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DeepThink IoT: The Strength of Deep Learning in Internet of Things

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Abstract

The integration of Deep Learning (DL) and the Internet of Things (IoT) has revolutionized technology in the twenty-first century, enabling humans and machines to perform tasks more efficiently. The combination of DL and the IoT has resulted in significant advancements in technology by improving the efficiency, security, and user experience of IoT devices and systems. The integration of DL and IoT offers several benefits, including improved data processing and analysis capabilities, the ability for IoT devices to learn from data and adapt to changing conditions, and the early detection of system malfunctions and potential security breaches. This survey paper provides a comprehensive overview of the impact of DL on IoT, including an analysis of sensor data to detect patterns and make predictions, and the implications for various industries such as healthcare, manufacturing, agriculture, and smart cities. The survey paper covers topics such as DL models, frameworks, IoT connectivity terminologies, IoT components, IoT service-oriented architecture, IoT applications, the role of DL in IoT, and challenges faced by DL in IoT. The study also presents quantitative achievements that highlight the potential impact of IoT and DL in environmental contexts such as precision farming and energy consumption. Overall, the survey paper provides an excellent resource for researchers interested in exploring the potential of IoT and DL in their field.

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Authors and Affiliations

  1. School of Computing, Indian Institute of Information Technology Una, Una, India

    Divyansh Thakur & Jaspal Kaur Saini

  2. Plaksha University, Mohali, India

    Srikant Srinivasan

Authors
  1. Divyansh Thakur
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  2. Jaspal Kaur Saini
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  3. Srikant Srinivasan
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DT wrote the manuscript. JKS and SS provided the relevant information and ideas. All the authors reviewed the manuscript.

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Correspondence to Divyansh Thakur.

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Thakur, D., Saini, J.K. & Srinivasan, S. DeepThink IoT: The Strength of Deep Learning in Internet of Things. Artif Intell Rev 56, 14663–14730 (2023). https://doi.org/10.1007/s10462-023-10513-4

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