Institute for Intelligent Systems Research and Innovation, Deakin University, Waurn Ponds, Geelong, VIC 3216, Australia.
Department of Computer Engineering, Faculty of Engineering, Fasa University, Vali asr Blvd, Fasa 74617-81189, Iran.
Sensors (Basel). 2023 Jan 28;23(3):1466. doi: 10.3390/s23031466.
Continuous advancements of technologies such as machine-to-machine interactions and big data analysis have led to the internet of things (IoT) making information sharing and smart decision-making possible using everyday devices. On the other hand, swarm intelligence (SI) algorithms seek to establish constructive interaction among agents regardless of their intelligence level. In SI algorithms, multiple individuals run simultaneously and possibly in a cooperative manner to address complex nonlinear problems. In this paper, the application of SI algorithms in IoT is investigated with a special focus on the internet of medical things (IoMT). The role of wearable devices in IoMT is briefly reviewed. Existing works on applications of SI in addressing IoMT problems are discussed. Possible problems include disease prediction, data encryption, missing values prediction, resource allocation, network routing, and hardware failure management. Finally, research perspectives and future trends are outlined.
随着机器对机器交互和大数据分析等技术的不断进步,物联网使得信息共享和智能决策成为可能,而物联网则利用日常设备实现了这一点。另一方面,群体智能(SI)算法旨在建立代理之间的建设性交互,而不管它们的智能水平如何。在 SI 算法中,多个个体同时运行,并且可能以协作的方式运行,以解决复杂的非线性问题。本文研究了 SI 算法在物联网中的应用,特别关注医疗物联网(IoMT)。简要回顾了可穿戴设备在 IoMT 中的作用。讨论了 SI 在解决 IoMT 问题中的应用的现有工作。可能的问题包括疾病预测、数据加密、缺失值预测、资源分配、网络路由和硬件故障管理。最后,概述了研究视角和未来趋势。