TY  - CONF
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174898281&doi=10.1109%2FICCE-Taiwan58799.2023.10226787&partnerID=40&md5=23c9634785969c2a2f1ae0b8a673a870
Y1  - 2023///
TI  - Edge Computing and AI for IoT: Opportunities and Challenges
PB  - Institute of Electrical and Electronics Engineers Inc.
N1  - Cited by: 7
EP  -  358
SN  - 9798350324174
AV  - none
ID  - scholars20429
A1  - Heng, Lim Ean
A1  - Yuen Chai, Tong
A1  - Muniandy, Manoranjitham A.P.
A1  - Fui, Tien
A1  - Ooi, Boonyaik Yaik
A1  - Lin, Jimmin Min
SP  - 357 
N2  - The proliferation of Internet of Things (IoT) devices has led to an exponential growth in data generated at the edge of the network. Edge computing, a distributed computing paradigm that enables computation and data storage at the network edge, has emerged as a promising solution for managing this data deluge. With the integration of Artificial Intelligence (AI) technologies, edge computing can provide real-time insights and decision-making capabilities, making it a powerful tool for a variety of IoT applications which poses both opportunities and challenges. © 2023 IEEE.
KW  - Decision making; Digital storage; Internet of things; Artificial intelligence technologies; Computing paradigm; Data storage; Decisions makings; Edge computing; Exponential growth; Network edges; Real- time; Technology EDGE
ER  -