IEEE 7th World Forum on Internet of Things

July 12, 2021   -  July 14, 2021


Progressing the future of the Internet of Things (IoT) requires solving key fundamental challenges in computing and information processing. Today, IoT systems enable collecting billions of bits of information from various sensors, devices, and systems. The collected information could be valuable for various markets. Processing the information requires huge computing power. High-performance computing (HPC) may empower artificial intelligence (AI) for producing results and findings that are way beyond what we have witnessed. Furthermore, IoT data analytics platforms that provide easy use of machine learning models (e.g., deep learning) can essentially transform the way businesses operate through data-driven insights.

While IoT and AI offer various benefits to societies, due to larger scales, more complex models, and increased data volumes, the existing challenges of computing and information processing are amplified. These challenges include the deployment of sensors, data collection, communication, and data analytics. To address these challenges, there has been a vast amount of research and development work in the last decade. The work in fields such as high-performance computing, big data analytics, cloud computing, and edge/fog computing can be considered in this context. In addition to those, In addition to the existing challenges, new challenges arise. Processing IoT data, sharing data securely and transparently, creating insights, as well as data privacy are among such key challenges. IoT data analytics platforms aim to solve these problems of information processing.

In this topical area track, we focus on the advancements as well as challenges of the high-performance computing and IoT data analytics platforms. In this context, our topics will include but are not limited to:

  • – High-performance computing
  • – High-performance software systems/operating systems
  • – Network virtualization
  • – IoT platforms
  • – Data analytics using AI and ML methods
  • – Open data markets
  • – Cloud computing
  • – Edge/fog computing
  • – IoT data privacy and security
  • – Smart cities/smart mobility
  • – Smart industry

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