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Towards Artificial General Intelligence (AGI) in the Internet of Things (IoT): Opportunities and Challenges

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arxiv 2309.07438 v1 pith:JXVM6XAZ submitted 2023-09-14 cs.AI cs.NI

classification cs.AIcs.NI
keywords artificialintelligencechallengescriticalgeneralinternetopportunitiesresearch
verification ladder T0 review T1 audit T2 compute T3 formal
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Artificial General Intelligence (AGI), possessing the capacity to comprehend, learn, and execute tasks with human cognitive abilities, engenders significant anticipation and intrigue across scientific, commercial, and societal arenas. This fascination extends particularly to the Internet of Things (IoT), a landscape characterized by the interconnection of countless devices, sensors, and systems, collectively gathering and sharing data to enable intelligent decision-making and automation. This research embarks on an exploration of the opportunities and challenges towards achieving AGI in the context of the IoT. Specifically, it starts by outlining the fundamental principles of IoT and the critical role of Artificial Intelligence (AI) in IoT systems. Subsequently, it delves into AGI fundamentals, culminating in the formulation of a conceptual framework for AGI's seamless integration within IoT. The application spectrum for AGI-infused IoT is broad, encompassing domains ranging from smart grids, residential environments, manufacturing, and transportation to environmental monitoring, agriculture, healthcare, and education. However, adapting AGI to resource-constrained IoT settings necessitates dedicated research efforts. Furthermore, the paper addresses constraints imposed by limited computing resources, intricacies associated with large-scale IoT communication, as well as the critical concerns pertaining to security and privacy.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Toward Edge General Intelligence with Agentic AI and Agentification: Concepts, Technologies, and Future Directions

    cs.NI 2025-08 conditional novelty 4.0 of 10

    A survey that organizes agentic AI for 6G edge networks into four pillars, compactness, efficiency, knowledge and reasoning, and migration, and illustrates them with prior case studies.

  2. UrbanMind: Towards Urban General Intelligence via Tool-Enhanced Retrieval-Augmented Generation and Multilevel Optimization

    cs.LG 2025-07 reject novelty 4.0 of 10

    The paper introduces UrbanMind, a tool-enhanced RAG framework with a multilevel optimization formulation for continual adaptation in urban AI, but offers only qualitative prototype results.

  3. Thinking Beyond Tokens: From Brain-Inspired Intelligence to Cognitive Foundations for Artificial General Intelligence and its Societal Impact

    cs.AI 2025-07 conditional novelty 2.0 of 10

    A broad survey arguing that AGI requires modular, memory-augmented, embodied architectures rather than scaled-up token prediction, with a brief proposal to decompose intelligence into five components.

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