enables network communication by creating an over-

lay P2P network that implements SOAP Tunneling as

transport mechanism for Web Service calls (Milagro

et al., 2008). This concept allows direct communica-

tion among all devices inside a LinkSmart network,

no matter if they appear behind a ﬁrewall or NAT

(Network Address Translator). The LinkSmart ad-

dressing scheme allows devices to transparently pub-

lish and use services anytime anywhere regardless of

network boundaries or ﬁxed service endpoints.

Event Management. For smart building applica-

tions it is essential to be modular, extensible and

provide low coupling of components, as set-ups can

change when devices are removed or new devices

are added to the environment. The Event Man-

ager addresses these requirements, implementing a

publish/subscribe mechanism for LinkSmart services.

Thus, we are able to develop loosely coupled applica-

tions, which are ﬂexible enough to face the require-

ments of dynamic AmI environments. The Event

Manager handles all subscriptions and is responsible

for publishing events via a Network Manager, com-

pliant to the LinkSmart communication model.

Proxies. A proxy is a software component that en-

ables basic syntactic interoperability between differ-

ent technologies; it is responsible for integrating a

certain kind of technology, device, or subsystem into a

LinkSmart network. A proxy acts as a bridge between

the LinkSmart network and the underlying technol-

ogy. It translates whatever kind of language the low-

level technology speaks into LinkSmart Web Services

so the low-level technology can be used transparently

by any other LinkSmart component. For example, our

EnOcean proxy internally can handle EnOcean tele-

grams and offers a Web Service interface to be used

by components on the middleware layer. This concept

allows us to use each low-level technology transpar-

ently inside the LinkSmart network.

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Figure 1: 3-Layered Software Architecture.

3.2.2 Smart Building Living Lab

The software architecture of our smart building living

lab is based on three layers (cf. Figure 1), adhering to

the principles of the LinkSmart middleware: On the

lowest level the proxy layer is responsible for syn-

tactic interoperability between the different low-level

technologies. We currently have proxies for EnO-

cean, Arduino WSN, TelosB WSN, Plugwise smart

plugs, and a proxy based on OPC for accessing the

Siemens Desigo BMS. On top of this, the middle-

ware layer provides components speciﬁcally designed

for the energy efﬁcient smart building applications,

which should support the management of reoccur-

ring tasks. We currently have three main components

on this layer: The Ontology- and Context Manager,

which manage semantic knowledge about the smart

buildings. This includes information about sensors

and other devices, buildings, and rooms. The Rule

Engine, which is the basis for developing custom con-

trol strategies. It allows us not only to implement con-

trol strategies for lighting and HVAC accross the dif-

ferent technologies but also to quickly react to user

needs or other lessons learned from the deployments.

For example, if there is a gap between simulation

and real behavior of a control strategy, we are able

to quickly tweak parameters or to even exploit infor-

mation from additional sensors. The topmost layer is

the application layer. On this layer reside all kinds

of applications that make use of the integrated system

and information that is available. For example, the

aforementioned control strategies reside on this layer,

as well as end-user applications for feedback and con-

trol, which will be described in the next chapter.

3.3 End User Applications

As one of our goals is to strengthen the role of end

users in smart buildings we are highly interested in

the needs and wishes of the different end users. We

mainly consider two categories of users in our build-

ings: expert users (i.e. the building managers) and oc-

cupants (i.e. students and employees). Based on ex-

isting studies and semi-structured interviews we con-

ducted with users (cf. (Jahn et al., 2011)) we imple-

ment a ﬁrst set of applications. As a ﬁrst approach

we implement a web portal that allows building man-

agers to monitor environmental values such as tem-

perature, humidity, or power consumption. As re-

ported in (Lehrer and Vasudev, 2010), the analysis of

such data is still not an easy task. The web portal

allows expert users to browse data by different cate-

gories and view information per room or device and

in a certain period of time. Figure 2 is an excerpt from

Figure 2: Web Portal Screenshot.

the web portal showing the recent trends for environ-

mental values in one ofﬁce. Regarding occupants we

aim at investigating new concepts of user-building in-

teraction. First, of course we want to increase the

acceptance of smart buildings by providing feedback

and enabling transparency. One goal is to ﬁnd out the

right types of information to show to the occupants or

the degree of transparency that is feasible. The second

concept we want to investigate is if it makes sense to

let occupants provide feedback to the system and if

it is possible to give them a certain amount of con-

trol over the system. Previous research indicates that

such concepts are fruitful and well recognized by oc-

cupants ((Krioukov et al., 2011) and (Krioukov and

Culler, 2012)).

4 CONCLUSIONS

We provided an overview of current research efforts in

the domain of smart energy efﬁcient buildings and de-

scribed our living lab approach to foster user-centered

research in such buildings. One goal of this paper is to

raise awareness for important issues in smart building

research. The main beneﬁt of our living lab approach

is that we are able to tackle technical issues and user-

related questions at the same time. By following this

SmartEnergyEfficientBuildings-ALivingLabApproach

175

approach our vision is to develop smart buildings that

are both, efﬁcient in the way they work and well ac-

cepted by end users. The current state of the system is

this: All hard- and software components for integra-

tion, monitoring, and control has been deployed. Now

we are in the phase of validating sensor measurements

and adapting the control strategies to the peculiarities

of deployed sensors. Once the basic monitoring and

control (HVAC and lighting) is running smoothly, we

will start the deployment of the ﬁrst end user applica-

tions and start the next iteration of the user-centered

development process.

ACKNOWLEDGEMENTS

The work presented in this paper was supported by

the European research project SEEMPubS (Project

no. 260139).

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