The rise in the average age and the decrease in the rate of births, cause the phenomenon called population ageing, which rises a number of issues. The oncoming shortage of caregivers and the strong desire of the older adults to live in their own homes originated an increasing interest in Ambient Assisted Living (AAL). AAL encompasses technical systems to support people in their daily routines. The paper focuses on the technological aspects of AAL systems describing the capabilities they require and how they are being addressed.
The rise in life expectancy is one of the great achievements of the twentieth
century. This is a still running trend, as life expectancy is projected to reach
83 years in the more developed regions and 75 years in less developed ones by
2045-2050 [
Considering constant the current use rates, the number of people requiring
such services will double by 2040 [
From a technological point of view, the oncoming shortage of caregivers and
the strong desire of the great majority of older adults to live in their own homes
and communities originated a still increasing interest in what has been de ned
as Ambient Assisted Living (AAL) [
AAL systems usually rely on the sense-act/interact loop depicted in Figure 1.
The Sensing and the Asking activities capture respectively information from
the environment and wanted from the users. Reasoning is in charge of
interpreting captured data to act on the environment and on the user respectively
through the Acting and the Noti ng capabilities. The user can be considered as
part of the environment itself: information about him can be obtained through
Q&A or observation capabilities. Finally, in order to cooperate, each activity
relies on Communicating technologies depicted as pink arrows in Figure 1.
Sensing is the fundamental capability of an AAL system because sensors capture
information about the environments and the people who inhabit it. Sensors are
usually enriched with processing and communication capabilities. Such sensors
are commonly called smart sensors, which can be seen as a special case of smart
objects, that is, autonomous cyber-physical objects augmented with sensing (or
actuating), processing, storing, and networking capabilities [
Person's position and movements are commonly exploited in order to perform
ADLs (Activities of Daily Living) recognition and classi cation [
IDenti cation (RFID). { Body position and movement are normally obtained by tri-axial accelerometers, magnetometers, and angular rate sensors.
Environmental Sensors. Environmental sensors are embedded into the
environment. They typically detect conditions that are descriptive of the
environment or interactions between users and the environment. Research in this speci c
eld is usually divided between video-based and non-video-based solutions.
Video-Based AAL Solutions. Vision-based solutions for AAL applications (VAAL)
is a trending topic mainly due to the high versatility of cameras. The most
explored areas are activity recognition in the rehabilitation and health care [
Non-Video-Based AAL Solutions. Sensors in this category usually have only
a few parameters they can monitor, reason for which they are often combined
together. Some examples of sensed parameters are:
{ Ambient light is usually measured with sensors based on photodiodes.
{ Room temperature is acquired as body temperature, thus using thermistors.
{ Humidity is usually sensed by a Relative Humidity (RH) sensor.
{ Movement and presence are usually sensed by Passive Infrared Sensors (PIR).
{ Door/window/cabinet open/closed is usually obtained by a magnetic
proximity switch based on reed elements.
{ Pressure, intended as the force applied toward a surface, is obtained by
forcesensing resistors that can be easily attached to at surfaces such as chairs.
{ Environmental sounds are sensed through microphones. The more widely
adopted are Electret, which are speci c kind of capacitor microphones that
do not need a constant source of electrical charge to operate. Microphones
can be used as presence sensor (like PIRs) or to achieve acoustic source
localisation [
Environmental sensors overcome the main issue of wearable sensors by not requiring the users to always wear them. However, they have their own issues (apart privacy and acceptability problems): their price is higher, their require installation (and, thus, related cost), and they are xed on their location, thus operating as long as the user is at home.
Trends in Sensor Technology. Since wearable sensors loose their
functionalities if not worn, the research trends are toward size and weight reduction,
durability, and waterproo ng. Microelectromechanical Systems (MEMS, but it
is also known as micro-machines in Japan or Micro Systems Technology (MST)
in Europe) is an innovative technology consisting in miniaturising mechanical
and electromechanical elements using micro-fabrication techniques.
Miniaturisation has also enabled ingestible sensors and implantable sensors, mostly used
in professional medical environments. Ingestible sensors are systems integrated
into ingested devices such pills. They are conceived to be powered by the body
and communicate through the tissue. These sensors can monitor ingested food,
weight, and various physiological parameters, but also body position and
activity, thus favouring users sustaining healthy habits and clinicians providing more
e ective healthcare services [
Reasoning is the process of converting data acquired from the eld to meaningful
information, which may have di erent meaning at multiple levels of
interpretation (e.g., 12 oclock (noon) may mean 12:00, mid-day, day time and so on),
depending on the personal context of the user. Personal Context is de ned as
user speci c context information: parts of the environment (e.g. things, services,
and other persons) accessed by the user; the physiological state (e.g. pulse, blood
pressure, weight) and psychological state (e.g. mood and stress); the tasks that
are being performed; the social aspects of the current user (e.g. friends, neutrals,
co-workers, relatives); the spatio-temporal aspects of the other context
components from the user point of view [
Data collection and processing. Data acquired via the sense activity is
usually easy to collect and process, however the amount of such data is a challenge
especially if audio and visual information is included. Being able to obtain and
integrate information from di erent kinds of sensors and sources is crucial to
make AAL systems able to recognise events and conditions and, thus, to
identify contexts and status. This skill is called sensor data fusion and is de ned as
the process of combining data to re ne state estimates and predictions [
in AAL should be able to understand the contexts and the current status not
only by using static rules and patters, but also dynamic and reactive models that
take into consideration complex information (e.g., behaviour models of users).
Moreover, they should be able to extract relevant information (data mining) and
update the same models (learning machine). Speci cally, AAL systems need to
have capabilities such as: reinforcement learning (i.e., learning from the world
observations), learning to learn (i.e., learning from previous experiences),
developmental learning (i.e., learning from the world exploration), and e-Learning
(i.e., learning from the Web and information technology) [
One of the main contribution that reasoning algorithms o er is the
ability to recognise user activities. Di erent methods are available to recognise
activities [
Models of the user behaviours and the recognition of activities are fundamental for predicting probable statuses and context outcomes. This property is necessary both for anticipating possible negative events and conditions, thus acting in order to avoid them, and for predicting desires of the users, thus increasing their satisfaction.
Although recognising normal activities has a key role in health applications,
abnormal events are very important too, as they usually indicate a crisis or an
abrupt change in regimen that is associated with health issues. Likewise
normal activities, abnormal activities can be recognised by classi ers, which
usually require to be trained with datasets containing examples of the activities to
be recognised. However, datasets containing activities related to critical
situations (such as heart disfunction or falls) are rarely available. For these reasons,
anomaly detection in AAL is receiving an increasing interest [
Spatio-temporal reasoning. Being able to reason on spatial and temporal
dimensions is a key element for understanding the current situation. For example,
a smart house system is able to recognise if someone turns on a cooker and leaves
it unattended for more than 10 minutes; if this happens the system takes action
by autonomously turning o the cooker and/or warning the user [
Interaction is a well studied area under the umbrella of the Human Computer
Interactions (HCI) and it encompasses all kinds of tool, both software and
hardware, that allow the interaction process between the user and the system [
The HCI may be explicit or implicit. Explicit HCI (eHCI) is used explicitly by the user who ask the system for something. This kind of interaction is in direct contrast with the idea of invisible computing, disappearing interfaces, and ambient intelligence in general. eHCI always require some sort of dialog between a user and the system and this dialog brings the computer to the centre of the user's activity.
Implicit HCI (iHCI) tries to reduce the gap between natural interaction and
HCI by including implicit elements into the communication: the system acquires
implicit input (i.e., human actions and behaviours done to achieve a goal, not
primarily regarded as interaction with a computer) and may present implicit
output (i.e., output from a computer that is not directly related to an explicit
input and that is seamlessly integrated with the environment and the task of
the user) [
Comparing the way in which people interact to the way people interact with
machines, it becomes clear that HCIs are still at their early stages. What
humans expect from interactions is dependent on the situation, which is one of the
concepts on which the eld of Context Awareness Computing is based [
This is particularly true in AAL because most of the current and near
future end-users of any AAL system are individuals with low to none a nity for
technology. In order to develop successful interfaces for AAL services, designers
should act accordingly to usability and acceptability criteria. Among all the
theories, the most important are the Technology Acceptance Model [
Adding acting capabilities to an AAL system can be seen as obtaining the equivalent of a Closed Loop Control System in Control Theory, although the parameters a ected by the actuation may not always be monitored by sensors and not every sensed parameter may be in uenced by the actuations.
While sensors are required to understand and monitor the physical world, actuators are those mechanical objects that act on the physical world as a consequence of a software system action.
The number of di erent available sensors greatly outnumbers the number of actuators. However a few key actuators are su cient to build a large number of complex smart objects.
The most common and simple actuators are already present in most of the homes, but almost always they are standalone systems. For example, indoor illumination and air conditioning (AC) systems. First attempts into making illumination systems more context aware have been achieved by coupling lightbulbs with motion sensors (PIRs): this way the lights do not require any explicit interaction in order to be switched on or o , but the movement of the user is an implicit input that cause the lights switching.
Actuators. As mentioned, there is a small set of common actuators that are
used as building blocks in AAL systems. Some examples are:
{ Relays are usually electromechanical devices acting as remote switches that
can be activated by a software system through a low-power signal.
{ MOSFETs (Metal-Oxide-Semiconductor Field-E ect Transistors) are
transistors and serve as switches. Compared to relays, MOSFETs are usually
very small and some of them can switch almost 10 orders of magnitude
faster then relays. However, magnetic elds, static electricity, and heat can
easily broke them. They are usually employed to operate in low amperage
situations (e.g., to switch on/o led lights or motors and servos).
{ Lights have been among the rst actuators included in AmI system.
Modern lights for AAL usually support dimmer facilities, provide di erent light
colours, and include a small micro controller handling communication. Most
of the modern lightning solutions are based on Light Emitting Diodes (LEDs)
that can come to full brightness without need for a warm-up time.
{ Motors commonly used are the DC (Direct Current) ones. Their are used in
garage doors, curtains, or wheel chairs. A DC motor is a device that converts
electrical energy into mechanical energy. In order to increase precision,
stepper motors are usually adopted. Another highly used class of electric motors
are servo motors, which are electric motors that can push or rotate an object
with great precision. Servo motors are commonly adopted for precise, small
movements that may require high torque.
{ Screens and speakers provide feedback or information by transforming
electrical data into physical phenomenons, light emissions, and sound waves
respectively.
{ Haptic feedback engines date back to 1968 [
Communicating capabilities are key aspects of AALs, since they are usually
made up of distributed devices cooperating to provide the desired services. Three
di erent types of networks are considered in AAL systems:
{ WANs are employed whenever an AAL system needs to transmit information
outside the system. Today solutions usually exploit an Internet connection
obtained through one of the di erent providers available. With the increasing
number of devices connected to the Internet, identi cation and addressing
have been the most studied issues, which resulted in IPv6.
{ LANs are used within home systems. They count di erent classes of
technologies, such as cabled connections, powerline communications or wireless LAN
(WLAN). Home automation often exploits dedicated buses, which means
that gateways must be considered in order to put home automation systems
in communication with the rest of the AAL structure.
{ BANs derives from the widespread use of wearable devices [
There are three generations of technologies supporting AAL [
First generation solutions requires users to wear a device, generally equipped
with a button that the user can press in order to alert call centers, informal
caregivers (family members), or emergency services. A reduction of the stress
levels among the users and the caregivers, the reduction of hospital admissions,
and the delayed transfers to long-term care facilities are some of the bene ts
achieved [
Second generation solutions usually feature a proactive behaviour. They are
able to autonomously detect emergency situations, such as falls [
Third generation solutions are the most advanced and exploit recent ICT advancements. Third generation solutions are not only able to detect and report problems, but proactively try to prevent problems and emergency situations. Prevention can be achieved by two di erent activities: the rst is the monitoring of the user's vital signs, and of any eventual change in his mobility and activity patterns, thus predicting ongoing changes in health status; the second activity is aimed at limiting the exposure of the user to high risk situations on the basis of actions performed and by using actuators.
Fall detection systems represents a good example of three stages of evolution of AAL systems: early proposals were passive and relied on the user actions; contemporary solutions are autonomous and proactively detect falls; nally, most innovative approaches are going toward falls prediction and avoidance.
Falls represent a major health risk that impacts the quality of life of elderly.
Roughly 30% of the over 65 population falls at least once per year, the rate
rapidly increases with age and among people a ected by Alzheimer's disease.
Fallers not able to get up by themselves and that lay for an extended period will
more likely require hospitalisation and face higher dying risks [
The factors that impact the risk of falls have been classi ed in two categories:
intrinsic and extrinsic risk factors. Intrinsic risk factors include age, low mobility,
bone fragility, poor balance, chronic diseases, cognitive and dementia problems,
Parkinson disease, sight problems, use of drugs that can a ect the mind, incorrect
lifestyle (inactivity, use of alcohol, and obesity), and previous falls. Extrinsic risk
factors are usually related to incorrect use of shoes and clothes as well as drugs
cocktails. Finally some environmental risk factors related to indoor falls have
been identi ed as slipping oors, stairs, and the need to reach high objects. Only
8% of people without any of the risk factors fell, compared to 19% of people with
one risk factors, 32% of people with two, 60% of people with three, and 78% with
four or more risk factors [
A number of platforms have been proposed in the literature, one of the rst and
more general purpose AAL projects was CASAS, that stands for Center for
Advanced Studies in Adaptive Systems. Its goal is to design a smart home kit that
is lightweight, extendable, and with a set of key capabilities [
Other solutions are more directly focused toward the phenomenon of the ageing population and therefore to the elderly.
As an example, the iNtelligent Integrated Network For Aged people (NINFA)
is a project focused on the users wellness. The aim is to build a service platform
suited for elder people whose user interface allows to deliver at home di
erent services, such as user supervision, communication and interaction among
users for social inclusion, exergame delivering [
There are also other solutions, that aim to support users with speci c needs,
regardless of their age. As an example, the BackHome project is focused on
designing, implementing, and validating person centred solutions to end users with
functional diversity. The project aims at studying how brain-neural computer
interfaces and other assistive technologies can help professionals, users, and their
families in the transition from hospitalisation to home care. BackHome main goal
is to help end users to accomplish goals that are otherwise impossible, di cult, or
create dependence on a carer [
Nefti et al. propose a multi agent system for monitoring dementia su erers.
Besides classical sensors (such as, temperature sensor and infrared motion
sensors), the system uses speci c sensors, such as natural gas and monoxide sensors,
smart cup in order to measure regular uid intakes, ood sensors near sinks, and
magnetic contact switches for monitoring doors and windows [
Jeet et al. propose a system in which verbal and nonverbal interfaces are used
to obtain an intuitive and e cient hands-free control of home appliances [
Alesii et al. propose a solution targeted to people a ected by the Down
Syndrome. The system provides a presence and identi cation system for domestic
safety, a dedicated time management system to help organise and schedule daily
actions, and remote monitoring, control, and communication to allow caregivers
and educators sending messages and monitoring the user situation [
Lind et al. propose a solution targeted to people with severe heart failure,
taking into consideration how an heart monitoring system should work in a contest
where users are used to heart monitoring but not accustomed to technology [
EpiWatch. EpiWatch helps users to manage their epilepsy by tracking the
seizures and possible triggers, medications, and side e ects. Data are collected
from sensors and from surveys that investigate the activities performed and the
user's state before and after the attacks, and notes about medical adherence [
The paper presented an overview of the current state of AAL from a technological point of view. Enabling technologies for both the Sensing and the Acting activities are nowadays available. Moreover, both sensors and actuators are going to be embedded in more and more items, which will allow to obtain more and diversi ed data and control di erent aspects of the physical world respectively. Finally, a lot of interest is currently put toward further miniaturization, cost reduction, and precision of both sensors and actuators.
For what concerns the Reasoning activity, the community is very active: context modelling and understanding is fundamental in order to make meaningful inferences on the sensed data. As the acquisition of the data improves in quality and quantity, new inference engines can be designed and with them new AAL systems. Finally, more detailed context and user understanding, allow the Interacting activity to move toward the concept of custom tailored implicit interaction between users and systems.