Internet of Things Controlled Home Objects for the Elderly
Research Dawadi, Zeeshan Asghar and Petri Pulli
Department of Information Processing Science, University of Oulu, Oulu, Finland
Keywords:
Systematic Literature Review, Internet of Things, Visualization, Elderly Assistance, Caretaker, Remote
Assistance, Assisted Living.
Abstract:
The number of elderly people suffering from physical or cognitive difficulty is increasing continuously. El-
derly people prefer to live in their familiar environment where they can easily perform different activities of
their daily life which is also good for their mental and physical well-being. Internet of Things is a mecha-
nism through which any objects can be monitored, controlled, and manipulated. In order to develop efficient
application for the elderly living at home independently, the researcher should be aware of the home objects
as well as of the living environment. This study uses systematic literature review to determine applications
developed to assist elderly people inside their home. A total of 25 primary studies are identified. With the
analysis of those studies, important and relevant objects in the daily life of the elderly are identified. Using the
results from the review, a new scenario of home environment is visualized. The visualization is expected to
provide caretakers with a better view of the living condition of the elderly and position and state of the home
objects. This new home scenario is expected to offer a secure and easy living environment for the elderly,
where Internet of Things can be used to control all the frequently used home objects by the elderly.
1 INTRODUCTION
Internet of Things (IOT) is a developing phenomenon
in the field of technological advancement as well as in
research domain (Atzori et al., 2010; Xu et al., 2013).
The main principle of IOT is continuous monitor and
control of everyday objects or things over the inter-
net. The thing in IOT has no limitation and can be
any objects that are used in day to day life (Bassi
and Horn, 2008). The thing can be any living or
non-living object; from electronic devices to foods,
clothes and furniture we use in our daily life, from
animals like cow, dog, cats, and rats, to plants and
trees (Madakam et al., 2015). An object or thing has
its own unique identity, which allows communication
between not only humans, but also between objects
(Madakam et al., 2015). With availability of continu-
ous internet connection, all the connected objects can
be monitored regularly through an interconnected net-
work.
Over 7% of the world population are over 65 years
of age and the number is expected to increase 20% by
the year 2050 (Morris et al., 2013). Also, by 2035, the
number of people affected by dementia is expected to
double. Hence there is requirement of policies and
resources to meet the need of the aging population
as well as of those suffering from dementia. Elderly
can live longer and safer if they stayed in their own
home environment (Bassi and Horn, 2008). Their
friends and family also feel secure to have them in
their own house in comparison to hospitals and care
homes (Arcelus et al., 2007). Hospitals and health-
care centres may not be able to provide services to all
who require (Arcelus et al., 2007). Smart homes can
provide automation of domestic tasks, easier commu-
nication, higher security, and are adaptive to modern
human needs as well as social needs (Morris et al.,
2013; L
ˆ
e et al., 2012).
The aim of technological advancement for elderly
is to provide them a sense of independence even if
they are physically or cognitively incapable. Avoid-
ing diseases and encouraging healthy living is also a
prime concern (Tran, 2002). Everyday activities that
are easy to accomplish can be problematic as people
get older. Simple tasks like brushing teeth, turning the
tap off, switching TV off or on, and taking medicines
can get tougher with age (Morris et al., 2013). IOT is
a step forward in helping elderly complete these activ-
ities without physical presence of a caretaker, which
also helps to minimize their expenses (Arcelus et al.,
2007). IOT will also help one caretaker to moni-
tor and assist multiple elderly patients from a remote
location. With IOT, caretakers have the freedom to
244
Dawadi R., Asghar Z. and Pulli P.
Internet of Things Controlled Home Objects for the Elderly.
DOI: 10.5220/0006109802440251
In Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2017), pages 244-251
ISBN: 978-989-758-213-4
Copyright
c
2017 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
manipulate the home objects themselves and control
them.
Above mentioned concerns motivated us to con-
duct a study to find different IOT based applications
targeted for the elderly people living alone. Moreover,
the goal of the study is to determine different kinds
of home objects dealt in those applications. Figure 1
shows the overall idea of the study. This study is ben-
eficial for those researchers and developers who are
using IOT for the care and well-being of the elderly.
The paper is structured as follows: section 2 presents
an overview of previous studies. Section 3 explains
the research method carried out for the study, and sec-
tion 4 presents the findings of the study, limitation of
the study, and scope for future research. Section 5
concludes the paper highlighting the main contribu-
tion of our work.
Figure 1: Overview of the study.
2 RELATED STUDIES
This section discusses about IOT and its all-round ef-
fectiveness. Furthermore, it accentuates some studies
that highlights importance of IOT based applications
for the elderly.
2.1 Internet of Things
IOT shows us a world where anything can be con-
nected to any other thing. With embodiment of sen-
sors and actuators in various physical objects, rang-
ing from roadways to pacemakers, an object can both
sense the environment and communicate. Informa-
tion about the objects can be retrieved faster with IOT
and people can make wise decisions quickly (Bassi
and Horn, 2008). IOT enables inter-connectivity of
different objects through a global infrastructure, in-
ternet (Madakam et al., 2015). IOT have been used
successfully in various fields such as assisted living,
e-health, domotics, enhanced learning, surveillance,
environment monitoring, health monitoring, critical
infrastructure monitoring, etc. (Atzori et al., 2010;
Gubbi et al., 2013).
The main strength behind IOT is that using inter-
connected devices, it can have high impact on several
aspects of our everyday life (Atzori et al., 2010). Con-
sidering the increasing number of research on IOT
in recent years (Stankovic, 2014), it can be expected
that IOT will play a greater role in our daily lives
in upcoming years. IOT can help in digitalization
of day to day activities, providing security in build-
ings, and decreasing the energy consumption of de-
vices. IOT is not an independent system, but it can
be regarded as a critical, integrated infrastructure by
the use of which many applications and services can
operate (Stankovic, 2014).
2.2 IOT and Elderly
As people grow older, their social circle and fre-
quency of communication decreases on a regular ba-
sis. It can be caused by loss of family members or
friends, diminishing eyesight or hearing ability, cog-
nitive impairment, memory loss, etc. (Touhy and Jett,
2013). Moreover, their relatives and family members
live far from them. It leads to a sense of isolation that
may impact mental as well as physical health (Var-
doulakis et al., 2012; Williams et al., 2014). The
loss of physical as well as cognitive abilities affects
their day to day activities and they require assistance
in completing their daily tasks.
The introduction of IOT in the life of elderly peo-
ple can help monitoring of chronic illness, on de-
mand provision of fresh food, sending alarms and
reminders, and enabling communication with family,
friends or health care professionals (Dohr et al., 2010)
as depicted in figure 2. Reminders of stove or iron
left on, alerts at front door about visitors or intruders
at home, etc. can be helpful for physically and cog-
nitively disabled elderly people (L
ˆ
e et al., 2012), but
with IOT this service can be improved since required
action can be taken by the caretaker remotely.
A caretaker can assist an elderly in completing
tasks inside as well as outside their home environment
for instance, guiding the elderly citizens to directions
where they need to go (Firouzian et al., 2015). The
concerns about privacy and security arise when we
consider helping elderly in their home environment.
Video monitoring is often regarded as an invasion to
privacy by the elderly (Arcelus et al., 2007; Beunk,
Internet of Things Controlled Home Objects for the Elderly
245
Figure 2: IOT and elderly, based on (Gubbi et al., 2013).
2015). To ease this concern, Old Birds, a web applica-
tion prototype was implemented (Korvala and Raap-
pana, 2015). It is run by a game engine that was
originally built for remote care giving (Pulli et al.,
2012). The elderly and their surrounding environment
are presented in gaming avatars, which helps to mini-
mize the concerns of privacy, as shown in figure 3.
Figure 3: Old Birds simulation environment, (Firouzian and
Nissinen, 2013).
Currently, one of the main challenges for IOT sys-
tem designers is to design a system that can help el-
derly in everyday activities as well as be supported
by health care workers (Bassi and Horn, 2008). This
rapid shift of the need of medical services for in-house
care (Lee et al., 2013) provides the developers of IOT
based applications with a new and productive area to
deal with. Daily monitoring is enhanced by IOT thus
increasing the quality of life and health of elderly peo-
ple (Tran, 2002; Yang et al., 2014).
3 RESEARCH METHOD
This section explains the research method utilized in
this study. Systematic Literature Review (SLR) was
selected as a research method, which is a means of
identifying, evaluating, and interpreting all research
relevant to the particular area of interest or research
question (Kitchenham, 2004). SLR can be used
to verify or contradict any research hypothesis and
can also lead to new research activities (Kitchenham,
2004; Biolchini et al., 2005).
The steps followed in the SLR were based on the
guidelines for conducting a SLR (Kitchenham, 2004;
Kitchenham and Charters, 2007). SLR, in general, is
more time consuming than other traditional reviews
and provides information about the effects of some
phenomenon across a wide range of settings and em-
pirical methods (Kitchenham, 2004). The first step in
SLR is the formation of the research protocol. After
a research area or a topic is finalized, it is necessary
to create a review protocol that consists of research
questions, inclusion and exclusion criteria, quality as-
sessment criteria, keywords used to search literature,
steps for reviewing the literature, and designated syn-
thesis of the findings (Kitchenham, 2004; Biolchini
et al., 2005).
The following two research questions were se-
lected for the study:
RQ1: What are the different areas inside the house
where IOT can be applied for the elderly?
RQ2: What kind of home objects necessary for
the elderly are controlled by IOT based applica-
tions?
The inclusion and exclusion criteria used for the
review are presented in table 1. Along with those,
following quality assessment criteria were created to
select the primary studies that were as relevant to the
research questions as possible:
1. Is the application discussed in paper targeted to
old people living alone?
2. How much is IOT discussed as part of everyday
life for the user?
3. Was the application an experiment, controlled ob-
servation study, observation study without control
groups or just theoretical?
4. Does the study clarify the problems faced during
implementation?
5. Does the study provide details of the objects con-
trolled by the applications?
6. Does the study is concentrated in daily activities
inside the home or outside.The labels consists of
sequential numbers?
HEALTHINF 2017 - 10th International Conference on Health Informatics
246
Table 1: Inclusion and Exclusion criteria.
Inclusion Criteria Exclusion Criteria
it covers the areas
of both IOT and el-
derly citizens
at least one home
’thing’ is con-
trolled remotely
focus on elderly or
elderly people with
dementia
it is a journal (peer
reviewed), confer-
ence article, chap-
ters from a book or
a doctoral disserta-
tion
it is about IOT fo-
cused on all age
group
it is not in English
it is a presentation
it is a technical re-
port
it presents an in-
complete project
it is theoretical in-
formation only
it covers IOT but
not elderly assis-
tance
it covers elderly
assistance but not
IOT
The use of inclusion and exclusion criteria along
with the quality assessment criteria was completed
following the steps shown in figure 4.
Figure 4: Steps to select primary studies.
4 RESULTS
This section discusses the findings of the SLR and re-
lates the data to the research questions. Limitations
of the study and scope for extending the research are
also pointed out.
4.1 Findings
A total of 229 papers were identified in ve differ-
ent databases; Scopus, IEEE Xplore, Science Direct,
Web of Science, and ProQuest. Following the steps
presented in figure 4, a total of 25 papers were iden-
tified as the final selection of primary studies, which
makes around 11% of the initial collection of papers.
Among the 25 studies, 15 were conference proceed-
ings paper, 8 were journal articles and 2 were mono-
graphs. Each of the studies explained applications
that were developed to assist the elderly, make their
life easier,improve their health, and take care of them
in emergencies.
It was observed that most of the applications fo-
cused on the health aspect of the elderly.Body sensors
were the most implemented sensors with applications
in 11 of the 25 papers utilising it. Ambient sensors
were second, with fall detection a common area of
concern as well. Applications also dealt with provid-
ing proper medication to the elderly and maintaining
a healthy lifestyle like guiding them in exercising. Ta-
ble 2 lists the areas of the focus for the study and the
number of paper that dealt with that area.
Table 2: Areas of Concern.
Areas of Concern Number of
Papers
Kitchen 7
Health Care 22
Dining room 1
Living room 6
Bedroom 4
Bathroom 3
Shopping 1
Social connection 2
Security 4
Training and gatherings 1
Job Search 1
Exploration 1
Study room 1
Table 3 lists all the home objects that were iden-
tified in the applications dealt in the primary studies.
There were some studies that did not clearly indicate
the objects controlled by the application, as they were
denoted as smart objects or as devices in the house,
and have been excluded.
4.2 Visualization
Most of the time, caretakers may not know the en-
vironment of the elderly well enough (Ikeda et al.,
2011). With visualization of IOT objects, a caretaker
Internet of Things Controlled Home Objects for the Elderly
247
Table 3: Home objects used in IOT applications.
Objects Corresponding Paper
Kettle (Brereton et al., 2015)
Mobile phone (Dohr et al., 2010; Fortino et al., 2015; Gomes et al., 2015; Tang et al.,
2015; Laranjo et al., 2013; Panicker and Kumar, 2015)
Blood Pressure meter (Dohr et al., 2010)
Body sensors (Fortino et al., 2015; Gomes et al., 2015; Guo and Bai, 2014; Dagale et al.,
2015; Liang, 2016; Panicker and Kumar, 2015; Savola et al., 2015; Zgheib
et al., 2015; Raad et al., 2015; Sung and Chang, 2014; Chen et al., 2015)
Ambient sensors (Gomes et al., 2015; Luo et al., 2012; Boric-Lubecke et al., 2014; Wu et al.,
2013; Savola et al., 2015; Zgheib et al., 2015; Rusu et al., 2015)
Gas (Gomes et al., 2015; Lee, 2015; Cunha and Fuks, 2015)
Lights (Gomes et al., 2015; Tang et al., 2015; Cunha and Fuks, 2015; Neßelrath
et al., 2011; Zgheib et al., 2015; Rusu et al., 2015)
Exhaust (Smoke) (Gomes et al., 2015; Lee, 2015)
TV (Konstantinidis et al., 2015; Lee, 2015; Wu et al., 2013; Neßelrath et al.,
2011)
Medicine bottle/drawer (Laranjo et al., 2013; Cunha and Fuks, 2015; Neßelrath et al., 2011; Sohn
et al., 2015)
Tablets (Laranjo et al., 2013)
Camera (Lee, 2015; Rusu et al., 2015; Sohn et al., 2015)
Food drawer (Lee, 2015)
Chair/ Sofa (Liang, 2016; Wu et al., 2013; Zgheib et al., 2015)
Bed (Liang, 2016; L
´
opez-de Ipi
˜
na et al., 2010; Wu et al., 2013; Zgheib et al.,
2015)
Temperature sensor (Cunha and Fuks, 2015; Rusu et al., 2015; Sung and Chang, 2014; Chen
et al., 2015)
Humidity sensor (Cunha and Fuks, 2015; Chen et al., 2015)
Infrared sensors (Cunha and Fuks, 2015)
Noise sensors (Cunha and Fuks, 2015)
Shoes (Wu et al., 2013)
Door (Wu et al., 2013; Savola et al., 2015; Rusu et al., 2015; Chen et al., 2015)
Oven/Microwave (Wu et al., 2013; Neßelrath et al., 2011)
Electricity meter (Tang et al., 2015; Wu et al., 2013)
Kitchen Surface (Neßelrath et al., 2011)
Fridge (Neßelrath et al., 2011)
Dishwasher (Neßelrath et al., 2011)
AC (Neßelrath et al., 2011)
Switches (Zgheib et al., 2015)
Window (Rusu et al., 2015)
PC (Sohn et al., 2015)
Weight scale (Sung and Chang, 2014)
can know the status of the objects continuously and
determine the changes in the state of the object due
to any activity of the elderly. With such visualization,
presence of camera is also redundant which will en-
courage old people to accept the technology as they
regard technology, mainly video surveillance, as an
intrusion to their privacy (Arcelus et al., 2007).
Visualization is a method to infer new knowl-
edge from collected information to get a comprehen-
sive view of the space of interest (Gershon and Eick,
1997). The home objects from table 3 were thus uti-
lized to vision a scenario in the day of an elderly per-
son. This visualization is intended to showcase an el-
derly person in different areas of the house and show
different IOT enabled home objects that they have
to deal with for their daily activities. The areas of
the house where elderly require assistance from the
caretakers were selected as: bedroom, living room,
kitchen, dining room, and bathroom.
The visualization will help the caretaker to deter-
HEALTHINF 2017 - 10th International Conference on Health Informatics
248
Figure 5: Visualization of different areas of the house.
mine the location of the elderly in the house and ob-
serve their actions. The caretaker can monitor the in-
take of medicine by analyzing weight of the medicine
pill bottle, and provide notifications via smart phone
or TV to take the medicine when necessary. Also, am-
bient sensors are enabled across all the rooms of the
house to determine sudden emergencies like falling
down. Wearable sensors will help to continuously
monitor the state of health of the elderly and take ac-
tion in case of sudden bodily changes. The home ob-
jects that are controlled by the above mentioned sce-
nario are listed in table 4.
Table 4: Home objects in the visualized scenario.
Bed Lamp Mobile
Pill Bottle Door/Windows Chair
Stove Dishwasher Sink
Kettle Fridge TV
Food Cabinet Table Sofa
4.3 Limitation and Future Scope
The main focus of the study is limited within the
perimeters of the house of the elderly. The research
can be extended by including the applications that are
designed to assist elderly people outside their home.
Since areas for use of IOT is quite large, future re-
search can be done by including applications that have
been designed not just for the elderly but for people
of all age group. This will help to determine various
other areas of concerns and home objects.
The data from SLR indicates that application de-
velopers consider health care as the major area of con-
cern. For future applications, not just health care,
but other aspects such as security can be integrated
into the existing system, as shown in the visualiza-
tion section. Also, there is a need of an IOT appli-
cation that helps not only assisting when necessary
but also constantly monitoring different parameters of
their health. For e.g. a caretaker can monitor stress
level or heart beat rate of an elderly while giving them
instructions on how to cook a meal. The data from
SLR and our visualization ideas both can be utilized
to create a simulation of the home environment of the
elderly.
The inclusion of scientific studies only in the re-
view process leaves out many newspaper articles,
electronic sources and other archives. It can be possi-
ble that all the IOT enabled applications designed for
the elderly might not have been discussed in scien-
tific literature. Future researchers are encouraged to
include other sources as well, to broaden the range of
application search.
5 CONCLUSION
The main contribution of this study is to provide the
information about existing applications for the elderly
in the context of their areas of concern and home ob-
jects controlled by them. The aim is also to visualize
a new scenario of IOT enabled home environment for
the elderly. Existing research have either focused on
IOT, or some particular areas like health care or so-
cializing. The visualization scenario integrates differ-
ent areas of concern for the elderly and provide some
data for the researchers as well as developers.
This study dealt with in-house environment only.
Since elderly people spend most of their time inside
their house, it is necessary to know about the objects
they use regularly in order to create an autonomous
environment for them. The data from SLR can be fur-
ther utilized to develop new applications to improve
quality of life and health of the elderly inside their
home environment. These applications can help to
assist elderly in their daily activities through techno-
logical assistance and also monitor them regularly.
The study also presents a 3D visualization of a
safe and secure living environment across different ar-
eas of the house including the home objects. This can
be utilized by application developers as a baseline to
develop IOT based applications for the elderly. The
visualized scenario is helpful for caretakers in moni-
toring and assisting the elderly.
Internet of Things Controlled Home Objects for the Elderly
249
REFERENCES
Arcelus, A., Jones, M. H., Goubran, R., and Knoefel, F.
(2007). Integration of smart home technologies in a
health monitoring system for the elderly. In Advanced
Information Networking and Applications Workshops,
2007, AINAW’07. 21st International Conference on,
volume 2, pages 820–825. IEEE.
Atzori, L., Iera, A., and Morabito, G. (2010). The internet of
things: A survey. Computer networks, 54(15):2787–
2805.
Bassi, A. and Horn, G. (2008). Internet of things in 2020:
A roadmap for the future. European Commission: In-
formation Society and Media.
Beunk, N. (2015). Visualize my data! : translating smart
home sensor data into relevant feedback for elderly,
informal caregivers and formal caregivers.
Biolchini, J., Mian, P. G., Natali, A. C. C., and Travas-
sos, G. H. (2005). Systematic review in software en-
gineering. System Engineering and Computer Sci-
ence Department COPPE/UFRJ, Technical Report
ES, 679(05):45.
Boric-Lubecke, O., Gao, X., Yavari, E., Baboli, M., Singh,
A., and Lubecke, V. M. (2014). E-healthcare: Remote
monitoring, privacy, and security. In 2014 IEEE MTT-
S International Microwave Symposium (IMS2014),
pages 1–3. IEEE.
Brereton, M., Soro, A., Vaisutis, K., and Roe, P. (2015).
The messaging kettle: Prototyping connection over
a distance between adult children and older parents.
In Proceedings of the 33rd Annual ACM Conference
on Human Factors in Computing Systems, pages 713–
716. ACM.
Chen, Y.-H., Tsai, M.-J., Fu, L.-C., Chen, C.-H., Wu, C.-L.,
and Zeng, Y.-C. (2015). Monitoring elder’s living ac-
tivity using ambient and body sensor network in smart
home. In Systems, Man, and Cybernetics (SMC), 2015
IEEE International Conference on, pages 2962–2967.
IEEE.
Cunha, M. and Fuks, H. (2015). Ambleds collaborative
healthcare for aal systems. In Computer Supported
Cooperative Work in Design (CSCWD), 2015 IEEE
19th International Conference on, pages 626–631.
IEEE.
Dagale, H., Anand, S., Hegde, M., Purohit, N., Supreeth,
M., Gill, G. S., Ramya, V., Shastry, A., Narasimman,
S., Lohith, Y., et al. (2015). Cyphys+: A reliable
and managed cyber-physical system for old-age home
healthcare over a 6lowpan using wearable motes. In
Services Computing (SCC), 2015 IEEE International
Conference on, pages 309–316. IEEE.
Dohr, A., Modre-Osprian, R., Drobics, M., Hayn, D., and
Schreier, G. (2010). The internet of things for ambient
assisted living. ITNG, 10:804–809.
Firouzian, A., Asghar, Z., Tervonen, J., Pulli, P., and Ya-
mamoto, G. (2015). Conceptual design and imple-
mentation of indicator-based smart glasses: A naviga-
tional device for remote assistance of senior citizens
suffering from memory loss. In 2015 9th International
Symposium on Medical Information and Communica-
tion Technology (ISMICT), pages 153–156. IEEE.
Firouzian, A. and Nissinen, H. (2013). A monitoring tool
to support remote caretaking of senior citizens. In
14th International Conference on Intelligent Games
and Simulation, GAME-ON 2013.
Fortino, G., Giordano, A., Guerrieri, A., Spezzano, G., and
Vinci, A. (2015). A data analytics schema for activity
recognition in smart home environments. In Interna-
tional Conference on Ubiquitous Computing and Am-
bient Intelligence, pages 91–102. Springer.
Gershon, N. and Eick, S. G. (1997). Information visual-
ization. IEEE Computer Graphics and Applications,
17(4):29–31.
Gomes, B., Muniz, L., e Silva, F. J. d. S., R
´
ıos, L. E. T.,
and Endler, M. (2015). A comprehensive cloud-based
iot software infrastructure for ambient assisted living.
In Cloud Technologies and Applications (CloudTech),
2015 International Conference on, pages 1–8. IEEE.
Gubbi, J., Buyya, R., Marusic, S., and Palaniswami, M.
(2013). Internet of things (iot): A vision, architectural
elements, and future directions. Future Generation
Computer Systems, 29(7):1645–1660.
Guo, Y. and Bai, G. (2014). An iot architecture for home-
based elderly healthcare. In International Conference
on Management and Engineering (CME 2014), page
329. DEStech Publications, Inc.
Ikeda, S., Asghar, Z., Hyry, J., Pulli, P., Pitkanen, A.,
and Kato, H. (2011). Remote assistance using vi-
sual prompts for demented elderly in cooking. In
Proceedings of the 4th International Symposium on
Applied Sciences in Biomedical and Communication
Technologies, page 46. ACM.
Kitchenham, B. (2004). Procedures for performing sys-
tematic reviews. Keele, UK, Keele University,
33(2004):1–26.
Kitchenham, B. and Charters, S. (2007). Procedures for
performing systematic literature reviews in software
engineering. Keele University & Durham University,
UK.
Konstantinidis, E. I., Antoniou, P. E., Bamparopoulos, G.,
and Bamidis, P. D. (2015). A lightweight framework
for transparent cross platform communication of con-
troller data in ambient assisted living environments.
Information Sciences, 300:124–139.
Korvala, T. and Raappana, H. (2015). Open visual guidance
system for mobile senior citizen. Master’s thesis, Uni-
versity of Oulu, Oulu, Finland, 2015.
Laranjo, I., Macedo, J., and Santos, A. (2013). Internet
of things for medication control: E-health architec-
ture and service implementation. International Jour-
nal of Reliable and Quality E-Healthcare (IJRQEH),
2(3):1–15.
L
ˆ
e, Q., Nguyen, H. B., and Barnett, T. (2012). Smart homes
for older people: Positive aging in a digital world. Fu-
ture internet, 4(2):607–617.
Lee, R. C. (2015). The new way of social connecting for
the elderly through smart home applications. In Inter-
national Conference on HCI in Business, pages 142–
152. Springer.
Lee, S. I., Ghasemzadeh, H., Mortazavi, B., Lan, M., Al-
shurafa, N., Ong, M., and Sarrafzadeh, M. (2013). Re-
HEALTHINF 2017 - 10th International Conference on Health Informatics
250
mote patient monitoring: what impact can data analyt-
ics have on cost? In Proceedings of the 4th Confer-
ence on Wireless Health, page 4. ACM.
Liang, P.-C. (2016). Cost-effective design of real-time home
healthcare telemonitoring based on mobile cloud
computing. PhD thesis, University of Surrey.
L
´
opez-de Ipi
˜
na, D., D
´
ıaz-de Sarralde, I., and Zub
´
ıa, J. G.
(2010). An ambient assisted living platform integrat-
ing rfid data-on-tag care annotations and twitter. J.
UCS, 16(12):1521–1538.
Luo, X., Liu, T., Liu, J., Guo, X., and Wang, G. (2012). De-
sign and implementation of a distributed fall detection
system based on wireless sensor networks. EURASIP
Journal on Wireless Communications and Network-
ing, 2012(1):1.
Madakam, S., Ramaswamy, R., and Tripathi, S. (2015). In-
ternet of things (iot): A literature review. Journal of
Computer and Communications, 3(05):164.
Morris, M. E., Adair, B., Miller, K., Ozanne, E., Hansen,
R., Pearce, A. J., Santamaria, N., Viega, L., Long, M.,
and Said, C. M. (2013). Smart-home technologies to
assist older people to live well at home. Journal of
aging science, 1(1):1–9.
Neßelrath, R., Haupert, J., Frey, J., and Brandherm, B.
(2011). Supporting persons with special needs in
their daily life in a smart home. In Intelligent Envi-
ronments (IE), 2011 7th International Conference on,
pages 370–373. IEEE.
Panicker, N. V. and Kumar, S. (2015). Design of a tele-
monitoring system for detecting falls of the elderly. In
Green Computing and Internet of Things (ICGCIoT),
2015 International Conference on, pages 800–803.
IEEE.
Pulli, P., Asghar, Z., Siitonen, M., Niskala, R., Leinonen,
E., PitkPitkanen, A., Hyry, J., Lehtonen, J., Kramar,
V., and Korhonen, M. (2012). Mobile augmented
teleguidance-based safety navigation concept for se-
nior citizens. In 2nd. International Conference on Ap-
plied and Theoretical Information Systems Research
(2nd. ATISR2012), pages 1–9.
Raad, M. W., Sheltami, T., and Shakshuki, E. (2015).
Ubiquitous tele-health system for elderly patients with
alzheimer’s. Procedia Computer Science, 52:685–
689.
Rusu, L., Cramariuc, B., Bent¸a, D., and Mailat, M. (2015).
Implementing bpmn 2.0 scenarios for aal@ home so-
lution. International Journal of Computers Communi-
cations & Control, 10(2):230–237.
Savola, R. M., Savolainen, P., Evesti, A., Abie, H., and Si-
hvonen, M. (2015). Risk-driven security metrics de-
velopment for an e-health iot application. In Infor-
mation Security for South Africa (ISSA), 2015, pages
1–6. IEEE.
Sohn, S. Y., Bae, M., Lee, D.-k. R., and Kim, H. (2015).
Alarm system for elder patients medication with iot-
enabled pill bottle. In Information and Communica-
tion Technology Convergence (ICTC), 2015 Interna-
tional Conference on, pages 59–61. IEEE.
Stankovic, J. A. (2014). Research directions for the internet
of things. IEEE Internet of Things Journal, 1(1):3–9.
Sung, W.-T. and Chang, K.-Y. (2014). Health parameter
monitoring via a novel wireless system. Applied Soft
Computing, 22:667–680.
Tang, L. Z. W., Ang, K. S., Amirul, M., Yusoff, M. B. M.,
Tng, C. K., Alyas, M. D. B. M., Lim, J. G., Kyaw,
P. K., and Folianto, F. (2015). Augmented reality con-
trol home (arch) for disabled and elderlies. In In-
telligent Sensors, Sensor Networks and Information
Processing (ISSNIP), 2015 IEEE Tenth International
Conference on, pages 1–2. IEEE.
Touhy, T. A. and Jett, K. F. (2013). Ebersole & Hess’ To-
ward Healthy Aging: Human Needs and Nursing Re-
sponse. Elsevier Health Sciences.
Tran, B. Q. (2002). Home care technologies for promot-
ing successful aging in elderly populations. In En-
gineering in Medicine and Biology, 2002. 24th An-
nual Conference and the Annual Fall Meeting of the
Biomedical Engineering Society EMBS/BMES Con-
ference, 2002. Proceedings of the Second Joint, vol-
ume 3, pages 1898–1899. IEEE.
Vardoulakis, L. P., Ring, L., Barry, B., Sidner, C. L., and
Bickmore, T. (2012). Designing relational agents as
long term social companions for older adults. In In-
ternational Conference on Intelligent Virtual Agents,
pages 289–302. Springer.
Williams, D., Ahamed, S. I., and Chu, W. (2014). Designing
interpersonal communication software for the abilities
of elderly users. In Computer Software and Appli-
cations Conference Workshops (COMPSACW), 2014
IEEE 38th International, pages 282–287. IEEE.
Wu, Q., Shen, Z., Leungy, C., Zhang, H., Cai, Y., Miao,
C., et al. (2013). Internet of things based data driven
storytelling for supporting social connections. In
Green Computing and Communications (GreenCom),
2013 IEEE and Internet of Things (iThings/CPSCom),
IEEE International Conference on and IEEE Cy-
ber, Physical and Social Computing, pages 383–390.
IEEE.
Xu, G., Ding, Y., Zhao, J., Hu, L., and Fu, X. (2013). Re-
search on the internet of things (iot). Sensors & Trans-
ducers, 160(12):463.
Yang, L., Ge, Y., Li, W., Rao, W., and Shen, W. (2014). A
home mobile healthcare system for wheelchair users.
In Computer Supported Cooperative Work in Design
(CSCWD), Proceedings of the 2014 IEEE 18th Inter-
national Conference on, pages 609–614. IEEE.
Zgheib, R., Conchon, E., et al. (2015). A semantic web-
of-things architecture for monitoring the risk of bed-
sores. In 2015 International Conference on Com-
putational Science and Computational Intelligence
(CSCI), pages 318–323. IEEE.
Internet of Things Controlled Home Objects for the Elderly
251