Abstract— the fuzzy model will apply the decision making

Abstract— Internet of things (IoT) is an important concept in
of pervasive computing environment gradually has gained signi?cant attention over the last few years. Nowadays sensors
are expected to be attached to all the objects around us, so that they can
communicate with each other with minimum human intervention. Understanding
sensor data collected from various sensors is one of the main challenges that
the IoT would face. Different context aware system has been developed by
researchers to solve these problems, however not much of the attention is done
on understanding the context effectively. The objective of the paper is to describe
various context reasoning techniques that help to understand the context in
context-aware applications. A context reasoning and decision
making model is proposed that
will handle cooling and lighting system to save energy consumption in an office
room. The simulation is done using occupancy detection dataset. Occupancy
context in an office room is identified by using statistical machine learning
model. Further the fuzzy model will apply the decision
making algorithm, to make the decision based on the identi?ed context
and CO2 level in the room to control the cooling and lighting system. Experimental
results demonstrate the feasibility of the proposed model and give a hope of
working on real-time data in future.


Keywords—Internet of Things (IoT);
Resource Description Framework (RDF); Web Ontology Language (OWL); Machine learning(ML);

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  Internet of Things (IoT) is a rapidly growing
technology and has gained huge popularity in last few years causing tremendous
growth in number of sensors deployed around us. Gartner report   predicts that billions of connected things
are already in use in 2015 and the number will reach 25 billion in just a few
short years. These sensors generate massive amount of data that needs to be
understood as it contains valuable information. Context-aware computing has
proven to be successful in understanding sensor data 4. Context-awareness plays a crucial role in Internet of Things and is
an important concept of pervasive computing application. There is a growing
need of using context-awareness as a technique for developing smart,
intelligent device that are flexible, adaptable, and capable of acting
autonomously on behalf of user. Devices, services and agents in pervasive
computing environments must be aware of their contexts and automatically adapt
to their changing context. Usually sensors are connected directly to
applications   that use traditional based
approach and become infeasible. In order to tackle the issue signi?cant amounts
of middleware solutions are introduced by researchers, however an ideal middleware solution addressing
the issue carefully is yet to be designed 4. By improving the mechanism for
understanding the context will provide more optimized and personalized services thereby increasing satisfaction of
the user. Different context reasoning technique has been developed by
researchers to solve this problems however there is a lot of scope of improvement as context changes from
situation to situation and is not fixed.


 In recent years, a
variety of context-aware applications have been developed however, these
application have not yet made the transition out of the laboratory and into
daily use. Two important tools to deal with these smart environments are
context modeling and context awareness. In Context modeling, context reasoning
is an important instrument to deal with contexts and how they are collected,
organized and represented whereas context awareness signifies for reasoning
about the context Thus realizing applications which can be managed and used in
pervasive environments is still a complex task. One of the major issues is
addressing uncertainty, which can be caused due to inaccuracy, ambiguity or
incompleteness of sensed context. Misinterpretation of context information can
lead to incorrect decision .The survey introduces and explains the fundamental
terms of context, context awareness and different reasoning approaches used by
researchers to identify the context.