Intelligence in Embedded Systems: Overview and Applications

  • Paul D. Rosero-MontalvoEmail author
  • Vivian F. López Batista
  • Edwin A. Rosero
  • Edgar D. Jaramillo
  • Jorge A. Caraguay
  • José Pijal-Rojas
  • D. H. Peluffo-Ordóñez
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 880)


The use of electronic systems and devices has become widely spread and is reaching several fields as well as indispensable for many daily activities. Such systems and devices (here termed embedded systems) are aiming at improving human beings’ quality of life. To do so, they typically acquire users’ data to adjust themselves to different needs and environments in an adequate fashion. Consequently, they are connected to data networks to share this information and find elements that allow them to make the appropriate decisions. Then, for practical usage, their computational capabilities should be optimized to avoid issues such as: resources saturation (mainly memory and battery). In this line, machine learning offers a wide range of techniques and tools to incorporate “intelligence” into embedded systems, enabling them to make decisions by themselves. This paper reviews different data storage techniques along with machine learning algorithms for embedded systems. Its main focus is on techniques and applications (with special interest in Internet of Things) reported in literature about data analysis criteria to make decisions.


Decision making Embedded systems Internet of things Machine learning 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Paul D. Rosero-Montalvo
    • 1
    • 2
    Email author
  • Vivian F. López Batista
    • 1
  • Edwin A. Rosero
    • 2
  • Edgar D. Jaramillo
    • 2
  • Jorge A. Caraguay
    • 2
  • José Pijal-Rojas
    • 3
  • D. H. Peluffo-Ordóñez
    • 4
    • 5
  1. 1.Departamento Informática y AutomáticaUniversidad de SalamancaSalamancaSpain
  2. 2.Universidad Técnica del NorteIbarraEcuador
  3. 3.Intituto Tecnológico Superior 17 de JulioIbarraEcuador
  4. 4.Yachay TechUrcuquíEcuador
  5. 5.Corporación Universitaria Autónoma de NariñoPastoColombia

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