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Big Data and Cognitive Computing, Volume 5, Issue 1

2021 March - 15 articles

Cover Story: Traditional IoT using Wi-Fi connectivity has inherent compatibility issues. Seamless integration among IoT devices is required to offer smart data-driven sensor controls and insightful user decisions. When information collected by one device is shared with others non-intrusively and intelligently, user acceptance becomes achievable for a smart automation of the future. This research work factors in the optimisation considerations of big data and machine learning approaches to propose a novel methodology for modelling a non-intrusive smart automation system. To validate it, we developed a prototype of our model to uniquely combine personalisation using an IoT hub implementation in a contemporary home environment. A real-time smart home automation use case was demonstrated by employing our model in big data processing and smart analytics via frameworks such as Apache Spark, Apache NiFi and FB-Prophet in public cloud platforms. View this pape

Articles (15)

  • Article
  • Open Access
31 Citations
11,656 Views
16 Pages

ParlTech: Transformation Framework for the Digital Parliament

  • Dimitris Koryzis,
  • Apostolos Dalas,
  • Dimitris Spiliotopoulos and
  • Fotios Fitsilis

Societies are entering the age of technological disruption, which also impacts governance institutions such as parliamentary organizations. Thus, parliaments need to adjust swiftly by incorporating innovative methods into their organizational culture...

  • Article
  • Open Access
5 Citations
5,445 Views
20 Pages

Nowadays, due to the extensive use of information networks in a broad range of fields, e.g., bio-informatics, sociology, digital marketing, computer science, etc., graph theory applications have attracted significant scientific interest. Due to its a...

  • Article
  • Open Access
13 Citations
7,315 Views
16 Pages

Knowledge processing is an important feature of intelligence in general and artificial intelligence in particular. To develop computing systems working with knowledge, it is necessary to elaborate the means of working with knowledge representations (...

  • Article
  • Open Access
36 Citations
12,684 Views
18 Pages

Big data have become a global strategic issue, as increasingly large amounts of unstructured data challenge the IT infrastructure of global organizations and threaten their capacity for strategic forecasting. As experienced in former massive informat...

  • Article
  • Open Access
6 Citations
7,460 Views
17 Pages

A Network-Based Analysis of a Worksite Canteen Dataset

  • Vincenza Carchiolo,
  • Marco Grassia,
  • Alessandro Longheu,
  • Michele Malgeri and
  • Giuseppe Mangioni

The provision of wellness in workplaces gained interest in recent decades. A factor that contributes significantly to workers’ health is their diet, especially when provided by canteen services. The assessment of such a service involves questions as...

  • Article
  • Open Access
52 Citations
7,681 Views
21 Pages

In quality evaluation (QE) of the industrial production field, infrared thermography (IRT) is one of the most crucial techniques used for evaluating composite materials due to the properties of low cost, fast inspection of large surfaces, and safety....

  • Review
  • Open Access
119 Citations
25,718 Views
40 Pages

IoT Technologies for Livestock Management: A Review of Present Status, Opportunities, and Future Trends

  • Bernard Ijesunor Akhigbe,
  • Kamran Munir,
  • Olugbenga Akinade,
  • Lukman Akanbi and
  • Lukumon O. Oyedele

The world population currently stands at about 7 billion amidst an expected increase in 2030 from 9.4 billion to around 10 billion in 2050. This burgeoning population has continued to influence the upward demand for animal food. Moreover, the managem...

  • Article
  • Open Access
4 Citations
5,036 Views
20 Pages

This paper introduces a novel approach for storing Resource Description Framework (RDF) data based on the possibilities of Natural Language Addressing (NLA) and on a special NLA basic structure for storing Big Data, called “NLA-bit”, which is aimed t...

  • Article
  • Open Access
2 Citations
4,728 Views
15 Pages

This paper aims to describe how pattern recognition and scene analysis may with advantage be viewed from the perspective of the SP system (meaning the SP theory of intelligence and its realisation in the SP computer model (SPCM), both described in an...

  • Article
  • Open Access
34 Citations
11,153 Views
21 Pages

Big Data and Personalisation for Non-Intrusive Smart Home Automation

  • Suriya Priya R. Asaithambi,
  • Sitalakshmi Venkatraman and
  • Ramanathan Venkatraman

With the advent of the Internet of Things (IoT), many different smart home technologies are commercially available. However, the adoption of such technologies is slow as many of them are not cost-effective and focus on specific functions such as ener...

  • Article
  • Open Access
9 Citations
6,960 Views
21 Pages

The outbreak of the COVID-19 led to a burst of information in major online social networks (OSNs). Facing this constantly changing situation, OSNs have become an essential platform for people expressing opinions and seeking up-to-the-minute informati...

  • Article
  • Open Access
32 Citations
7,847 Views
16 Pages

Structured data on customer feedback is becoming more costly and timely to collect and organize. On the other hand, unstructured opinionated data, e.g., in the form of free-text comments, is proliferating and available on public websites, such as soc...

  • Review
  • Open Access
129 Citations
20,480 Views
24 Pages

Every year, plant diseases cause a significant loss of valuable food crops around the world. The plant and crop disease management practice implemented in order to mitigate damages have changed considerably. Today, through the application of new info...

  • Review
  • Open Access
260 Citations
30,002 Views
24 Pages

A Review of Local Outlier Factor Algorithms for Outlier Detection in Big Data Streams

  • Omar Alghushairy,
  • Raed Alsini,
  • Terence Soule and
  • Xiaogang Ma

Outlier detection is a statistical procedure that aims to find suspicious events or items that are different from the normal form of a dataset. It has drawn considerable interest in the field of data mining and machine learning. Outlier detection is...

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Big Data Cogn. Comput. - ISSN 2504-2289