seminar report on ambient intelligent

AAmmbbiieenntt IInntteelllliiggeennccee ((AAmmII))
SEMINAR REPORT
2015-2016
In partial fulfillment of Third year
In
COMPUTER SCIENCE
SUBMITTED BY
ANKITA
SRIVASTAVA
DEPARTMENT OF COMPUTER SCIENCE
VIVEKANANDA COLLEGE OF TECHNOLOGY AND
MANAGEMENT

VIVEKANANDA COLLEGE OF TECHNOLOGY
AND MANAGEMENT
DEPARTMENT OF COMPUTER SCIENCE
CCEERRTTIIFFIICCAATTEE
This is to certify that the seminar report entitled “AAmmbbiieenntt IInntteelllliiggeennccee ((AAmmII))”” is being
submitted by AAnnkkiittaa SSrriivvaassttaavvaa in partial fulfillment of Third Year in Computer
Science is a bonafide record of the seminar presented by her.
Mr. Ranjeet Rai Prof. Mr. Lalit Mohan Gupta
Lecturer HOD
Dept. of Computer Science Dept. of Computer Science

AACCKKNNOOWWLLEEDDGGEEMMEENNTT
First of all let me thank our HOD Prof: Mr. Lalit Mohan Gupta , Dept. of
Computer Science, VCTM who provided with the necessary facilities and advice. I am
also thankful to Mr. Ranjeet Rai , Lecturer, Dept of Computer Science, VCTM for
his valuable suggestions and support for the completion of this seminar. With great
pleasure I remember Miss. Aayushi Saxena, Lecturer, Dept. of Computer
Science,VCTM for her sincere guidance. Also I am thankful to all of my teaching and
non-teaching staff in the department and my friends for extending their warm kindness
and help.
I would like to thank my parents without their blessings and support I would not
have been able to accomplish my goal. I also extend my thanks to all my well wishers.
Finally, I thank the almighty for giving the guidance and blessings.

ABSTRACT
Philips Research introduced Ambient Intelligence(AmI) in the year 1998. In 2001,
AmI was taken up by The European Commission’s Information Society Technologies
Advisory Group (ISTAG). In computing, AmI refers to electronic environments that are
sensitive and responsive to the presence of people. Ambient intelligence is a vision on the
future of consumer electronics, telecommunications and computing for the time frame
2010–2020.
The development of ambient intelligence applications that effectively adapt to the
needs of the users and environments requires the presence of planning mechanisms for
goal-oriented behavior. A planning system for AmI applications is based on the
hierarchical task network (HTN) approach and is called distributed hierarchical task
network (D-HTN). D-HTN is able to find courses of actions to address given goals.
The application areas of AmI include health-related applications, public
transportation sector, education services etc. This seminar aims to give an insight into
ambient intelligence technology and a planner for AmI applications.
Keywords: Ambient intelligence, context awareness, sensors, planning, multiagents

CONTENTS
Se.no
1
Title
Introduction to AmI
Page no.
1
2 History 2
3 AmI
3.1 Vision 3
3.2 Semantics 4
3.3 Key concepts 4
3.4 Key Technologies 5
4 Social and political aspects of AmI 6
5 Relation between AmI and other Computer Science areas 7
6 5Ws and 3Ps of AmI 9
7 Architecture of AmI system 11
8 Components of AmI system 12
9 AmI System - Planning
9.1 Features of AmI systems 15
9.2 Why planning needed for AmI
Applications?
15
9.3 Planning and D-HTN planner 16
9.4 D-HTN algorithms 18
10 Application areas 20
11 Challenges 21
12 Conclusion 23
13 References 24

Dept. of Computer Science, Vivekananda College Of Technology And Management
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1. Introduction
Ambient Intelligence (AmI) is a new paradigm in Information Technology that has
potential for great impact in the future. The vision of AmI is that the people will be
surrounded by intelligent objects that can sense the context and respond according to the
desire of the people. AmI is a multidisciplinary topic, since it combines the features of many
of the areas in Computer Science.
In the last five years, we have seen significant advances in three promising technology
areas: virtual environments, in which 3D displays and interaction devices immerse the user in
a synthesized world, mobile communication and sensors, in which increasingly small and
inexpensive terminals and wireless networking allow users to roam the real world without
being limited to stationary machines. The merging of these areas allows the emergence of a
new vision: the Ambient Intelligence (AmI).
AmI refers to a digital environment that proactively, but sensibly, supports people in
their everyday lives. It will make the feeling that the people live with technology. It is aligned
with the concept of ‘disappearing computer’, since the AmI environment make the
technology invisible. As the devices grow smaller, more connected and more integrated into
our environment, the technology disappears into our surroundings.
“The most profound technologies are those that disappear. They weave themselves into the
fabric of everyday life until they are indistinguishable fromit.” M. Weiser
The basic idea behind AmI is that by enriching an environment with technology
(mainly sensors and devices interconnected through a network), a system can be built to take
decisions to benefit the users of that environment based on real-time information gathered
and historical data accumulated.
An important aspect of AmI has to do with interaction. On one side there is a
motivation to reduce the human-computer interaction as the system is supposed to use its
intelligence to infer situations and user needs from the recorded activities, as if a passive
human assistant was observing activities unfold with the expectation to help when (and only
if) required. On the other side, a diversity of users may need or voluntarily seek direct
interaction with the system to indicate preferences and needs. The entire environment around
us, homes and offices, cars and cities, will collectively develop a pervasive network of
intelligent devices that will cooperatively gather, process and transport information.

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2. History
In 1998, the board of management of Philips commissioned a series of presentations
and internal workshops, organized by Eli Zelkha and Brian Epstein of Palo Alto Ventures
(who coined the name 'Ambient Intelligence') to investigate different scenarios that would
transform the high-volume consumer electronic industry from the current “fragmented with
features” world into a world in 2020 where user-friendly devices support ubiquitous
information, communication and entertainment. In the years after, these developments grew
more mature. In 1999, Philips joined the Oxygen alliance, an international consortium of
industrial partners within the context of the MIT Oxygen project, aimed at developing
technology for the computer of the 21st century. In 2000, plans were made to construct a
feasibility and usability facility dedicated to Ambient Intelligence. This HomeLab officially
opened on 24 April 2002.
Along with the development of the vision at Philips, a number of parallel initiatives
started to explore ambient intelligence in more detail. In 2001, the concept of Ambient
Intelligence (AmI) was taken up by European Commission’s Information Society
Technologies Advisory Group (ISTAG). The term Ambient Intelligence is defined by ISTAG
as "the convergence of ubiquitous computing, ubiquitous communication, and interfaces
adapting to the user". Following the advice of the ISTAG, the European Commission used
the vision for the launch of their sixth framework (FP5) in Information, Society and
Technology (IST), with a subsidiary budget of 3.7 billion euros. EU FP6: driving vision in a
3.7BEuro 5 year ICT (Information and Communication Technologies) research program
(2002-2006). EU FP7 (9.1 BEuro for ICT): acknowledged (mainstreamed) but more
focused, systemic and transformational (2007-2012)
The European Commission played a crucial role in the further development of the
AmI vision. As a result of many initiatives the AmI vision gained traction. Fraunhofer
Society started several activities in a variety of domains including multimedia, Microsystems
design and augmented spaces. MIT started an AmI research group at their Media Lab.
Several more research projects started in a variety of countries such as USA, Canada, Spain,
France and the Netherlands. In 2004, the first European symposium on AmI (EUSAI) was
held and many other conferences have been held that address special topics in AmI.

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3. AmI: Vision, semantics, key concepts and key technologies
3.1 Vision
Ambient Intelligence (AmI) will radically change how people interact with
technology. In AmI, people will be surrounded by a multitude of interconnected embedded
systems. These devices will be able to locate and recognize objects and people, as well as
people’s intentions.
The vision of AmI is characterized by two key features: intelligence and embedding.
The feature of “intelligence” refers to the fact that the digital environment is able to analyze
the context, adapt itself to the people and objects that reside in it, learn from their behavior,
and eventually recognize as well as express emotion. The feature of “embedding” means that
miniaturized devices will increasingly become part of the invisible background of peoples’
activities, and that social interaction and functionality will move to the foreground.
it.”
According to the AmI vision,” people will not just use technology: they will live with
Hence, AmI is :-
 vision for our environment
 ‘smart electronic environment that is sensitive and responsive to the presence of
people’
 ‘Electronics embedded in every-day objects; natural interaction; context aware;
Personalized ; adaptive; responsive; pro-active.’
 Enhancing productivity, healthcare, well-being, expressiveness, creativity.

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3.2 Semantics
Ambient Intelligence refers to electronic environments that are sensitive and
responsive to the presence of people
The term ambient refers to the environment and reflects the need for typical
requirements such as distribution, ubiquity, and transparency.
 Distribution refers to noncentral systems control and computation.
 Ubiquity means the embedding is present everywhere.
 Transparency indicates that the surrounding systems are invisible and
unobtrusive.
The term Intelligence means the digital surroundings exhibit specific forms of social
interaction. In other words, an environment must recognize the people that live in it, adapt
itself to them, learn from their behavior, and possibly show emotion. In short, the
environment should be intelligent.
3.3 Key Concepts
AmI provides ‘Smarter’ living. ie. AmI is a technology for people. To refine the
notion of ambient intelligence, Marzano and Emile Aarts formulated the following five key
concepts of AmI:
 Embedded. Many networked devices are integrated into the environment.
 Context aware. The system can recognize you and your situational context.
 Personalized. The system can tailor itself to meet your needs.
s
 Adaptive. It can change in response to you.
 Anticipatory. The system anticipates your desires without conscious
mediation.
The first two elements relate to the integration of hardware devices into the
environment, and refer to embedded systems in general. Embedded systems play an

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important role in the realization of ambient intelligence because they account for the
embedding of electronic devices into people’s surroundings.
The three other key elements of ambient intelligence concern the adjustment of
electronic systems in response to users. These system adjustments occur on different time
scales. Personalization refers to those occurring on a short time scale (for example, installing
personalized settings). Adaptation involves adjustments to changing user behaviors detected
by monitoring the user over longer periods of time. Ultimately, when the system gets to know
the user so well that it can detect behavioral patterns, adjustments are possible over a very
long period of time.
3.4 Key Technologies
The benefit of an AmI system is measured by how much can give to people while
minimizing explicit interaction. The aim is to enrich specific places (a room, a building, a car,
a street) with computing facilities which can react to people’s needs and provide assistance.
In order for AmI to become a reality a number of key technologies are required:
 Unobtrusive hardware (Miniaturisation, Nanotechnology, smart devices,
sensors etc.)
 Seamless mobile/fixed communication and computing infrastructure
(interoperability, wired and wireless networks, service-oriented architecture,
semantic web etc.)
 Dynamic and massively distributed device networks, which are easy to control
and program (e.g. service discovery, auto-configuration, end-user
programmable devices and systems etc.).
 Human-centric computer interfaces (intelligent agents, multimodal interaction,
context awareness etc.)
 Dependable and secure systems and devices (self-testing and self repairing
software, privacy ensuring technology etc.)

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4. The social and political aspects of ambient intelligence
Ambient intelligence is more than just a question of embedding technology into objects.
It involves human culture in its broadest sense: universal desires; complex social
relationships; diverse value systems; individual likes and dislikes; the sustainability of
economic and natural ecosystems; and codes of ethics, conduct, and communication, both in
civil society and in business. This is also what makes ambient intelligence markedly different
from other concepts such as pervasive computing and ubiquitous computing
In AmI, technology lives with the people, hence AmI has both social and political
influences. The current phase of AmI/pervasive computing, in which computers are already
being embedded in many devices, has begun to affect our everyday lives in ways we do not
even notice.
ISTAG identified a series of necessary characteristics that will permit the eventual
societal acceptance of AmI.
AmI should:
 facilitate human contact.
 be orientated towards community and cultural enhancement.
 help to build knowledge and skills for work, better quality of work, citizenship and
consumer choice.
 inspire trust and confidence.
 be consistent with long term sustainability - personal, societal and environmental -
and with life-long learning.
 be made easy to live with and controllable by ordinary people.

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5. Relationbetween AmI and other Computer Science areas
Fig 1
Networks, Sensors, Human Computer Interfaces (HCI), Pervasive Ubiquitous
Computing and Artificial Intelligence (AI) are all relevant and interrelated but none of them
conceptually covers the full scope of AmI. Ambient Intelligence puts together all these
resources to provide flexible and intelligent services to users acting in their environments.
Ambient intelligence involves the convergence of several computing areas. It is a
multi-disciplinary approach which aims to enhance the way environments and people interact
with each other. The ultimate goal of the area is to make the places we live and work in more
beneficial to us.

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6. 5Ws and 3Ps of AmI
Of Importance for AmI are the “5Ws” (Who, Where, What, When and Why) principle
of design:
Who: the identification of a user of the system and the role that user plays within the system
in relation to other users. This can be extended to identifying important elements like pets,
robots and objects of interest within the environment.
Where: the tracking of the location where a user or an object is geographically located at
each moment during the system operation. This can demand a mix of technologies, for
example technology that may work well indoors may be useless outdoors and vice -versa.
When: the association of activities with time is required to build a realistic picture of a
system’s dynamic. For example, users, pets and robots living in a house will change location
often change location and knowing when those changes happened and for how long they
lasted are fundamental to the understanding of how an environment is evolving.
What: the recognition of activities and tasks users are performing is fundamental in order to
provide appropriate help if required. The multiplicity of possible scenarios that can follow an
action makes this very difficult. Spatial and temporal awareness help to achieve task
awareness.
Why: the capability to infer and understand intentions and goals behind activities is one of
the hardest challenges in the area but a fundamental one which allows the system to
anticipate needs and serve users in a sensible way
There seems to be a growing consensus that achieving sustainability requires a good
balance between three factors, sometimes referred to as the three P’s: people, planet, and
profit.
People: Humans exploit everything around them to improve their lives and expand the ir
powers. They want to acquire everything with minimum effort and maximum comfort. This
desire, to have devices that amplify human powers without hindering or cluttering their lives
is what drives the increasing miniaturization of devices. Many devices have already made the

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transition from big static objects to small objects that people can carry around on their bodies.
Clocks are now wristwatches, and more recently phones and audio systems have reached the
stage of becoming worn on the body. This instinct to find greater comfort, power, knowledge,
and freedom has been the main driving force behind technological innovation.
Ambient intelligence intends to improve the quality of people’s lives. Not everything
that’s possible with technology is actually desirable. Therefore, it’s crucial that people make
the right choices with ambient intelligence. This is only possible if people agree on what
quality of life and what sort of world they would like to see develop.
Planet: AmI has a great contribution to the planet. AmI provides better care for the
environment. Numerous novel ecological developments are possible by integrating smart
electronics into the environment. They aid in checking pollution and checking uncontrolled
dumping of waste products. There are also techniques for determining energy wastage and
reduce needless consumption.
Profit: Ambient Intelligence describes a new economy called “experience economy”. It is
positioned as the fourth major wave following the classic economies of commodity, goods,
and service. People are willing to spend money for getting better experience. Recollection of
a personal event might just bring back that good old feeling.
Virtual worlds in an ambient-intelligent environment might support such events.
There are many other applications, such as ambient lighting, ambient sounds and poetic
interfaces which all could bring good feel to people. A salient property of an experience is
that it can feel real, whether it has been generated by a real or a virtual cause; what counts is
the belly feeling.

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7. Architecture of AmI system
Fig 2
Sensors bring data to the system. The data collected is transmitted by the network and
pre-processed by the middleware, which collates and harmonizes data from different devices.
In order to make decision-making easier and more beneficial to the occupants of the
environment the system will have a higher level layer of reasoning which will accomplish
diagnosis and advise or assist humans with responsibility for intervention.
Elements that may be included in the high level ‘Decision Making’ process are a
‘Knowledge Repository’ where the events are collected and an ‘AI Reasoner’ which will
apply for example spatial-temporal reasoning to take decisions. For example, a decision
could be to perform some action in the environment and this is enabled via ‘Actuators’.
Knowledge discovery and machine learning techniques learn from the acquired information in
order to update the AI Reasoner in the light of experience of the
system.

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8. Components of AmI system
AmI system is comprised of three main components: ubiquitous computing,
ubiquitous communication, and user adaptive interfaces.
Ubiquitous computing means any computing device, while moving with you, can
build incrementally dynamic models of its various environments and configure its services
accordingly. The devices will be able to either "remember" past environments they operated
in, or proactively build up services in new environments. Ubiquitous computing" refers to
omnipresent computers that serve people in their everyday lives at home and at work,
functioning invisibly and unobtrusively in the background and freeing people to a large
extent from tedious routine tasks. This includes pen-based technology, hand-held or portable
devices, large-scale interactive screens, wireless networking infrastructure, and voice or
vision technology.
Ubiquitous communication: Ubiquitous computing is the introduction and
expansion of wireless network technology, which enables flexible communication between
interlinked devices that can be stationed in various locations or can even be portable.
Wireless LAN (W-LAN) applications per standard IEEE 802.11b offer high-speed
transfer rates of 11 Kbits/s and can be extended over entire office buildings and
production areas by using several access points. While W-LAN is considerably cheaper than a
traditional stationary LAN, it is often still too costly to be included in small individual devices
Bluetooth technology is used in today's handheld applications like cellular phones or
personal digital assistants (PDAs) per standard IEEE 802.15 to allow wireless connection
within a personal area network (W-PAN). While the cost of Bluetooth equipment is
significantly lower than the cost of W-LAN, the transmission range of up to 10 meters and
the data transfer rate of less than 720 Kbit/s are inferior. New Bluetooth versions are
currently under development that attempt to eliminate the latter drawback. V1.2 allows rates
of up to 3 Mbit/s, V2.0 of up to 12 Mbit/s
High rate W-PANs per standard IEEE 802.15 TG3, launched in 2003, use higher
power devices (8 dBm) than regular Bluetooth equipment (0 dBm) to transmit data at a rate
of up to 55 Mbit/s and over a range of up to 55 m. This technology is, therefore, an attractive

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alternative to W-LAN, especially considering the comparatively lower cost.
Low power W-PANs per standard IEEE 802.15 TG4 are particularly useful for handheld
devices since energy consumption for data transmission purposes, and costs, are extremely
low. The range of operation of up to 75 m is higher than current Bluetooth applications, but
the data transfer rate of 250 Kbit/s is lower.
Wireless body area networks (BANs) interlink various wearable devices, such as
wireless data glasses, earpieces, microphones, and sensors, and can connect them to outside
networks. BANs are often used for medical applications but also in work-related fields, for
example, to provide production operators with instructions that are adapted to the respective
work situation. BANs usually consist of a central network unit, which connects the devices
and which can provide an interface to further networks outside the BAN, for example, via
Bluetooth. Advantages of BANs versus W-PANs are the short range and the resulting lower
risk of tapping and interference, as well as low frequency operation, which leads to lower
system complexity. Technologies used for wireless BANs include magnetic, capacitive, low-
power far-field and infrared connections, while non-wireless BANs use wires or conductive
fabrics.
Radio frequency identification (RFID) encompasses wireless identification through radio
transmission. RFID systems comprise a read/write station and active (with own power
source) or passive (power supplied by the read/write station) transponders (transmitter /
responder), and can be used in a variety of applications. Traditional examples include
protection against theft, access control, and billing. The range of possible applications is
much greater: RFID systems can be used for material tracking in manufacturing and logistics,
for cash register applications in stores as an alternative to barcode scanning, or for localizing
items or persons.
Network administration is facilitated by minimizing the effort required for setting up
networks. The introduction of mobile ad hoc networks (MANETs) is an important step in this
direction. A MANET uses the wireless technologies described in the list above but is more
flexible than conventional networks, since the routers are included in the mobile nodes
instead of being fixed and have the ability to configure themselves. This provides the network
with great flexibility due to its ability to adapt automatically to a changing network
environment.

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User adaptive interfaces
User adaptive interfaces, the third integral part of AmI, are also referred to as
"Intelligent social user interfaces" (ISUIs). These interfaces go beyond the traditional
keyboard and mouse to improve human interaction with technology by making it more
intuitive, efficient, and secure. They allow the computer to know and sense far more about a
person, the situation the person is in, the environment, and related objects than traditional
interfaces can.
ISUIs encompass interfaces that create a perceptive computer environment rather than
one that relies solely on active and comprehensive user input. ISUIs can be grouped into five
categories:
 Visual recognition (e.g. face, 3D gesture, and location) and output
 Sound recognition (e.g. speech, melody) and output
 Scent recognition and output
 Tactile recognition and output
 Other sensor technologies
The key to an ISUI is the ease of use, in this case the ability to personalize and
adapt automatically to particular user behavior patterns (profiling) and different situations
(context awareness) by means of intelligent algorithms. In many cases, different ISUIs, such
as voice recognition and touch screen, are combined to form multi-modal interfaces. ISUIs
make network usage more secure as the interfaces can identify users automatically by, for
example, face or voice recognition instead of requesting a password.

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9. AmI system - Planning
9.1 Features of AmI Systems
AmI system is composed of numerous agents. Agents are smart devices, which are
fixed or mobile devices. Agents form part of AmI system either permanently or temporarily.
For example a person comes with a mobile phone into a room equipped with AmI system.
The cell phone, when properly connected to the network of other devices, is temporarily part
of the system. After the person leaves the room is disconnected.
Features of AmI system are:-
• Feature 1: Some agents could take no responsibility in building the plan because of their
limitations in processing and communication. This pushes toward the centralized
planning process.
• Feature 2: The skills to perceive the environment and to perform the actions are
distributed over the agents. This pulls toward the distributed planning process.
9.2 Why Planning needed for AmI applications?
The development of ambient intelligence (AmI) applications that effectively adapt to
the needs of the users and environments requires the presence of planning mechanisms for
goal-oriented behavior. An AmI system that plans is able to find a course of action that, when
executed, achieves a desired effect. The planning system builds plans according to the
capabilities of available devices that perform actions to satisfy the user’s need.
A planning system for AmI applications proposed by Francesco Amigoni, Associate
Member, IEEE and Nicola Gatti, Member, IEEE, is based on the hierarchical task network
(HTN) approach and it is called distributed hierarchical task network (D-HTN). D-HTN
planner can support both the features of AmI systems; i.e centralized as well as distributed
features.

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9.3 Planning and D-HTN planner
A planning algorithm has three inputs:
– a description of the world,
– a description of the goal,and
– a description of the capabilities in form of possible actions that can be
performed.
The planning algorithm’s output is a sequence of actions such that, when they are executed in
a domain satisfying the initial state description, the goal will be achieved. AmI system need a
centralized planner that manages distributed capabilities. A distributed HTN approach
appears appropriate for AmI applications because it naturally supports heterogeneous agents
and knowledge exchange among them.
D-HTN planners are based on the concept of task network that is represented as
[(n1:1 ),(n2:2 ),……(nm: m), ]
where
 i are tasks, either primitive (that can be directly executed by an agent) or
nonprimitive (that must be further decomposed);
 ni are labels to distinguish different occurrences of the same task;
 is a Boolean formula representing the constraints on the tasks, such as variable
bindings constraints [e.g.,v=v’], ordering constraints [e.g., (n<n’), with the meaning
that n must be executed before n’], and state constraints [e.g.,(n,l,n’) , with the
meaning that l must be true immediately after n, immediately before n’, and in all
states between n and n’ ].
A task network can be represented by a graph. For example, the task network:

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Fig 3
The intended meaning of this graph is that, in order to request a good g1 by e-mail, we
first have to create the RequestText t1 and look for the EmailAddress a1 of a supplier of g1,
and then we have to SendEmail with content t1 to a1.
Functions of Agents and Planner in D-HTN planner:-
• AGENT:
– Each agent keeps a local data structure called plan library, which stores all the
decompositions it knows.
– The decompositions in the plan library of an agent have been defined by the
designer during the installation of the agent and are peculiar for each agent
• PLANNER:
– generate a plan, the other agents are only requested to communicate
decompositions .
By means of a communication mechanism based on message passing,
– the planner can ask the currently connected agents to send their available
decompositions for a given task
– the agents can send to the planner the requested decompositions.
D-HTN planning starts with an initial task network D representing the problem (the
goal) and with a set M of methods or decompositions. Each decomposition is a pair
m=(t,d),where t is a non-primitive task and d is a task network; m says that a way to achieve
is to perform the tasks in . Then, D-HTN planning proceeds by finding a non-primitive task
from the current task network D and a method m=(t’,d’), in M such that t’

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unifies with t and by replacing t with d’ in D. When only primitive tasks are left in D, a
plan for the original problem can be found. A plan is a sequence of ground primitive
tasks .This pure HTN planning process can be refined to make it more efficient by
introducing backtracking, critic functions, and other technicalities.
Each decomposition has associated three numerical indexes that are associated to:-
– Performance -measures the expected effectiveness of the decomposition
– Cost- measures the expected resource consumption for performing the tasks in
the decomposition
– Probability of success - measures the expected likeliness that no error occurs
9.4 D-HTN Algorithms
D-HTN is composed of a set of distributed algorithms that are executed concurrently
by the planner and by the agents. Algorithm 1 presents an overview of the D-HTN algorithm
executed by the planning agent. The main data structure to represent the plan that is being
formed is a task network D. D is initialized with the initial task to be solved (i.e., the goal to
be reached). The D-HTN planner produces a final plan D composed only of primitive tasks
that can be executed by the agents. M(t) denotes the decomposition set.
Algorithm 1 D-HTN algorithm for the planner
1: D = initial task
2: while D contains non-primitive tasks do
a) choose a non-primitive task t from D
b) populate M(t), by requesting the currently connected agents to send
the decompositions m = (t’, d’) such that t’ unifies with t and by
collecting these decompositions
c) choose a decomposition m = (t’,d’) from M(t)
d) if t is primitive for the agent a proposing m then
bind a to t and remove t from the non-primitive tasks
3:end while
e) end if
f) replace t with d’ in D

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Algorithm 2 D-HTN algorithm for the agents
1: while the agent is active do
a) wait for a message from the planner
b) if the message is a request of decompositions for a non-primitive task t
then
send to the planner the decompositions m = (t’, d’) in the
plan library such that t’ unifies with t
c) end if
2: end while

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10. Application areas
Ambient Intelligence possesses applications in many areas. Some of them are listed below:-
• Health-related applications. Hospitals can increase the efficiency of their services by
monitoring patients’ health and progress by performing automatic analysis of activities in
their rooms. They can also increase safety by, for example, only allowing authorized
personnel and patients to have access to specific areas and devices.
• Public transportation sector. Public transport can benefit from extra technology including
satellite services, GPS-based spatial location, vehicle identification, image processing and
other technologies to make transport more fluent and hence more efficient and safe.
• Education services. Education-related institutions may use technology to track students
progression on their tasks, frequency of attendance to specific places and health related issues
like advising on their diet regarding their habits and the class of intakes they opted for.
• Emergency services. Safety-related services like fire brigades can improve the reaction to a
hazard by locating the place more efficiently and also by preparing the way to reach the place
in connection with street services. The prison service can also quickly locate a place where a
hazard is occurring or is likely to occur and prepare better access to it for security personnel.
• Production-oriented places. Production-centred places like factories can self-organize
according to the production/demand ratio of the goods produced. This will demand careful
correlation between the collection of data through sensors within the different sections of the
production line and the pool of demands via a diagnostic system which can advice the people
in charge of the system at a decision-making level.

~ 21 ~
11. Challenges
Fig 4
The fast penetration of wireless communications has put into evidence the user’s need
to get easily connected anywhere and anytime at an affordable price. On the one hand,
wireless communications clearly proved that the most a technology provides simple access
means, added to freedom of movement and increased security, the most the user is willing to
accept it.
On the other hand, the most a technology is complex and costly, the less the user is
prone to accept it, in spite of possibly large potential advantages, which are generally not
reachable by the average user not interested in spending time and energies in acquiring the
underlying technology fundamentals. As a consequence, the successful systems of the future
will adhere to the paradigm of ”disappearing technologies”, both valid for communications
and computing, and will provide improved ease-of use at the expense of an increased, but
invisible to the user, complexity of the underlying systems and networks necessary to
transport and process the information in the different multimedia forms and usage contexts.

~ 22 ~
Ambient Intelligence faces a lot of challenges. Among these are the social implications
of AmI environments, the different potentials of AmI to enrich our lives, aspects of privacy
and trust, characteristics of different AmI interactions, how much intelligence people are
willing to accept, the different dimensions of the term ambient, the design of future
interaction spaces and intelligent artifacts, factors of user experience for implicit interaction,
existing and emerging AmI application areas and scenarios, the connection of AmI concepts
to physical spaces where it happens etc.
• Challenges in Interaction technology
 Develop ambient interaction concepts that are truly intelligent, simple,and
intuitive.
 Integrate multi-modality with context awareness and intuitive feedback
mechanisms.
 Integrate smart media access into surroundings (audio, video, and light).
Develop interaction concepts for novel AmI technologies (photonic textiles, e-
paper, polymer lighting)
• Challenges in Innovation
 Build an eco-system that uses co-creation as a model for open innovation.
 Involve multiple parties in the user centered design cycle at large.
 Concentrate on well-defined business domains (i.e., hospitality, fashion,
furniture, well-being, city beautification).
 Develop new business models for AmI innovation
• Challenges in Involvement
 Reach out to ordinary people so as to let them participate in the AmI effort.
 Involve ordinary people in the user centered design cycle at large.
 Let people experience the AmI future and live in it yourselves.
 Make AmI part of education.

~ 23 ~
12. Conclusion
Ambient Intelligence (AmI) is growing fast as a multi-disciplinary topic of interest
which can allow many areas of research to have a significant beneficial influence into our
society. AmI is a vision on the future of consumer electronics, telecommunications and
computing for the time frame 2010–2020.
Ambient Intelligence envisions a world where people are surrounded by intelligent
and intuitive interfaces embedded in the everyday objects & physical environments around
them. These interfaces recognize and respond to the presence and behaviors of an individual
in a personalized and relevant way.
The new paradigm of ambient intelligence can bring about a revolution in the design,
appearance, and use of electronics in ordinary life. It could support and facilitate simple and
recurrent tasks, but it could also lead to a culture very different from today’s. This new
culture could develop through the expansion of the use media into a world in which physical
and virtual experiences merge to support personal expression, business productivity , and
personal lifestyles.
Technology will not be the limiting factor in realizing ambient intelligence. The
ingredients to let the computer disappear are already available, but the true success of the
paradigm will depend on the ability to develop concepts that allow natural interaction with
digital environments.

~ 24 ~
13. References
1. www.comsis.org/pdf.php?id=nst-4604
2. https://en.wikipedia.org/wiki/Ambient_intelligence
3. www.sciencedirect.com/science/article/pii/S157411920900025X
4. www.slideshare.net/nikhilpatteri/ambient-intelligence-28697238
5. Scholarly articles for ambient intelligence technologies
applications and opportunities
6. www.neurovr.org/emerging/book5/01_AMI_Alcaniz.pd
7. www.collegelib.com/t-ambient-intelligence-seminar-report-
abstract.html
8. www.research.microsoft.com/enus/um/people/liuj/publications/ami.p
df
9. AmbientIntelligence:European Conference,AmI2008,Nuremberg,
Germany ...
10.https://books.google.co.in/books?isbn=3642251676

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