Journal of Information Processing Systems

Korea Information Processing Society (한국정보처리학회)
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Heuristic and Statistical Prediction Algorithms Survey for Smart Environments

  • Malik, Sehrish (Dept. of Computer Engineering, Jeju National University) ;
  • Ullah, Israr (Dept. of Computer Engineering, Jeju National University) ;
  • Kim, DoHyeun (Dept. of Computer Engineering, Jeju National University) ;
  • Lee, KyuTae (Division of Information and Communication Engineering, Kongju National University)
  • Received : 2018.12.31
  • Accepted : 2019.07.31
  • Published : 2020.10.31
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Abstract

There is a growing interest in the development of smart environments through predicting the behaviors of inhabitants of smart spaces in the recent past. Various smart services are deployed in modern smart cities to facilitate residents and city administration. Prediction algorithms are broadly used in the smart fields in order to well equip the smart services for the future demands. Hence, an accurate prediction technology plays a vital role in the smart services. In this paper, we take out an extensive survey of smart spaces such as smart homes, smart farms and smart cars and smart applications such as smart health and smart energy. Our extensive survey is based on more than 400 articles and the final list of research studies included in this survey consist of 134 research papers selected using Google Scholar database for period of 2008 to 2018. In this survey, we highlight the role of prediction algorithms in each sub-domain of smart Internet of Things (IoT) environments. We also discuss the main algorithms which play pivotal role in a particular IoT subfield and effectiveness of these algorithms. The conducted survey provides an efficient way to analyze and have a quick understanding of state of the art work in the targeted domain. To the best of our knowledge, this is the very first survey paper on main categories of prediction algorithms covering statistical, heuristic and hybrid approaches for smart environments.

Keywords

References

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