智能物联网AIoT研究综述

doi:10.11959/j.issn.1000-0801.2021204

Abstract

Abstract:

AIoT (artificial intelligence of things) is an integrated product of artificial intelligence (AI) and internet of things (IoT).Currently, it has been widely used in smart cities, smart homes, smart manufacturing, and driverless.However, the research of AIoT is still in its infancy, facing with many problems and challenges.In order to clarify the concept and provide possible solutions, a comprehensive survey was carried out on AIoT.Firstly, a clear definition of AIoT was provided, along with the brief introduction on its background and application scenarios.And then a novel cloud-edge-end hybrid AIoT architecture for intelligent information processing was constructed.Based on the research framework of AIoT, the research status and solutions were discussed, including AI integrated IoT data acquisition, complex event processing and coordination, cloud-edge-end integration, AI-enhanced IoT security and privacy, and AI-based applications, etc.Finally, it identified the open challenges and offers future research directions.

Key words: AIoT, cloud-edge-end hybrid computing framework, AI integrated IoT application, research direction

CLC Number:

TP393

Jiyi WU, Wenjuan LI, Jian CAO, Shiyou QIAN, Qifei ZHANG, Rajkumar BUYYA. AIoT: a taxonomy, review and future directions[J]. Telecommunications Science, 2021, 37(8): 1-17.

Figures/Tables 11

References 60

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数据来源时间	公司名称	战略重点	应用场景
2018年3月	阿里巴巴	IoT成为第5个主赛道	智能人居、智慧城市、工业物联网
2018年4月	百度	与硬蛋签订AIoT合作协议	无人驾驶、智能家居
2018年5月	腾讯	布局人联网、物联网和智联网	腾讯超级大脑
2018年11月	小米	成为核心战略	智能家居、硬件平台研发
2018年12月	华为	首次公布AIoT战略	全场景应用
2018年12月	京东	退出“京鱼座”生态品牌	智能硬件、智能家居、智慧出行等
2019年1月	云知声	公布多模态AI芯片战略	智慧城市、智慧家居、智慧出行等
2019年1月	思必驰	发布首款AI芯片TAIHANG	智能家居、智能车载、企业服务
2019年1月	OPPO	成立新兴移动事业部、注意AIoT技术研发	智慧生活
2019年1月	旷世	宣布打造AIoT操作系统	制造业、智慧物流等

文献	应用场景	主要贡献	性能检测
参考文献[8]	物联网智能数据采集	提出面向大数据环境、基于云平台的物联网体系架构和智能数据采集方法	使用车间环境现场采集，验证采集准确率和安全性
参考文献[9]	无线传感器网络	提出最小时延数据采集策略	采用仿真实验验证时延和能耗
参考文献[10]	云物联平台	提出多源数据汇集方法和异构数据分类存储方法	开发云物联平台验证存储系统的可用性、合法性、可扩展性、稳健性、实时性和安全性

文献	应用场景	主要贡献	性能检测
参考文献[11]	物联网环境大规模异构网元互联、分布式自组织和动态协作	提出基于生物启发算法的物联网网元信息交互机制，基于人体血糖调节模型的物联网动态自组织机制和物联网智能服务模型	通过仿真实验证明了算法的稳定性、目标跟踪能力和服务处理能力
参考文献[12]	5G支持的IoT中的通信问题	提出基于遗传算法的小区负载均衡策略	采用仿真实验验证吞吐率、时延、接入成功率
参考文献[13]	制造物联云平台复杂事件处理	设计分布式复杂事件处理机制	通过两个案例对平台进行功能测试和性能评估
参考文献[14]	物联网智能网关	设计了包含视频监控、数据采集和智能控制的IoT网关	通过仿真系统对智能网关的功能进行测试，同时在智慧农业平台进行了部署和识别视频检测
参考文献[15-16]	基于软件定义网络的IoT系统	提出基于深度学习的数据流量预测算法和信道分配算法提高传输质量	通过仿真验证了预测和信道分配算法的准确度和性能（吞吐量和丢包率）
参考文献[17]	IoT 组件的智能集成、配置和监测	提出语义增强型智能控制系统（SEMIoTICS）架构，支持IoT组件的语义建模及在线配置	以场景案例分析方式对架构的可用性进行了讨论

文献	应用场景	主要贡献	性能检测
参考文献[18]	基于IoT的5G网络数据决策	对AI技术在基于IoT的5G网络中应用现状进行了综述	对各种现存方案做了理论分析和比较
参考文献[19]	5G 支持的 IoT 网络中的通信和数据挖掘	提出5G智能物联网范式以实现智慧大数据处理和信道优化	采用仿真实验验证系统性能
参考文献[20]	AIoT支持的能源管理	提出AIoT进行智能能源管理的理论模型	理论分析和建模
参考文献[21]	融合边缘和雾计算的AIoT应用	对智能算法在云-雾-边混合框架的应用进行了综述	对各种现存方案做了理论分析和比较
参考文献[22]	智慧城市基于IoT的能源管理	提出具备深度学习能力的边缘辅助 IoT 能源管理模型	通过仿真验证了策略的性能（回报率和时延）
参考文献[23]	云边混合计算系统智能决策	提出云边智能框架的落地模型	理论分析和建模
参考文献[24]	车载网	提出车载网智能推荐算法	通过仿真实验验证了推荐算法的精确度和时间效率
参考文献[25]	智能制造	提出基于云的智能制造模型	构建了原型系统验证制造设备智能感知和获取方法的有效性
参考文献[26]	工业物联网	提出云-边协同工业物联网架构和智能任务卸载模型	通过仿真实验检测了模型的服务精确度和服务流量

文献	应用场景	主要贡献	性能检测
参考文献[53]	无线传感器网络	提出基于区块链的海量IoT数据采集框架以提高数据采集的安全、可信和有效性	通过仿真验证了数据采集的时延、信任模型的准确性和数据聚合的计算开销
参考文献[54]	车载无线网	提出可信智能协同网络框架以提高数据采集的安全性和准确性	通过仿真验证了协同数据采集方法的成本、时间和准确度
参考文献[55]	基于 IoT 的智能电力服务系统隐私保护	提出基于k-means和差分隐私的隐私和可用性数据聚类方案	通过理论分析了策略的安全性，通过仿真验证了聚类算法的效率
参考文献[56]	安全审计系统	提出基于区块链架构、符合ISO标准的安全审计系统，提升AIoT应用的安全性	通过理论论证了方案的可行性（性能和隐私保护能力）
参考文献[57]	物联网安全防护	提出基于机器学习的安全框架，实现对安全威胁的快速诊断和预防	构建了安全框架的理论模型，通过仿真实验验证了模型的性能
参考文献[58]	物联网安全及隐私保护	设计IoT攻击模型，对基于机器学习的IoT安全策略进行了综述	采用理论分析和仿真对比了不同策略的有效性
参考文献[59]	数字交易市场	分析了边缘智能在IoT数字交易中应用的安全和隐私问题	对存在问题及可行处理方案进行了理论分析

AIoT: a taxonomy, review and future directions

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