Artificial intelligence of things

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The Artificial Intelligence of Things (AIoT) is the combination of Artificial intelligence (AI) technologies with the Internet of things (IoT) infrastructure to achieve more efficient IoT operations, improve human-machine interactions and enhance data management and analytics.[1][2][3]

In 2018, KPMG published a foresight study on the future of AI including scenarios until 2040.[4] The analysts describe a scenario in detail where a community of things would see each device also contain its own AI that could link autonomously to other AIs to, together, perform tasks intelligently. Value creation would be controlled and executed in real-time using swarm intelligence.

In the AIoT an important facet is AI being done on some Thing. In it's purest form this involves performing the AI on the device, i.e. at the edge or Edge Computing, with no need for external connections. There is no need for an Internet in AIoT, it is an evolution of the concept of the IoT and that is where the comparison ends.

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References[]

  1. ^ Ghosh, Iman (12 August 2020). "AIoT: When Artificial Intelligence Meets the Internet of Things". Visual Capitalist. Retrieved 22 September 2020.
  2. ^ Lin, Yu-Jin; Chuang, Chen-Wei; Yen, Chun-Yueh; Huang, Sheng-Hsin; Huang, Peng-Wei; Chen, Ju-Yi; Lee, Shuenn-Yuh (March 2019). "Artificial Intelligence of Things Wearable System for Cardiac Disease Detection". 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS): 67–70. doi:10.1109/AICAS.2019.8771630. Retrieved 22 September 2020.
  3. ^ Chu, William Cheng-Chung; Shih, Chihhsiong; Chou, Wen-Yi; Ahamed, Sheikh Iqbal; Hsiung, Pao-Ann (November 2019). "Artificial Intelligence of Things in Sports Science: Weight Training as an Example". Computer. 52 (11): 52–61. doi:10.1109/MC.2019.2933772. ISSN 1558-0814. Retrieved 22 September 2020.
  4. ^ Rethinking the value chain. A study on AI, humanoids and robots - Artificial Intelligence: Possible business application and development scenarios to 2040 (Authors: Angelika Huber-Straßer, Marcus Schüller, Nils Müller, Heiko von der Gracht, Petra Lichtenau, Hannah M. Zühlke). KPMG, 2018, accessed 01 August 2021 via researchgate.


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