• Corpus ID: 229188854

Developing Future Human-Centered Smart Cities: Critical Analysis of Smart City Security, Interpretability, and Ethical Challenges

  title={Developing Future Human-Centered Smart Cities: Critical Analysis of Smart City Security, Interpretability, and Ethical Challenges},
  author={Kashif Ahmad and Majdi Maabreh and Mohamed Ghaly and Khalil Khan and Junaid Qadir and Ala Al-Fuqaha},
As we make tremendous advances in machine learning and artificial intelligence technosciences, there is a renewed understanding in the AI community that we must ensure that humans being are at the center of our deliberations so that we don't end in technology-induced dystopias. As strongly argued by Green in his book Smart Enough City, the incorporation of technology in city environs does not automatically translate into prosperity, wellbeing, urban livability, or social justice. There is a… 

The Duo of Artificial Intelligence and Big Data for Industry 4.0: Review of Applications, Techniques, Challenges, and Future Research Directions

This paper provides a comprehensive overview of different aspects of AI and Big Data in Industry 4.0 with a particular focus on key applications, techniques, the concepts involved, key enabling technologies, challenges, and research perspective towards deployment of Industry 5.0.

Collaborative Federated Learning for Healthcare: Multi-Modal COVID-19 Diagnosis at the Edge

This paper utilized the emerging concept of clustered federated learning (CFL) for an automatic COVID-19 diagnosis and evaluated the potential of intelligent processing of clinical data at the edge under different experimental setups on two benchmark datasets.

Artificial intelligence based prognostic maintenance of renewable energy systems: A review of techniques, challenges, and future research directions

An overview of the predictive/prognostic maintenance frameworks reported in the literature is provided, with a particular focus to the approaches, challenges, including data‐related issues, such as the availability of quality data and data auditing, feature engineering, interpretability, and security issues.

Earthquake-Induced Building-Damage Mapping Using Explainable AI (XAI)

This paper proposes the use of SHAP (Shapley additive explanation) to interpret the outputs of a multilayer perceptron (MLP)—a machine learning model—and analyse the impact of each feature descriptor included in the model for building-damage assessment to examine the reliability of the model.

Analyzing the Adoption Challenges of the Internet of Things (IoT) and Artificial Intelligence (AI) for Smart Cities in China

This study explored the driving and dependent power of the challenges, and causal relationships between the barriers were established, which can help regulatory bodies, policymakers, and researchers to make better decisions to overcome the challenges for developing sustainable smart cities.

Online Intrusion Detection for Internet of Things Systems With Full Bayesian Possibilistic Clustering and Ensembled Fuzzy Classifiers

A fuzzy system for the online defense of IoT that incorporates a full Bayesian possibilistic clustering module for feature processing and an ensemble module motivated by reinforcement learning and adaptive boosting that dynamically fits the streaming data.

ML Attack Models: Adversarial Attacks and Data Poisoning Attacks

This work presents a new approach to attack models that addresses the challenge of directly simulating the dynamic response of the immune system in the face of attackers.



The ethics of smart cities and urban science

  • Rob Kitchin
  • Computer Science
    Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
  • 2016
It is argued that smart city initiatives and urban science need to be re-cast in three ways: a re-orientation in how cities are conceived; a reconfiguring of the underlying epistemology to openly recognize the contingent and relational nature of urban systems, processes and science; and the adoption of ethical principles designed to realize benefits of smart cities and urbanScience while reducing pernicious effects.

Algorithmic Decision-Making in AVs: Understanding Ethical and Technical Concerns for Smart Cities

This article investigates the ethical and technical concerns surrounding algorithmic decision-making in AVs by exploring how driving decisions can perpetuate discrimination and create new safety risks for the public.

The pursuit of citizens' privacy: a privacy-aware smart city is possible

This article identifies a number of privacy breaches that can appear within the context of smart cities and their services and defines the concept of citizens' privacy as a model with five dimensions: identity privacy, query privacy, location privacy, footprint privacy and owner privacy.

Smart Cities, Big Data, and the Resilience of Privacy

It is concluded that if the legal and regulatory systems that are available today cannot adapt, then the fundamental right to privacy will become brittle and break under the burden of ubiquitous and opaque surveillance in the smart city.

Privacy concerns in smart cities

It is argued that the general hypothesis of the framework offers clear directions for further empirical research and theory building about privacy concerns in smart cities, and that it provides a sensitizing instrument for local governments to identify the absence, presence, or emergence of privacy concerns among their citizens.

Smart Cities: A Survey on Data Management, Security, and Enabling Technologies

The fundamental data management techniques employed to ensure consistency, interoperability, granularity, and reusability of the data generated by the underlying IoT for smart cities are described.

Security, Privacy and Risks Within Smart Cities: Literature Review and Development of a Smart City Interaction Framework

This comprehensive review provides a useful perspective on many of the key issues and offers key direction for future studies, and develops a smart city interaction framework.

Applications of Artificial Intelligence and Machine learning in smart cities

The AR face database