Personal e-Comfort Modelling and Management based on
Multi-Agent System and Internet of Things Network
Benjamin Gateau
1
and Jarogniew Rykowski
2
1
SSI, Public Research Center Henri Tudor, Luxembourg, G-D. of Luxembourg
2
Department of Information Technology, Poznan University of Economics, Poznan, Poland
Keywords: Internet of Things, Multi-Agent Systems, Comfort Management, Ubiquitous Computing.
Abstract: In this paper a new approach to complex comfort management is presented, aiming in automatic treatment
of different comfort parameters by means of Internet-of-Things devices and multi-agent system. The paper
presents a new model of e-comfort, based on common treatment of all the parameters as identified across
the Maslows hierarchy of needs. Next, a new architecture of e-comfort management is discussed, based on
two layers: low-level layer of IoT devices, representing at-the-place possibilities of the system, and upper
layer of software agents, formulating and negotiating the needs and expectations of human users.
1 INTRODUCTION
Comfort is often provided in homes or places of
work by automation systems connecting actuators
(shutters, lights, heating, etc.) and sensors and
linking them together through scenarios and/or rules.
Typical scenarios define rules triggering the
execution of one or several actuators according to an
event. The event can be based on time (when it is
6:30 AM, execute the “wake-up” scenario), can be a
result of a direct interaction with the user, e.g., while
pushing a button (physical on the wall or virtual on
an interface) or the value reached by a sensor (when
the inside temperature is more than 25°C, switch on
the air conditioner).
The above notion of comfort is quite
straightforward and not deep enough. Comfort is not
only a set or rules or predefined scenarios, comfort
is equilibrium between the needs of the user and
his/her environment. Users want to be comfortable
without taking a lot of time to perfectly adjust
settings of their environment. The home automation
system has to anticipate the needs of the users in
order to reach a comfortable environment. The idea
behind is to automatically provide comfort at certain
level as Weiser’s good servant rules (Weiser 1991)
based on ubiquitous computing. This kind of e-
comfort and fully manageable conditions at-a-place
would be done via smart IoT devices able to
coordinate themselves to bring intelligent
assistantship and switch-less or hands-free home.
The goal of the paper is to propose a new way of
complex comfort management, having a set of
devices at one end, and human needs and
expectations at the other end. The idea is to manage
the comfort automatically based on the fuzzy-
declared parameters and available at-the-place
devices, to minimize manual activities of a user. The
paper is the first step towards such automatization,
aiming in the presentation of the way of comfort
modelling and controlling.
The remainder of the text is organized as
follows. In Section 2 we discuss basic comfort
elements that should be taken into consideration.
Then, Section 3 describes how these elements are
used to model the comfort in a complex and uniform
way. Section 4 briefly describes system architecture,
and Section 5 provides some conclusions and
directions for the future work.
2 COMFORT ELEMENTS
Comfort is surely not a simple and costless goal to
achieve. On the contrary, we see the notion of
comfort as extremely complex and embroiled. Thus,
we devote this section to a description and
discussion on the components of the whole term, in
division to physical conditions of the comfort,
psychological aspects, economics aspects, and
83
Gateau B. and Rykowski J..
Personal e-Comfort Modelling and Management based on Multi-Agent System and Internet of Things Network.
DOI: 10.5220/0005229900830089
In Proceedings of the 5th International Conference on Pervasive and Embedded Computing and Communication Systems (PECCS-2015), pages 83-89
ISBN: 978-989-758-084-0
Copyright
c
2015 SCITEPRESS (Science and Technology Publications, Lda.)
safety/security conditions, these are enumerated and
briefly discussed below.
Due to the well-known theory of self-motivation,
people tend to live in so called comfort zone our
everyday home&work environment. Comfort zone
determines our way of live, our friends and any
other social contacts, our customs, beliefs,
imagination, goals etc. Within our comfort zone, we
feel safe and secured, and we tend to keep this
situation stable. Sometimes we are forced to go out
from the comfort zone, to the adaptation zone
there, we do not like the situation and we tend to
change it, keeping closer to the missing comfort.
This is a positive trend, as we are active and make
several efforts on inducing the changes to us, or to
the environment. However, sometimes the change is
so critical we land in the panic zone there, we are
not able to react to the changes and go back to the
comfort zone, and we need some help and
assistance.
Anyway, the overall goal of keeping ourselves in
the comfort zone is achieved by:
understanding of what “comfort” means to every
one of us, and
addressing some external assistance to help us to
go out from the panic and adaptation zones.
As mentioned before, we consider the comfort as
a balance between the user and his environment. We
are constantly evolving in changing contexts. By
context we mean “any information that can be used
to characterize the situation of an entity”. Here, the
entity is the user and the information that
characterizes the situation is the one that can be
compared to the user’s needs to be comfortable.
Thus, it is crucial to identify our needs and
expectations related with comfort, in as many its
aspects and possible, and explain these to the
assistants humans and recently intelligent
devices/places in order to improve the unwanted
situation. The first step towards such identification is
to classify all possible sub-notions of comfort, to be
personalized in the second step towards optimal
adaptation to individuals, situations, places etc. To
this goal, in this section we discuss several aspects
of the comfort, starting from the physical conditions
(natural and close environment), and finishing on
some psychological and social aspects.
According to well-known Maslow’s theory on
the hierarchy of human needs, our behaviour (and
indirectly the comfort) is determined by a level of
fulfilling the needs. The needs create a hierarchy, to
be fulfilled in certain order. A need provokes certain
actions to fulfil it. Maslow's hierarchy of needs is
often portrayed in the shape of a pyramid with the
largest, most fundamental levels of needs at the
bottom and the need for self-actualization at the top
(Fig. 1) (Maslow 2014). Starting from the bottom of
the pyramid, physical conditions of the comfort are
related with our natural environment and its
measurable parameters temperature, air flow,
humidity, lightness, etc. These conditions are
directly perceptible by the senses: sight, hearing,
touch, including sense of temperature, smell, taste,
balance and more. Thus, a natural trend is to link the
comfort aspects to the senses, as depicted below.
Figure 1: Maslow’s hierarchy of needs.
2.1 Thermal Comfort
Thermal control is mainly related with the sensitivity
of our skin towards the detection of external
temperature. Humans may exist and be functional in
a wide range of the temperature starting from
-100°C (in clothes, or for a very short period,
however) to +100°C (for a very short period, or well
protected by special fire suit). The thermal comfort
zone is very special for particular humans, however,
most of us see an air temperature around 22°C as
optimal. Thermal control is strongly related with air
flow and drafts, temperature gradient, clothes, etc.
This topic was addressed many times by the
researches working in different domains, perhaps the
work (PhD thesis and further books) of Ole Fanger
is the most completed in that area (Fanger 1970).
Maintaining thermal comfort for occupants of
buildings or other enclosures is one of the important
goals of HVAC (heating, ventilation, and air
conditioning) systems c.f. the description for air-
conditioning comfort below.
2.2 Ventilation and Air-Conditioning
Comfort
Addressed to closed environments such as buildings,
ventilating (the V in HVAC acronym) is the process
of "changing" or replacing air in any space to
provide high indoor air quality (i.e. to control
temperature, replenish oxygen, or remove moisture,
odours, smoke, heat, dust, airborne bacteria, and
carbon dioxide). Ventilation is used to remove
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unpleasant smells and excessive moisture, introduce
outside air, to keep interior building air circulating,
and to prevent stagnation of the interior air.
Ventilation includes both the exchange of air to the
outside as well as circulation of air within the
building. It is one of the most important factors for
maintaining acceptable indoor air quality in
buildings. Methods for ventilating a building may be
divided into mechanical/forced and natural types
(Ventilation 2014).
Complementary to the ventilation, air
conditioning is the process of altering the properties
of air (primarily temperature and humidity) to more
favourable conditions, typically with the aim of
distributing the conditioned air to an occupied space
to improve comfort. In the most general sense, air
conditioning can refer to any form of technology,
heating, cooling, de-humidification, humidification,
cleaning, ventilation, or air movement that modifies
the condition of air (McDowall, 2006).
2.3 Humidity/Hygrometric Comfort
Humidity is the amount of water vapour in the air.
Humans are sensitive to humid air because the
human body uses evaporative cooling as the primary
mechanism to regulate temperature. Under humid
conditions, the rate at which perspiration evaporates
on the skin is lower than it would be under arid
conditions. Because humans perceive the rate of heat
transfer from the body rather than temperature itself,
we feel warmer when the relative humidity is high
than when it is low. Some people experience
difficulty breathing in high humidity environments.
Some cases may possibly be related to respiratory
conditions such as asthma, while others may be the
product of anxiety. Sufferers will often
hyperventilate in response, causing sensations of
numbness, faintness, and loss of concentration,
among others (Humidity 2014).
Above-mentioned air conditioning reduces
discomfort not only by reducing temperature, but
also by reducing humidity. In winter, heating cold
outdoor air can decrease relative humidity levels
indoor to below 30%, leading to discomfort such as
dry skin and excessive thirst.
2.4 Gases and Smells/Odours
Smell sense is responsible for the detection of
certain chemical compounds dissolved in the air
not only gases, but also liquids and solids.
Historically, this sense is the most archaic one – first
living organisms on Earth were equipment with such
detectors for communication and self-security.
Human smell sense is not as efficient as the one for
some animals, anyway, we are able to detect several
compounds, some of them are neutral for our health,
some of them (un)pleasant, and some dangerous,
especially at higher concentration. Unfortunately,
humans are not able to detect some very dangerous
compounds such as carbon oxide and dioxide. Thus,
broadening smell sense to detect all the unwanted
and dangerous components in the air is a very
desired part of the comfort zone.
Most heating, ventilation and air conditioning
systems (HVAC) re-circulate a significant portion of
the indoor air to maintain comfort and reduce energy
costs associated with heating or cooling outside air.
When occupants and building operators sense air
coming out of an air supply duct, it’s virtually
impossible to judge how much of this air is simply
re-circulated air and how much is outside air.
Current technology allows easy and relatively
inexpensive measurement of carbon dioxide (CO
2
)
as an indicator to help ensure ventilation systems
(for high density occupancy zones) are delivering
the recommended minimum quantities of outside air
to the building’s occupants (Prill 2000). CO
2
is a
natural product of human respiration whose rate can
be predicted based on an occupant’s age and activity
level. Beginning as early as 1916 (Mechanical
Engineer’s Handbook by McGraw-Hill) and found
in the New York City Building Code of 1929, CO
2
of 800 to 1,000 ppm and 1,000 ppm respectively
were recommended. However, the key point is that
CO
2
levels are good predictors or surrogates for
human emitted bioeffluents (i.e., odours) that are
considered undesirable for the overall human
comfort inside conditioned spaces. Thus CO
2
is a
surrogate for levels of other bioeffluents that cause
odours that are likely to be viewed as unacceptable
by others in the space, not because of their presence
as a direct health hazard (Petty 2014).
2.5 Visual and Light Comfort
Light, mainly detected by the sight sense, is crucial
for human feeling of the comfort. Humans used to
act in the day-night cycle, with sunlight marking the
period of the activity, and darkness indicating the
period of the rest. Both are needed for our health,
and both may vary and depend on very individual
preferences, including the mood, company, etc.
Global tendency is to achieve the level and quality
of the light as close to natural (sun, outdoor) one as
it is possible (thermal temperature and spectrum,
distributed sources and background light, lightness,
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etc.). Historically, lights and lightness control is the
fundamental issue for any modern (not to say
“intelligent”) building, starting from simply
dimmers, via light scenes, to nowadays LED-based
“walls of light” with distributed sources of the light,
fully controlled with respect to spectrum, intensity,
direction of the light beam, etc. Thus, a lot of
research has been already devoted to this aspect,
resulting in plenty of systems, norms, regulations,
standards, etc. Anyway, optimum lighting is crucial
for good sense of the comfort.
2.6 Acoustical Comfort
Noise and sound background is an essential element
of our life. It is hard to imagine we cannot hear
anything at the moment, thus for most of people
such silence is not a comfortable situation. On the
contrary, too much noise is also not needed, as it is
usually very disturbing.
Source of noise are internal of the
home/building, inside the same room or from others
rooms or could come from outside of the
home/building. It is influenced by first of all the
insulation used for external wall and the windows
from one side and for the internal walls and door
from other side. The user can act on the environment
to reduce the noise as, for instance, closing doors
and windows.
For those who do not like too much noise – there
are basically three ways to avoid it. The first one is
passive: walk away of the noise emitter. Surely, this
simple approach is not efficient in many cases, such
as a small room or a crowded place. Second
approach is to do some simple things to reduce the
noise, such as closing the windows mentioned
above. And third, we may apply some advanced
technical solutions, for example active headphones.
Such a device generates sound of the same intensity
but in opposite phase, thus somehow enduring
source of noise. It is questionable if such generation
is healthy or not, but in some cases it cannot be
avoided (such as ear protectors for ground handling
staff at an airport, construction workers, etc.).
By contrast, user could like to have a soft
background noise as classical or relaxing music for a
studious and focused environment or loud music. It
depends on the user’s needs and preferences but also
on the type of activity he is doing. For those who do
not like silence this condition is correlated with
background “noise” such as music/TV programme.
2.7 Other Comfort Aspects
The upper is level of the Maslow’s pyramid of needs
the more the needs are abstracted and related with
psychology and sociology rather that physical
conditions. Thus, it is quite hard to maintain these
parameters by means of IoT devices. Anyway, some
of them should be taken into consideration for
complex comfort management, to enumerate at least:
societal acceptance and the need for efficient
communication with other people regardless
place and time (mobile phones and VoIP
communication tools well serve to this goal),
leisure, free-time organization (even if seen by
most of people as an evening in front of a TV),
fear for bad activity, self-learning of new
environments (including RTFM problems for
new devices/technologies at home and work),
stable economic situation,
safety and security aspects, including personal
security, alerting and anti-theft systems, etc.
3 COMFORT MODELING
As drawn from the list of comfort elements given in
the previous section, there are two basic types of
comfort aspects: those that reflect the (desired) state,
and those that are a consequence of a fulfilment of a
need. For the first group, we cannot simply express
what we really want, but being in certain situation
we may usually assess if we like it or not. For the
second group, we are able in advance to define
several strict demands, and further we can measure
how far we are from the fulfilment of these
demands. Thus, we may say that the notion of
comfort is a summary of two aspects (Fig. 2):
contentment, that could be define as a state of
being contented, or happiness in one’s situation,
satisfaction, that could be seen as a fulfilment of
a need (a desire).
Figure 2: Modelling e-comfort as a summary of
contentment and satisfaction.
The contentment in one’s situation is however
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linked to the satisfaction of needs and is a function
of factors. For instance, the International Standard
ISO 7730:2005 (ISO 2014) says about the thermal
comfort: A human being's thermal sensation is
mainly related to the thermal balance of his or her
body as a whole. This balance is influenced by
physical activity and clothing, as well as the
environmental parameters: air temperature, mean
radiant temperature, air velocity and air humidity.
So the fact that a human feels well in a certain
situation is not only due to a fulfilment of a need
relating to the air temperature, and some other
parameters should be taken into account. These
parameters composed the context in which the user
is situated, namely air velocity, air humidity etc. If
we generalize this idea to all comfort’s components,
we can see that e-comfort cannot be only a set of
values setting the needs. If we take another example
related to luminosity, user’s needs cannot be
restricted to light source and light intensity only, in
all situations and places. Indeed, if the user prefers
natural light as a light source, and the night comes,
the user clearly cannot be fully satisfied. His needs
are dependent on the time, the location and the
activity (to mention a few basic factors). Similarly,
if he is at work, at home or at sport place, the needs
in term of light don’t will be same. As he tends to
read, cook, eat or watch TV, his needs evaluate
towards these activities. At a sport place, some of
the factors, such as luminosity, are not so important,
while a temperature takes a role of a leading factor.
In general, human preferences towards comfort
strongly depend on the environment, or globally - a
context, which constraints user’s needs according to
(among others) time, location and activity.
Dealing with the context is not a trivial task.
Returning to the previous example, the user should
be able to define needs composed by an ordered
choice of light source and luminosity value (if a light
source is the first choice, no matter the luminosity
value, he/she will prefer natural light, or, if the first
choice is related with an amount of luminosity, no
matter from where the light comes, as long as there
is enough light, the situation is seen as comfortable),
linked to a contextual triplet {time * location *
activity}. But even if we can strictly specify
preferences for the same time, the same activity and
the same location, how can we define a moment of
optimum switch from natural light to the electrical
one because of bad weather suddenly bringing dark
clouds?
As we saw, the configuration of needs for the
user could be very difficult. Our goal is to infer
situations contenting the user from context. As
define in (Naudet 2011) a situation is a known and
pre-determined context which is composed of
elements having a location and an interval of time
and being measured (having value) coming from a
sensor. A context concerns an entity (a user), having
a status and an activity”. From that we deduce our
representation of e-comfort (cf. Fig. 3) being an
evaluation/measurement/assessment of a situation
regarding needs (or needs regarding a situation).
Situation and needs are composed of physical
comfort components which complete the
specification of a context based on (at least) the
location, the activity and the identity of the user
besides time period and/or current time.
Figure 3: e-Comfort representation for a user.
4 TWO-LEVEL ARCHITECTURE
The general architecture of the system aims at
controlling e-comfort at two layers (Fig. 4). The
upper layer is based on a multi-agent system
organized with the Moise
Inst
model (Boissier 2007).
This level is responsible for comfort management,
Figure 4: Layered system architecture.
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including the storage of user-defined requirements to
personalize the meaning of e-comfort (their needs)
and their processing regarding the situation.
Comfort definition is represented by software
agents in the form of fuzzy-assessed goals
constrained by a set of value used as arguments and
stored in the needs database. Goals are specified
through the Functional Specification of Moise
Inst
. As
the goals are restricted by the capabilities of local
IoT devices and thus usually to be reached partially
only, the system places the users in “the most
comfortable situation as possible”, however, not
necessary ideal from individual point of view. This
solution is reasonable and similar to the one widely
used for non-automated systems (“I’ll do my best,
but I cannot promise a lot”).
The meaning of comfort is mapped by the agents
to the requests for activation of IoT devices. The
requests are addressed to the lower layer. The IoT
devices are never addressed individually. Instead,
the requests are mapped to an activation of a set (a
conglomerate) of these IoT devices that are the most
suitable to fulfil this request. For that, the Structural
Specification of Moise
Inst
defined roles played by
agent representing IoT devices able to influence a
specific category of needs (temperature for
instance). The set of activated devices depends not
only on the request, it is also adjusted according to
the number and type of devices accessible at given
location, and independent context of invocation. The
above process is controlled by SITE (Semantic
Internet-of-Things Environment) (Rykowski 2011)
framework, originally designed to control dynamic
and mobile IoT systems. SITE made it possible to
propose an “intelligent” network capable of
addressing functions (services) provided by the
devices (including personal devices such as
computers/ smartphones/tablets etc.) rather than the
devices themselves, based on the semantic
descriptions of devices’ capabilities. It abstracts the
way the devices are reached through gateways and
other hardware able to communicate with the
devices according to different protocols like Zigbee,
EnOcean, Z-wave or even “traditional” WiFi, IR,
Bluetooth, etc.
5 CONCLUSIONS
In this paper a new approach to complex comfort
management is presented, aiming in automatic
treatment of different comfort parameters by means
of Internet-of-Things devices and multi-agent
system. First, we discussed comfort parameters,
based on Maslow’s pyramid of needs. We
concentrated on these parameters that may be
controlled and managed by means of IoT devices:
temperature, ventilation, humidity, noise and
acoustic background, communication, safety and
security, etc. Next, we propose a uniform way to
model the comfort pointing out mutual dependency
of several parameters (such as temperature and
humidity), and overall context (such as place and
time, but also a company of other people with
different needs and expectations). To solve possible
conflicts, we proposed two level architecture aimed
in indirect control of IoT devices (SITE
environment, lower layer) based on an ontology of
device functions, and negotiations by means of
software agents, being representatives of their
human owners (upper layer). Currently, we work on
the implementation based on SITE and Moise
Inst
MAS environments, within the scope of GOLIATH
(Goal Oriented Layered system for Interoperable
Activities of Things) project.
ACKNOWLEDGEMENTS
This work is supported by the GOLIATH project
jointly funded by the Poland NCBR and
Luxembourg FNR Lead Agency agreement, under
NCBR grant number POLLUX-II/1/2014 and
Luxembourg National Research Fund grant number
INTER/POLLUX/13/6335765.
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