Developing smart city services using intent‐aware recommendation systems: A survey

Author:

Rafique Wajid1ORCID,Hafid Abdelhakim Senhaji1,Qadir Junaid2

Affiliation:

1. Department of Computer Science and Operations Research University of Montreal Montreal Quebec Canada

2. Department of Computer Science and Engineering College of Engineering, Qatar University Doha Qatar

Abstract

AbstractSmart 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.

Funder

Qatar National Research Fund

Publisher

Wiley

Subject

Electrical and Electronic Engineering

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Towards people-centric smart cities: A comparative evaluation of citizens’ sense of gain in pilot cities in China;Journal of Cleaner Production;2024-01

2. A taxonomy for decision making in IoT systems;Internet of Things;2023-12

3. Development of Recommender Systems for Better Services and Products using Data Science;2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC);2023-07-06

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