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1701284PublishedVol 2 · Issue 12

Edge-to-Cloud Intelligence: Enhancing IoT Devices with Machine Learning and Cloud Computing

Satyanarayan Kanungo

Subject area: Science,Engineering and Technology  ·  Area of research: Machine Learning and Cloud Computing

Abstract

The rapid growth of the Internet of Things (IoT) has exponentially increased the number of connected devices that generate large amounts of data. Leveraging advanced technologies such as machine learning and cloud computing is key to generating meaningful insights and enabling intelligent decision-making. This article describes the concept of edge-to-cloud intelligence, which combines edge and cloud computing paradigms to improve the capabilities of IoT devices. Explore the benefits, challenges, and considerations of edge computing, machine learning, and cloud computing in the context of IoT. Additionally, we are exploring the integration of these technologies to create a smart and efficient IoT ecosystem. This paper highlights the critical role of edge computing in enabling real-time analysis and decision-making at the edge while leveraging the power of cloud resources for advanced analytics, scalability, and storage. We discuss various use cases and examples of edge-to-cloud intelligence implementation and address challenges related to scalability, security, and privacy. Finally, we consider new trends and future directions in this field. By leveraging intelligence from the edge to the cloud, IoT devices can realize their full potential, enabling innovative applications in areas such as healthcare, manufacturing, transportation, and smart cities, resulting in increased efficiency. , reliability, and user experience.

Keywords

Edge-to-Cloud Intelligence, Internet of Things (IoT), Machine Learning, Cloud Computing, Edge Computing, IoT

How to cite this paper

Satyanarayan Kanungo "Edge-to-Cloud Intelligence: Enhancing IoT Devices with Machine Learning and Cloud Computing" Iconic Research And Engineering Journals Volume 2 Issue 12 2019 Page 238-245
Satyanarayan Kanungo "Edge-to-Cloud Intelligence: Enhancing IoT Devices with Machine Learning and Cloud Computing" Iconic Research And Engineering Journals, vol. 2, no. 12, Jun. 2019
Satyanarayan Kanungo (2019). Edge-to-Cloud Intelligence: Enhancing IoT Devices with Machine Learning and Cloud Computing. Iconic Research And Engineering Journals, 2(12).
Satyanarayan Kanungo "Edge-to-Cloud Intelligence: Enhancing IoT Devices with Machine Learning and Cloud Computing" Iconic Research And Engineering Journals, vol. 2, no. 12, Jun. 2019.
@article{1701284,
      author = {Satyanarayan Kanungo},
      title = {Edge-to-Cloud Intelligence: Enhancing IoT Devices with Machine Learning and Cloud Computing},
      journal = {Iconic Research And Engineering Journals},
      year = {2019},
      volume = {2},
      number = {12},
      pages = {238-245},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/17012841.pdf},
      abstract = {The rapid growth of the Internet of Things (IoT) has exponentially increased the number of connected devices that generate large amounts of data. Leveraging advanced technologies such as machine learning and cloud computing is key to generating meaningful insights and enabling intelligent decision-making. This article describes the concept of edge-to-cloud intelligence, which combines edge and cloud computing paradigms to improve the capabilities of IoT devices. Explore the benefits, challenges, and considerations of edge computing, machine learning, and cloud computing in the context of IoT. Additionally, we are exploring the integration of these technologies to create a smart and efficient IoT ecosystem. This paper highlights the critical role of edge computing in enabling real-time analysis and decision-making at the edge while leveraging the power of cloud resources for advanced analytics, scalability, and storage. We discuss various use cases and examples of edge-to-cloud intelligence implementation and address challenges related to scalability, security, and privacy. Finally, we consider new trends and future directions in this field. By leveraging intelligence from the edge to the cloud, IoT devices can realize their full potential, enabling innovative applications in areas such as healthcare, manufacturing, transportation, and smart cities, resulting in increased efficiency. , reliability, and user experience.},
      keywords = {Edge-to-Cloud Intelligence, Internet of Things (IoT), Machine Learning, Cloud Computing, Edge Computing, IoT},
      month = {June},
  }