IEEE Consumer Electronics Magazine - April 2017 - 65

platform. The choice for selecting an optimal software platform will be driven by the instruments provided, specifically,
the IDE for programming and the API available for access of
data and notifications.
Furthermore, the efficiency of data management tools, such
as desktop and mobile applications, dashboards, and the like,
also makes the particular choice significant. Finally pricing,
community support, and available documentation should also
be considered in selecting a software platform. Table 4 compares IoT software platforms that are compatible with and support the various IoT hardware platforms discussed above and
are either open source or offer free accounts.

GENERIC API DEVELOPMENT
In this era of sensor technology, scientific advancements have
led to the miniaturization of sensors, which are available in
various specifications and forms. One cannot imagine any
smart IoT device or application without sensors. Because of
the rapid increase in IoT sensors, data collection has become
a tedious task for the DIYer. Putting sensor data on the web
has so far been a slow and ad-hoc process. Moreover, hardware manufacturers are flooding the market with different
platforms and sensors that may be incompatible. Dealing

The ultimate goal of the IoT is
to make all objects in homes and
offices smart, so they can be
controlled from anywhere in
the world.
with this poses challenges in application and product development, requiring substantial technical expertise that may be
more costly than the actual end product.
Another cost factor, one that can also slow the product
development process, involves different APIs for different
sensors. The independence to use any platform and sensor
technology can be achieved by following a generic approach
that reduces the work of data integration.
Possible solutions like the Semantic Sensor Network Ontology of the World Wide Web Consortium [46] have been established during the past decade. The latter emphasizes generic
sensor API development, which in turn is increasing the speed
of new sensors' web exposure and implementation process

Table 3. A comparison of boards and platforms in terms of connectivity.

aDC/DaC

Ethernet

Wi-Fi

Bluetooth

Camera
Interface

onboard
sensors
and Display

Features

gPIo

PWm analog
Pins Pins

SparkFun
Blynk Board

10 b

IEEE 802.11 b/g/n

Temperature
and humidity sensor,
RGB LED

Arduino
Yun

10 b

IEEE 802.3
10/100 Mb/s

IEEE 802.11 b/g/n

Raspberry
Pi 3

IEEE 802.3
10/100 Mb/s

IEEE 802.11 b/g/n

Bluetooth
4.1 LE

CSI

cloudBit

IEEE 802.11 b/g/n

Photon

12-b ADC,
12-b DAC

IEEE 802.11 b/g/n

Yes

Real-time
clock

BeagleBone
Black

12-b ADC

IEEE 802.3
10/100 Mb/s

Pinoccio

10-b ADC

Wi-Fi Backpack
IEEE 802.11 b/g/n

Temperature
sensor, RGB
LED

UDOO

12-ADC,
2-DAC

12-b ADC,
12-b DAC

IEEE 802.3
10/100 Mb/s

IEEE 802.11 b/g/n

CSI

Artik 10
Samsung

Six-channel

IEEE 802.11 b/g/n

Bluetooth
4.1 LE

1x two-lane
MIPI CSI, 1x
four-lane
MIPI CSI up
to 23 MP still,
8 MP @ 30 fps

fps: frames per second.

APRIL 2017

IEEE ConsumEr ElECtronICs magazInE

Table of Contents for the Digital Edition of IEEE Consumer Electronics Magazine - April 2017