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An Investigation of the Use of Innovative Biology-Based Computational Intelligence in Ubiquitous Robotics Systems: Data Mining Perspective

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Trends in Ambient Intelligent Systems

Part of the book series: Studies in Computational Intelligence ((SCI,volume 633))

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Abstract

Sensor technologies are crucial in ambient assisted living system because they can observe, measure, and detect users’ daily activities, in the meanwhile issue warnings when parameters exceed particular thresholds. Despite their enormous supporting potential, the quantities of data generated from multiple sensor is huge (i.e., big data), because they involved everywhere, such as smart home, health-based wearable devices, and assistive robots. Generally speaking, big data can be defined as large pools of data which comes from digital pictures, videos, intelligent sensors, posts to social media sites, purchase transaction records, cell phone global positioning system signals, to name a few. During the past few years, there is a great interest both in the commercial and in the research communities around big data. Under these circumstances, data mining, whose main purpose is to extract value from mountains of datasets, is drawing a lot of people’s attention. To follow this trend, in this article, we intend to take an algorithmic point of view, i.e., applying intelligent algorithms to data, with an emphasis on the biology-based innovative computational intelligence (CI) methods. This work makes several contributions. First, it investigates a set of biology-based innovative CI algorithms which can enable a high throughput under extract from the insights of data. Second, it summarizes the core working principles of these algorithms systematically and highlights their preliminary applications in different areas of data mining. This will allow us to clearly pinpoint the intrinsic strengths of these novel algorithms, and also to define the potential further research directions. The findings of this chapter should provide useful insights into the current big data literature and be a good source for anyone who is interested in the application of CI approaches to big data and its corresponding fields.

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Authors and Affiliations

  1. Computational Intelligence, Robotics, and Cybernetics for Leveraging E-Future (CIRCLE), Department of Computer Science, School of Mathematical and Computer Sciences, Faculty of Science and Agriculture, University of Limpopo, Private Bag X1106, Sovenga, Limpopo, 0727, South Africa

    Bo Xing

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  1. Bo Xing
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Editors and Affiliations

  1. School of Engineering & Technology, Sharda University, Greater Noida, India

    Kiran Kumar Ravulakollu

  2. Computing (Ministry of Comm. and IT, Centre for Development of Advanced, Noida, India

    Mohammad Ayoub Khan

  3. (MIR Labs), Machine Intelligence Research Labs, Auburn, Washington, USA

    Ajith Abraham

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Xing, B. (2016). An Investigation of the Use of Innovative Biology-Based Computational Intelligence in Ubiquitous Robotics Systems: Data Mining Perspective. In: Ravulakollu, K., Khan, M., Abraham, A. (eds) Trends in Ambient Intelligent Systems. Studies in Computational Intelligence, vol 633. Springer, Cham. https://doi.org/10.1007/978-3-319-30184-6_6

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