Muntean Maria Viorela
Department of Informatics, Mathematics and Electronics, 1 Decembrie 1918 University of Alba Iulia, 510009 Alba Iulia, Romania.
Sensors (Basel). 2024 Dec 10;24(24):7886. doi: 10.3390/s24247886.
Analyzing IoT data is an important challenge in the smart cities domain due to the complexity of network traffic generated by a large number of interconnected devices: smart cameras, light bulbs, motion sensors, voice assistants, and so on. To overcome this issue, a multi-agent system is proposed to deal with all machine learning steps, from preprocessing and labeling data to discovering the most suitable model for the analyzed dataset. This paper shows that dividing the work into different tasks, managed by specialized agents, and evaluating the discovered models by an Expert System Agent leads to better results in the learning process.
由于大量互联设备（智能摄像头、灯泡、运动传感器、语音助手等）产生的网络流量复杂，分析物联网数据是智慧城市领域的一项重要挑战。为克服这一问题，提出了一种多智能体系统来处理所有机器学习步骤，从数据预处理和标注到为分析数据集发现最合适的模型。本文表明，将工作划分为由专门智能体管理的不同任务，并由专家系统智能体评估发现的模型，会在学习过程中带来更好的结果。
