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Perera, Charith, Liu, Chi Harold and Jayawardena, Srimal 2015. The emerging Internet of Things
marketplace from an industrial perspective: a survey. IEEE Transactions on Emerging Topics in
Computing 3 (4) , pp. 585-598. 10.1109/TETC.2015.2390034 file
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IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTING 1
The Emerging Internet of Things Marketplace From
an Industrial Perspective: A Survey
Charith Perera, Member, IEEE, Chi Harold Liu Member, IEEE , Srimal Jayawardena, Member, IEEE,
Abstract—The Internet of Things (IoT) is a dynamic global
information network consisting of internet-connected objects,
such as Radio-frequency identification (RFIDs), sensors, actu-
ators, as well as other instruments and smart appliances that
are becoming an integral component of the future internet. Over
the last decade, we have seen a large number of the IoT solutions
developed by start-ups, small and medium enterprises, large cor-
porations, academic research institutes (such as universities), and
private and public research organisations making their way into
the market. In this paper, we survey over one hundred IoT smart
solutions in the marketplace and examine them closely in order
to identify the technologies used, functionalities, and applications.
More importantly, we identify the trends, opportunities and open
challenges in the industry-based the IoT solutions. Based on the
application domain, we classify and discuss these solutions under
five different categories: smart wearable, smart home, smart,
city, smart environment, and smart enterprise. This survey is
intended to serve as a guideline and conceptual framework for
future research in the IoT and to motivate and inspire further
developments. It also provides a systematic exploration of existing
research and suggests a number of potentially significant research
directions.
Index Terms—Internet of things, industry solutions, smart
wearable, smart home, smart city, smart environment, smart
enterprise, IoT marketplace, IoT products
I. INTRODUCTION
The Internet of Things (IoT) is a network of
networks where, typically, a massive number of
objects/things/sensors/devices are connected through
communications and information infrastructure to provide
value-added services. The term was first coined in 1998 and
later defined as “The Internet of Things allows people and
things to be connected Anytime, Anyplace, with Anything and
Anyone, ideally using Any path/ network and Any service”
[1]. As highlighted in the definition, connectivity among the
devices is a critical functionality that is required to fulfil the
vision of the IoT. The main reasons behind such interest are
the capabilities and sophistication that the IoT will bring to
society [2]. It promises to create a world where all the objects
around us are connected to the Internet and communicate with
each other with minimal human intervention. The ultimate
goal is to create “a better world for human beings”, where
objects around us know what we like, what we want, and
what we need, and hence act accordingly without explicit
instructions [3].
This work is sponsored in part by National Natural Science Foundation of
China (Grant No.: 61300179).
Charith Perera, and Srimal Jayawardena, are with the Research School of
Computer Science, The Australian National University, Canberra, ACT 0200,
Australia. (e-mail: firstname.lastname@ieee.org)
Chi Harold Liu is with Beijing Institute of Technology, China. (e-mail:
chiliu@bit.edu.cn)
Manuscript received xxx xx, xxxx; revised xxx xx, xxxx.
There have been a number of surveys conducted in the IoT
domain. The area of the IoT has been broadly surveyed by
Atzori et al. in [2]. Bandyopadhyay et al. have surveys of
the IoT middleware solutions in [4]. Layered architecture in
industrial IoT are discussed in [5]. A similar survey focusing
on data mining techniques for the IoT are discussed in [6].
Edge mining in IoT paradigm is discussed in [7]. In contrast
to the traditional data mining, edge mining takes place on the
wireless, battery-powered, and smart sensing devices that sit at
the edge points of the IoT. The challenges in self organizing
in IoT are discussed in [8]. Atzori et al [9] have discussed
how smart objects can be transformed in to social objects.
Such transformation will allow the network to enhance the
level of trust between objects that are ‘friends’ with each
other. IoT technologies and solutions towards Smart Cities are
reviewed in [10]. Communication protocols and technologies
play a significant role in IoT. Sheng et al. [11] have survey
a protocol stack developed specifically for IoT domain by
Internet Engineering Task Force (IETF).
Internet of things: vision, applications and research chal-
lenges are discussed from a research perspective in [12],
[13]. Further, the IoT has been surveyed in a context-aware
perspective by Perera et al. [14]. A survey on facilitating
experimentally IoT research is presented by [15]. Palattella
et al. [16] have introduced a communications protocol stack
to support and standardise IoT communication. Security chal-
lenges such as general system security, network security, and
application security in the IoT are discussed in [17]. The
security issues in perception layer, network layer and appli-
cation layer in architectures have discussed in [18]. Hardware
devices, specially nano sensors and technologies, used in IoT
are surveyed in [19]. Another similar survey has been done
by Hodges et al. [20]. This paper discusses a open-source
hardware platform called .NET Gadgeteer, a rapid prototyping
platform for small electronic gadgets and embedded hardware
devices..NET Gadgeteer is coming from an industrial setting
similar to Arduino [21].
Besides the above articles, there are a number of surveys
and reviews that have been conducted by researchers around
the world in the IoT domain, from which we have hand picked
some to represent the existing body of knowledge.
As far as we know, however, no survey has focused on
IoT industry solutions. All the above-mentioned surveys have
reviewed the solutions proposed by the academic and research
community and refer to scholarly publications. In the present
paper, we review the IoT solutions that have been proposed,
designed, developed, and brought to market by industrial
organisations. These organisations range from start-ups and
small and medium enterprises to large corporations. Because
of their industrial and market-driven nature, most of the IoT
solutions in the market are not published as academic works.
arXiv:1502.00134v1 [cs.CY] 31 Jan 2015
IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTING 2
Therefore, we collected information about the solutions from
their respective web-sites, demo videos, technical specifica-
tions, and consumer reviews. Understanding how technologies
are used in the IoT solutions in the industry’s marketplace is
vital for academics, researchers, and industrialists so they can
identify trends, opportunities, industry requirements, demands,
and open research challenges. It is also critical for understand-
ing trends and open research gaps so future research directions
can be guided by them.
The present paper is organised into sections as follows:
In Section II, we evaluate and examine the functionalities
provided by each solution under the five categories identified
in the earlier section. At the end of that section, we summarise
the functionalities and highlight the major domains that are
commonly targeted by the solutions. Then, we examine the
IoT solutions from a technology and business perspective.
Hardware platforms, software platforms, additional equipment,
communication protocols, and the energy sources used by each
solution are examined in Section III. At the end of that section,
we summarise the technologies and business models used by
the IoT solutions so trends and opportunities can be identified.
In Section IV, we identify such trends using the evaluations
we conducted in the previous sections. Later, opportunities
for research and development will be assessed in Section V.
Concluding remarks will be presented in Section VI.
II. FUNCTIONALITY REVIEW OF IOT SOLUTIONS
In this section, we focus on the functionalities of the IoT
solutions. The next section discusses the technologies used by
these solutions under common themes. In both sections, our
intention is not to describe each IoT solution in detail, but to
organise them into common themes so we can identify trends
and opportunities. However, readers can use citation numbers
to track a given IoT solution throughout the paper, if desired.
Such an option allows consolidating the knowledge we have
put separately in two sections, to better understand a single
IoT solution. In Section IV, we will analyse the trends from
both the functional and the technological point of views.
A. Smart Wearable
Wearable solutions are diverse in terms of functionality.
They are designed for a variety of purposes as well as for
wear on a variety of parts of the body, such as the head, eyes,
wrist, waist, hands, fingers, legs, or embedded into different
elements of attire. In Table I, we summarise popular wearable
IoT solutions. This table includes a brief description of each
solution, context information gathered, similar solutions, and
the context-aware functionality provided by the solution. The
IoT solutions are categorised by the body part on which
the solution must be worn, as illustrated in Figure 1. In
addition to the industry IoT solutions, academic solutions
in the wearable computing area are discussed in [26], [27].
Challenges and opportunities in developing smart wearable
solutions are presented in [28].
B. Smart Home
Solutions in this category make the experience of living at
home more convenient and pleasant for the occupants. Some
smart home [54] solutions also focus on assisting elderly
Hand
(Gloves)
Finger
(Rings)
Wrist
(Watch/
Bands)
Eyes
(Glasses)
Legs
(Socks)
Foot (Shoes)
Head
(Helmet)
Body
(Cloth)
Waist
(Band)
Chest
(Band)
Fig. 1. Different body parts popularly targeted by wearable IoT solutions in
the industry market-place.
people in their daily activities and on health care monitoring
[55]. Due to the large market potential, more and more
smart home solutions are making their way into the market.
From the academic point of view, smart energy and resource
management [56], [57], human–system interaction [58], and
activity management [59], have been some of the major foci.
Platforms: Smartthings [60] is a generic platform that con-
sists of hardware devices, sensors, and software applications.
Context information is collected through sensors and injected
into applications where reasoning and action are performed
accordingly. For example, the sprinkler installed in the user’s
garden can detect rain and turn itself off to save energy. Nin-
jablocks [61] and Twine [62] provide similar functionalities.
These solutions were mainly developed to support smart home
and building domains, but they can be customised to other
domains. HomeOS [63] is a platform that supports home au-
tomation. Instead of custom hardware (e.g. a smartthings hub),
HomeOS is a software platform which can be installed on a
normal PC. As with the smartthings platform, applications can
be installed to support different context-aware functionalities
(e.g. capturing an image from a door camera and sending it
to the user when someone rings the doorbell). Lab-of-things
[64] is a platform built for experimental research. It allows
the user to easily connect hardware sensors to the software
platform and enables the collection of data and the sharing of
data, codes, and participants.
Virtual Assistance: Ubi [65] supports residents by acting as
a voice-activated computer. It can perform tasks such as audio
calendar, feed reader, podcast, voice memos, make lighting-
based notifications to indicate the occurrence of certain events,
weather, stock, email, and so on. Ubi has a microphone and
speakers. It also has sensors to monitor the environment,
such as monitoring the temperature, humidity, air pressure,
and ambient light. Netatmo [66] is an air quality monitoring
solution for smart homes. In order to determine air quality,
it collects context information from sensors such as temper-
ature, humidity, and CO2. The solution monitors the home
environment and sends an alert when the residents’ attention
is required. Meethue [67] is a bulb which can be controlled
from mobile devices. The bulb reacts to the context and can
change its colour and brightness according to user preferences,
IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTING 3
TABLE I
SUMMARY OF WEARABLE IOT SOLUTIONS
Functionalities Provided by Different wearable IoT solutions
Cloth
• Monitor respiration, body position, activity level, skin temperature, and audio of a baby using pressure, stretch, noise, and
temperature sensors, and provide notification through a smart phone regarding any situation that parents need to attend to (Baby
Monitor: RestDevice / Mimobaby [29]).
• A sleep-tracking device that uses a thin-film sensor strip placed on a mattress in combination with smart phone to help to create
a nightly rest profile. It helps to improve user’s sleep over time (Sleep Tracking: Beddit [30]).
• Jacket relieves anxiety and stress from those diagnosed with autism spectrum disorder (ASD) or attention-deficit/hyperactivity
disorder. Built-in motion sensors and pressure sensors track the frustration and activity levels of the child throughout the day
and generate custom notification alerts based on that information (Medical Assistant :MyTJacket [31]).
Waist / Chest
• Tracks posture and daily activities in real time. It provides advice on posture issues so users can improve their posture (Daily
Activity and Fitness Monitor / Medical: Lumoback [32]).
• A device that updates Twitter when a baby in the womb kicks its mother (Medical Assistant: kickbee [33]).
• A chest band that tracks heart rate, speed, distance, stress level, calories, and activity level. It allows recommended working out
within certain heart rate zones to achieve goals such as weight loss or cardiovascular improvement. (Personal Sports Assistant:
BioHarness [34]).
Wrist
• A wrist band that tracks steps taken, stairs climbed, calories burned, and hours slept, distance travelled, and quality of sleep and
provides recommendation for a healthier lifestyle (Daily Activity and Fitness Monitor: MyBasis [35], BodyMedia [36], Lark
[37]).
• Open wearable sensor platform, a wrist band that comprises number of different sensors such as pulse, blood flow sounds, blood
oxygen saturation, blood flow waveform, pulse, acceleration, type of activity, calories burned and number of steps taken, skin
temperature (Open Platform: AngelSensor [38]).
• EMBRACE+, a wrist band that connects to the user’s smartphone via Bluetooth and displays any notifications user may receive
as ambient light notifications (Personal Sports Assistant: EmbracePlus [39]).
• Electrocardiogram technology (ECG), Bluetooth connectivity and a suite of sensors are used to recognize users’ heart rhythm
uniquely and securely and continuously log into users’ nearby devices (Secure Authentication: nymi [40]).
• A watch that helps athletes to keep track of their training. Context information such as mapping, distance, speed, heart rate, and
light are collected and fused to generate athletes’ training profile (Personal Sports Assistant: Leikr [41]).
Eyes
• Sports-specific (skiing) goggles that monitor jump analytics, speed, navigation, trip recording, and peer tracking (Personal Sports
Assistant: Oakley Goggles [42]).
• A pair of glasses that consist of camera, projector, and sensors to support functionalities such as navigation calendar notification,
navigation, voice activated, voice translation, communication and so on. It also acts as an open platform where different context-
ware functionalities can be built using provided sensors and processing capabilities (Open Platform: Google Glass [43]).
Head
• Sports-specific (American football) helmet that determines when to take a player off the field and seek medical advice through
impact detection and analysis (Personal Sports Assistant: TheShockBox [44]).
• A bicycle helmet that detects a crash. If the user’s head hits the pavement (or anything hard (ice, snow, dirt)), a signal will be
sent to the smartphone automatically to generate a call for help (Emergency Accident monitor: ICEdot [45]).
Hands
• Monitor, analyze and improve golf swing through motion sensors embedded in gloves (Personal Sports Assistant: Zepp [46] )
• A ring that monitors and keeps track of the user’s heart rate (Medical Assistant: ElectricFoxy [47]).
Legs / Foot
• A sock that combines an accelerometer with textile sensors to measure steps, altitude and calories burnt. It helps runners to avoid
potentially dangerous techniques: heel striking or excessive forefoot running that could lead to back pain or Achilles ten-don
injuries. (Daily Activity and Fitness Monitor / Medical: Heapsylon [48])
• A pair of shoes that provides feedback through vibrations in an intuitive and non-obstructive way. The shoes suggest the right
direction and detect obstacles (Disability Assistance: LeChal [49])
Internal
• A small patch worn on the body working together with 1mm sensor-enabled pills and a back-end cloud service to collect and
process real-time information (e.g. heart rate, temperature, activity and rest patterns throughout the day) on the user’s medication
adherence (Medical: Proteus Digital Health [50]).
Multi
• A device that can be worn on multiple body parts tracks steps taken, stairs climbed, calories burned, and hours slept, distance
travelled, quality of sleep (Daily Activity and Fitness Monitor: Fitbit [51]).
• An ultra-small GPS unit and five in-built sensors are used to collect data and fused to tell the camera exactly the right moment
to take photos (Leisure: Autographer [52]).
• Remote monitoring system that collects data through devices that can be worn on different body parts on a patient’s physiological
conditions to support physicians (Health Monitoring: Preventice BodyGuardian [53]).
IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTING 4
time / day / season, and activity (e.g. resident enters home)
and is also sensitive to changes in the weather during the day.
Smart Objects: WeMo [68] is a Wi-Fi enabled switch that
can be used to turn electronic devices on or off from anywhere.
Context-aware schedules are also supported, where turning on
or off is performed automatically according to the time of day,
sunrise, or sunset. Tado [69] is an intelligent heating control
that uses a smartphone. It offers context-aware functionalities
such as turning down the heating when the last person leaves
the house, turning the heating back up before someone gets
home, and heats the house less when the sun is shining.
Nest [70] is a thermostat that learns what temperatures users
like and builds a context-aware personalised schedule. The
thermostat automatically turns to an energy-efficient ‘away
temperature’ when occupants leave the home. If it senses
activity, such as a friend’s coming over to water the plants,
Nest could start warming up the house. The thermostat can
be activated remotely through the Nest mobile app. Lockitron
[71] is a door lock that can be opened and closed by a phone
over the Internet. Residents can authorise family and friends
to open a given door by providing authorisation over the
Internet, so that others can use their smartphones to unlock
doors. Blufitbottle [72] is a water bottle that records drinking
habits while keeping the users healthy and hydrated. If the user
starts to fall behind with hydration, the bottle has customisable
sounds and lights to alert them.
Digital Relationships: Wheredial [73] offers a way to
make a personal connection with family members or friends.
It retrieves a person’s location from Foursquare, Google Lat-
itude, and a variety of other services. Then it rotates the
dial (like a clock) to show where the person is at a given
moment. Goodnightlamp [74] is a family of connected lamps
that let the user remotely communicate the act of coming back
home to their loved ones easily and in an ambient way by
fusing location-aware sensing. The objective of Wheredial and
Goodnightlamp is the same: helping to build and maintain
family relationships and further strengthen friendships by
mitigating the fact that the users are apart from each other.
Such solutions are extremely important in terms of social,
psychological, and mental well-being.
C. Smart City
Towns and cities accommodate one-half of the world’s
population, creating tremendous pressure on every aspect of
urban living. Cities have large concentrations of resources and
facilities [75]. The enormous pressure towards efficient city
management has triggered various Smart City initiatives by
both government and private sector businesses to invest in in-
formation and communication technologies to find sustainable
solutions to the growing problems [14]. Smart grid is one of
the domains in which academia, industry, and governments are
interested and invested significantly [76], [77].
Smart Traffic ParkSight [78] is a parking management
technology designed for cities. Context information is retrieved
through sensors (magnetometers) embedded in parking slots.
Application support is provided via location and map services
to guide drivers to convenient parking based on real-time
context analysis. Uber [79] allows users to request a ride at
any time. The company in a particular place sends a cab.
In contrast to transitional taxi services, no phone call or
pick-up location is required. A mobile application shows the
cabs close to the users and their movement in real time. A
cab can be requested by means of a single smartphone tap.
Alltrafficsolutions [80] collects traffic data through sensors and
visualises it on maps in order to provide drivers with traffic
updates. Further, it provides remote equipment management
support related to traffic control (e.g. changes in digital road
signs, speed limit boards, variable message signs (e.g. ‘event
parking’) to drivers, and changes in the brightness of digital
signs based on the context information). Streetbump [81] is
a crowd-sourcing project that helps residents to improve their
neighbourhood streets. Volunteers use the Streetbump mobile
application to collect road condition data while they drive. The
data are visualised on a map to alert residents regarding real-
time road conditions. The collected data provide governments
with real-time information with which to fix problems and
plan long-term investments.
Platforms Libelium [25] provides a platform of low-level
sensors that is capable of collecting a large amount of
context information to support different application domains
[9]. Thingworx [82] and Xively [83] are cloud-based on-
line platforms that process, analyse, and manage sensor data
retrieved through a variety of different protocols.
Resource Management SmartBelly [84] is a smart waste
management solution. It provides a sensor-embedded trash can
that is capable of real-time context analysis and alerting the
authorities when it is full and needs to be emptied. Loca-
tion information is used to plan efficient garbage collection.
Echelon [85] has developed a smart street lighting solution
transforming street-lights into intelligent, energy-efficient, re-
motely managed networks. It schedules lights to be turned
on or off and sets the dimming levels of individual lights or
groups of lights so a city can intelligently provide the right
level of lighting needed by analysing the context such as time
of day, season, or weather conditions.
Activity Monitoring Livehoods [86] offers a new way to
conceptualise the dynamics, structure, and character of a city
by analysing the social media its residents generate. This
is achieved through collecting context information such as
check-in patterns. Livehoods shows how citizens use the urban
landscape and other resources. Scenetap [87] shows real-
time info about the city’s best places. It shows the context
information of a given location such as how many people are
there, the male to female ratio, and the average age of everyone
inside. This helps users to find the best places to hang out (e.g.
cinema, bar, restaurant) at a given time and gives information
such as availability.
D. Smart Environment
Air Quality Monitoring Airqualityegg [88] is a community-
led sensor system that allows anyone to collect context in-
formation such as the carbon monoxide (CO) and nitrogen
dioxide (NO2) gas concentrations outside their home. Such
data are related to urban air pollution. Communitysensing [89]
is also an air quality monitoring system which provides both
hand-held devices and a platform to be fixed into municipal
vehicles such as street sweepers. Aircasting [90] is a platform
for recording, mapping, and sharing health and environmental
data using smartphones and custom monitoring devices. Con-
text information includes sound levels, temperature, humidity,
