Research Article
Optimization of Governance Factors for Smart City Through Hierarchical Mamdani Type-1 Fuzzy Expert System Empowered with Intelligent Data Ingestion Techniques
@ARTICLE{10.4108/eai.13-7-2018.159975, author={Areej Fatima and Sagheer Abbas and Muhammad Asif and Muhammad Adnan Khan and Muhammad Saleem Khan}, title={Optimization of Governance Factors for Smart City Through Hierarchical Mamdani Type-1 Fuzzy Expert System Empowered with Intelligent Data Ingestion Techniques}, journal={EAI Endorsed Transactions on Scalable Information Systems}, volume={6}, number={23}, publisher={EAI}, journal_a={SIS}, year={2019}, month={9}, keywords={Product Inference Engine, Information and Communication Technology, Ubiquitous Sensor Networks, Internet of Things, Internet of Services, Internet of Energy, Internet of People}, doi={10.4108/eai.13-7-2018.159975} }- Areej Fatima
Sagheer Abbas
Muhammad Asif
Muhammad Adnan Khan
Muhammad Saleem Khan
Year: 2019
Optimization of Governance Factors for Smart City Through Hierarchical Mamdani Type-1 Fuzzy Expert System Empowered with Intelligent Data Ingestion Techniques
SIS
EAI
DOI: 10.4108/eai.13-7-2018.159975
Abstract
A Smart City is an urban area that uses the Internet of things (IoT) sensors to collect data and information to enhance the operational aptitude, in a way to manage assets and resources efficiently. Smart governance is a factor of a smart city for intelligent utilization of ICT to enhance the basic leadership. The smart government may be considered as a reason for creating smart governance, through the application of rising information and communication technology for administering. Smart Governance is totally dependent on the information that is being recorderded. Smart consists of multiple factors that an essential role in smart city activities, which require complex collaborations between governments, citizens and different partners. In this article, a new computational method is proposed for the evaluation of the Governance factors of the smart city using Hierarchical Mamdani Type-1 Fuzzy Expert System and empowered with fuzzy based data ingestion techniques.
Copyright © 2019 Areej Fatima et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
