14,550 research outputs found
Crisis Analytics: Big Data Driven Crisis Response
Disasters have long been a scourge for humanity. With the advances in
technology (in terms of computing, communications, and the ability to process
and analyze big data), our ability to respond to disasters is at an inflection
point. There is great optimism that big data tools can be leveraged to process
the large amounts of crisis-related data (in the form of user generated data in
addition to the traditional humanitarian data) to provide an insight into the
fast-changing situation and help drive an effective disaster response. This
article introduces the history and the future of big crisis data analytics,
along with a discussion on its promise, challenges, and pitfalls
Big data analytics:Computational intelligence techniques and application areas
Big Data has significant impact in developing functional smart cities and supporting modern societies. In this paper, we investigate the importance of Big Data in modern life and economy, and discuss challenges arising from Big Data utilization. Different computational intelligence techniques have been considered as tools for Big Data analytics. We also explore the powerful combination of Big Data and Computational Intelligence (CI) and identify a number of areas, where novel applications in real world smart city problems can be developed by utilizing these powerful tools and techniques. We present a case study for intelligent transportation in the context of a smart city, and a novel data modelling methodology based on a biologically inspired universal generative modelling approach called Hierarchical Spatial-Temporal State Machine (HSTSM). We further discuss various implications of policy, protection, valuation and commercialization related to Big Data, its applications and deployment
Storage Solutions for Big Data Systems: A Qualitative Study and Comparison
Big data systems development is full of challenges in view of the variety of
application areas and domains that this technology promises to serve.
Typically, fundamental design decisions involved in big data systems design
include choosing appropriate storage and computing infrastructures. In this age
of heterogeneous systems that integrate different technologies for optimized
solution to a specific real world problem, big data system are not an exception
to any such rule. As far as the storage aspect of any big data system is
concerned, the primary facet in this regard is a storage infrastructure and
NoSQL seems to be the right technology that fulfills its requirements. However,
every big data application has variable data characteristics and thus, the
corresponding data fits into a different data model. This paper presents
feature and use case analysis and comparison of the four main data models
namely document oriented, key value, graph and wide column. Moreover, a feature
analysis of 80 NoSQL solutions has been provided, elaborating on the criteria
and points that a developer must consider while making a possible choice.
Typically, big data storage needs to communicate with the execution engine and
other processing and visualization technologies to create a comprehensive
solution. This brings forth second facet of big data storage, big data file
formats, into picture. The second half of the research paper compares the
advantages, shortcomings and possible use cases of available big data file
formats for Hadoop, which is the foundation for most big data computing
technologies. Decentralized storage and blockchain are seen as the next
generation of big data storage and its challenges and future prospects have
also been discussed
Challenges of Internet of Things and Big Data Integration
The Internet of Things anticipates the conjunction of physical gadgets to the
In-ternet and their access to wireless sensor data which makes it expedient to
restrain the physical world. Big Data convergence has put multifarious new
opportunities ahead of business ventures to get into a new market or enhance
their operations in the current market. considering the existing techniques and
technologies, it is probably safe to say that the best solution is to use big
data tools to provide an analytical solution to the Internet of Things. Based
on the current technology deployment and adoption trends, it is envisioned that
the Internet of Things is the technology of the future, while to-day's
real-world devices can provide real and valuable analytics, and people in the
real world use many IoT devices. Despite all the advertisements that companies
offer in connection with the Internet of Things, you as a liable consumer, have
the right to be suspicious about IoT advertise-ments. The primary question is:
What is the promise of the Internet of things con-cerning reality and what are
the prospects for the future.Comment: Proceedings of the International Conference on International
Conference on Emerging Technologies in Computing 2018 (iCETiC '18), 23rd
-24th August, 2018, at London Metropolitan University, London, UK, Published
by Springer-Verla
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