Recent Progress on the Convergence of the Internet of Things and Artificial Intelligence

被引:34
作者
Shi, Feifei [1 ]
Ning, Huansheng [1 ]
Huangfu, Wei [1 ]
Zhang, Fan [1 ]
Wei, Dawei [2 ]
Hong, Tao [3 ]
Daneshmand, Mahmoud [4 ,5 ]
机构
[1] Univ Sci & Technol Beijing, Sch Comp & Commun Engn, Beijing, Peoples R China
[2] Univ Sci & Technol Beijing, Beijing, Peoples R China
[3] Beihang Univ, Sch Elect & Informat Engn, Beijing, Peoples R China
[4] Stevens Inst Technol, Dept Business Intelligence & Analyt, Hoboken, NJ 07030 USA
[5] Stevens Inst Technol, Dept Comp Sci, Hoboken, NJ 07030 USA
来源
IEEE NETWORK | 2020年 / 34卷 / 05期
基金
中国国家自然科学基金;
关键词
Artificial intelligence; Convergence; Sensors; Internet of Things; Neural networks; Routing; Smart cities;
D O I
10.1109/MNET.011.2000009
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The overwhelming increase of ubiquitous data, connections, and services brings serious challenges, in particular facing the demanding requirements of the Internet of Things (IoT). In order to seek better solutions and achieve more efficient information retrieval, artificial intelligence (AI) serves as a strong technical earthquake and contributes a lot to data analysis and decision making. It plays a compelling role in prompting digital and intelligent services. In this article, we focus on and emphasize the great significance pertaining to the convergence of IoT and AI. We first elaborate two typical forms of AI, namely knowledge-enabled AI and data-driven AI, with a comparison between respective advantages and disadvantages. Then we survey recent progress relating to the convergence of AI throughout the IoT architecture, from the sensing layer through the network layer to the application layer. In addition, a case study of a smart city is presented illustrating the convergence between IoT and AI. Furthermore, we point out open issues worth further research. The convergence of IoT and AI marries the merits of both and enables strong capability of resolving a broad range of problems.
引用
收藏
页码:8 / 15
页数:8
相关论文
共 15 条
[1]  
Aosen Wang, 2015, 2015 IEEE Biomedical Circuits and Systems Conference (BioCAS), P1, DOI 10.1109/BioCAS.2015.7348375
[2]   Selective Vision Sensing with Neural Gas Networks [J].
Cretu, Ana-Maria ;
Payeur, Pierre ;
Petriu, Emil M. .
2008 IEEE INSTRUMENTATION AND MEASUREMENT TECHNOLOGY CONFERENCE, VOLS 1-5, 2008, :478-483
[3]  
Esmaeeli M., 2015, INT J COMPUT APPL, V126, P8
[4]   Ontology-based user profile learning [J].
Eyharabide, Victoria ;
Amandi, Analia .
APPLIED INTELLIGENCE, 2012, 36 (04) :857-869
[5]  
Guo W., 2008, 2008 4 INT C WIR COM, P1
[6]  
Huansheng N., 2019, IEEE T COMPUTATIONAL
[7]   Edge-Computing-Enabled Smart Cities: A Comprehensive Survey [J].
Khan, Latif U. ;
Yaqoob, Ibrar ;
Tran, Nguyen H. ;
Kazmi, S. M. Ahsan ;
Tri Nguyen Dang ;
Hong, Choong Seon .
IEEE INTERNET OF THINGS JOURNAL, 2020, 7 (10) :10200-10232
[8]   Human-Attention Inspired Resource Allocation for Heterogeneous Sensors in the Web of Things [J].
Ning, Huansheng ;
Liu, Hong ;
Du, Wei ;
Wu, Jiajia ;
Wang, Ziou ;
Yang, Laurence T. ;
Min, Geyong .
IEEE INTELLIGENT SYSTEMS, 2013, 28 (06) :20-28
[9]   SCHEDULING STRATEGY BASED ON BP NEURAL NETWORK AND FUZZY FEEDBACK IN NETWORKED CONTROL SYSTEM [J].
Pan, Wei-Hua ;
Han, Pu ;
Zhang, Li-Jing ;
Wang, Tian-Kun .
PROCEEDINGS OF 2009 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-6, 2009, :806-+
[10]   Energy-Efficient Location and Activity-Aware On-Demand Mobile Distributed Sensing Platform for Sensing as a Service in IoT Clouds [J].
Perera, Charith ;
Talagala, Dumidu S. ;
Liu, Chi Harold ;
Estrella, Julio C. .
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS, 2015, 2 (04) :171-181