Database Reference
In-Depth Information
RFID technology
is a key enabler for the internet of things, be-
cause it allows the simultaneous identification of large numbers of
objects with cost-effective tags [108]. However, in practice many
other kinds of embedded sensor technology may be used for enable-
ment. Furthermore, where more sophisticated sensor information
is required about the object,
RFID
technology can only provide a
partial component of the data required for full enablement.
Social sensing
is a paradigm which refers to the interaction between
people with embedded sensor devices, which are typically mobile
phones. However, the internet of things is a more general concept,
where even mundane objects of everyday life such as refrigerators,
consumer products, televisions, or cars may be highly connected,
and may be utilized for making smarter and automated decisions.
1.1 The Internet of Things: Broader Vision
The
Internet of Things
is a vision, which is currently being built-
there is considerable diversity in its interpretation by different commu-
nities, who are involved in an inherently cross-disciplinary effort, involv-
ing sensor networking, data management and the world wide web. This
diversity is also a result of the technical breadth of the consortiums,
industries and communities which support the vision. Correspondingly,
this is also reflected in the diversity of the technologies, which are being
developed by the different communities. Nevertheless, there are numer-
ous common features across the different visions about what the internet
of things may constitute, and it is one of the goals of this paper to bring
together these visions from a data-centric perspective.
A simple and broad definition of the internet of things [41, 16] is as
follows: “
The basic idea of this concept is the pervasive presence around
us of a variety of things or objects - such as Radio-Frequency IDenti-
fication (RFID) tags, sensors, actuators, mobile phones, etc. - which,
through unique addressing schemes, are able to interact with each other
and cooperate with their neighbors to reach common goals
”. The pro-
cess of machines communicating with one another, is also referred to as
the Machine-to-Machine (M2M) paradigm. This requires tremendous
data-centric
capabilities, which is the primary medium of communica-
tion between the different entities. Therefore, the ability to securely
and privately collect, manage, index, query and process large amounts
of data is critical.
In order to enable these goals, a variety of research efforts have been
initiated supporting various aspects of these goals. Each of these visions
has a slightly different emphasis on different parts of this data-centric
