Developing smart city services using intent-aware recommendation systems: A survey
Author | Rafique, Wajid |
Author | Hafid, Abdelhakim Senhaji |
Author | Qadir, Junaid |
Available date | 2023-07-13T05:40:52Z |
Publication Date | 2023 |
Publication Name | Transactions on Emerging Telecommunications Technologies |
Resource | Scopus |
ISSN | 21613915 |
Abstract | Smart cities could be defined as urban areas that use Information and Communication Technology (ICT) to solve city problems in efficient and sustainable ways. Intent-aware Recommender Systems (IARS) within ICT play a crucial role in filtering useless information according to user demands and assist in decision-making in various smart city platforms. In smart cities, the user traces on IoT, RFIDs, mobiles, and smart sensors capture actual user intent of performing an activity and enhance user satisfaction by proposing optimal services. This paper presents a detailed literature survey of the field of IARS and how it can be used for developing smart city services. First, we present the evolution of IARS with the development of computing technology. Then, we present case studies, synergies, advances, and a reference implementation architecture of IARS for smart cities. We discuss requirements for developing smart city services using IARS. Furthermore, we devise a comprehensive taxonomy of applications and techniques of IARS using different performance parameters. Finally, we elaborate on current issues, challenges, and future research directions in IARS; these directions we believe will pave the way for autonomous service provisioning in smart cities. 2023 John Wiley & Sons, Ltd. |
Sponsor | Qatar National Research Fund, Grant/Award Number: 13S-0206-200273 Funding information |
Language | en |
Publisher | John Wiley and Sons Inc |
Subject | Decision making Information filtering Smart city Case-studies Computing technology Decisions makings Information and Communication Technologies Literature survey Reference implementation Urban areas User demands User trace Users' satisfactions Recommender systems |
Type | Article |
Issue Number | 4 |
Volume Number | 34 |
Files in this item
Files | Size | Format | View |
---|---|---|---|
There are no files associated with this item. |
This item appears in the following Collection(s)
-
Computer Science & Engineering [2402 items ]