Big data analytics is becoming important to process unimaginably large amounts of information and data in many applications. The typical big data analytics is Hadoop, an open-source software framework that supports data-intensive distributed applications, and the running of applications on large clusters of commodity hardware. Hadoop, that is based on the architectural framework MapReduce, collects both structured data and unstructured data, processes the collected data set in a distributed network cluster in parallel, and extracts valuable information from the processed data set within a short time. Followings illustrate some examples of patents that provide current status of the big data analytics applications.

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Big Data Applications Insights from Patents
Big data analytics is becoming important to process unimaginably large amounts of information and data in many
applications. The typical big data analytics is Hadoop, an open-source software framework that supports data-
intensive distributed applications, and the running of applications on large clusters of commodity hardware.
Hadoop, that is based on the architectural framework MapReduce, collects both structured data and unstructured
data, processes the collected data set in a distributed network cluster in parallel, and extracts valuable information
from the processed data set within a short time. Followings illustrate some examples of patents that provide current
status of the big data analytics applications.
Industrial Automation
US20140337086 illustrates a risk assessment system for industrial systems using the big data analytics in a cloud
platform. Industrial controllers and their associated I/O devices are central to the operation of modern automation
systems. These controllers interact with field devices on the plant floor to control automated processes relating to
product manufacture, material handling, batch processing, supervisory control, and applications. Industrial
controllers read input data from sensors and metering devices that provide discreet and telemetric data regarding
the states of the controlled system, and generate control outputs based on these inputs in accordance with the user-

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defined program. The risk assessment system performs the risk assessment by analysis of large and diverse sets of
data from the industrial controllers (big data analysis) in a cloud platform.

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Health Information Management System
US20140304003 illustrates a health information management system which enables analysis of patient referrals in
a medical network for the purpose of optimizing referral practices exploiting big data analytics. Currently, when a
patient sees various medical professionals over the years, there is no method for tracking recommendations,
thoughts, prescriptions, referrals, or diagnosis. By being able to properly analyze patient referral practices, insurers
and health managers are able to provide better referral service to patients, increase patient retention, and increase
operational efficiency. The health information management system can identify explicit referral activity reported
into a referral workflow system, infer referral activity not reported into the referral workflow system intent-based
clustering of medical information and generate reporting metrics from the inferred and explicit referral activity
using the big data analyzer.
Augmented Reality
Augmented Reality (AR) has applications in various areas, such as education, advertising, maintenance, marketing,
and entertainment. In the areas of maintenance and education specifically, the use of augmented reality can provide
for the transfer of knowledge at a faster rate than other traditional methods. Additionally, the use of AR can help
companies train their employees faster and better. The use of AR can also assist company employees in performing
job tasks more competently and efficiently. US20140247283 illustrates a system unifying AR and streaming video

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with big data analytics. An area that can benefit from the use of unifying AR and streaming video with big data
analytics is the maintenance of complex systems, such as aircraft maintenance. To that end, 3D or 2D graphics or
images, text, or other media can be generated such that they are overlaid on and registered with surrounding objects
in the environment. Applying AR to maintenance tasks can make it possible for users to be trained for those tasks,
and actively assisted during their performance. Use of AR can decrease the overall time of the repair, reduce errors
in the repair process, and increase the knowledge of maintenance personnel.
CRM
US20140143012A illustrates a system for providing prediction of content usage in a website based on statistically
analyzing online visitor's behavior patterns. The system uses the clustering algorithm that enables classifying
visitors into groups by analyzing the profile and navigation activities parameters of the user. The system uses the
predictive analytics that utilizes machine learning algorithms over big data to provide recommendation for further
communication or actions to be taken.
Telecom Network Management
US20150207706 illustrates the network traffic big data analytics. Telecommunication network traffic is generated
from a large amount of nodes (e.g., consumer devices, routers, servers, base stations, etc.) continuously at a very

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high speed. Network traffic analytics is fundamental and critical to understanding the behavior of the network and
optimizing the performance of the network and applications. Network traffic analytics also play an important role
in identifying attacks to the network and allowing network administrators to take appropriate security measures. To
cope with the high volume and high speed of the traffic data, big data analytics can be applied.