Abstract
Ubiquitous computing has proposed the idea of seamless integration of computing devices into smart spaces earlier. The proliferation of Internet of Things (IoT) technologies offers users an expanding array of device control options, including voice activation and home automation. However, these technologies necessitate user intervention for adjusting device state, relying on information derived from the environment and events within the smart space. This article introduces an AI autonomous decision system designed to address the reliance on user intervention in adjusting device states within IoT-enabled smart space. The proposed system consists of a sensing layer, transmission layer, decision layer, and execution layer, responsible for information sensing, transmission, decision generation, and device control, respectively. The decision layer incorporates a large language model (LLM) and accompanying modules to facilitate real-time decision making. This study validates the core functionalities of the system within an unmanned smart home and examines the advantages, disadvantages, potential security risks, and future development directions of the AI autonomous decision.
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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Du, J., Jia, B., Fu, X. (2024). Space Brain: An AI Autonomous Spatial Decision System. In: Fang, L., Pei, J., Zhai, G., Wang, R. (eds) Artificial Intelligence. CICAI 2023. Lecture Notes in Computer Science(), vol 14474. Springer, Singapore. https://doi.org/10.1007/978-981-99-9119-8_6
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DOI: https://doi.org/10.1007/978-981-99-9119-8_6
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