About the Journal
Aims
The Intelligent Systems for Cities and Society (ISCISO) is an international, peer-reviewed scholarly journal dedicated to advancing the theory, development and application of intelligent systems for addressing complex challenges in cities and society. The journal provides an interdisciplinary platform for research integrating artificial intelligence, computational intelligence, data science, intelligent infrastructure, advanced sensing, control, optimisation and decision-support technologies to develop smarter, more adaptive, sustainable, resilient and human-centred urban environments.
ISCISO aims to advance intelligent approaches to the planning, design, operation, monitoring and management of interconnected urban and societal systems. It welcomes theoretical, methodological, computational and empirical contributions that demonstrate meaningful advances in intelligent technologies and their application to real-world urban challenges. Particular emphasis is placed on trustworthy and explainable AI, intelligent cyber-physical systems, digital twins, edge intelligence, autonomous and connected infrastructure, human–AI interaction, and data-driven decision-making.
The journal encourages interdisciplinary research that connects technological innovation with environmental sustainability, social inclusion, infrastructure resilience, public well-being and responsible urban governance. It particularly values contributions that integrate multiple systems, address uncertainty and complexity, and demonstrate measurable improvements in the performance, reliability, accessibility, safety, efficiency or sustainability of cities and society.
Scope
The journal welcomes original research articles, systematic and critical review papers, methodological contributions and high-quality applied studies across the following interconnected areas:
1. Artificial Intelligence and Computational Intelligence for Cities
Artificial intelligence (AI), machine learning, deep learning, generative AI, foundation models, large language models, natural language processing, computer vision, reinforcement learning, federated learning, swarm intelligence, evolutionary computation, fuzzy systems, neuro-fuzzy systems, hybrid intelligent algorithms, explainable and trustworthy AI, and responsible AI for urban and societal applications.
2. Intelligent Sensing, IoT and Cyber-Physical Urban Systems
Internet of Things (IoT), wireless sensor networks, smart sensing, distributed intelligence, edge AI, fog and cloud computing, embedded intelligence, cyber-physical systems, autonomous sensing and actuation, robotics, intelligent communication networks, 5G/6G, connected devices, context-aware systems, ubiquitous computing and real-time urban monitoring.
3. Digital Twins, Urban Modelling and Simulation
Computational modelling and AI are driving the evolution of Urban Digital Twins (UDTs), transforming static city maps into dynamic, complex adaptive systems. By integrating agent-based modeling, multi-agent systems, and discrete-event simulations, urban scientists can capture real-time human behavior, infrastructure interactions, and systemic feedback loops across city spaces. Predictive simulation and real-time data assimilation enable municipalities to stress-test urban policies, run multi-criteria scenario analyses, and anticipate spatial bottlenecks before deploying physical infrastructure. Immersive virtual and augmented reality platforms further translate complex computational urban models into intuitive visual environments for multi-stakeholder governance. By establishing continuous sync between physical sensor networks and digital representations, integrated urban systems simulation empowers cities to remain agile, resilient, and responsive to rapid urban transformations.
4. Intelligent Control, Optimisation and Decision Support
Intelligent control systems, predictive and adaptive control, multi-objective optimisation, operational research, mathematical programming, computational optimisation, multi-criteria decision-making, decision-support systems, uncertainty modelling, fuzzy decision analysis, robust and resilient optimisation, risk assessment, resource allocation and intelligent planning under uncertainty.
5. Smart and Resilient Urban Infrastructure
Intelligent infrastructure design, monitoring and management; structural and infrastructure health monitoring; predictive maintenance; infrastructure asset management; critical infrastructure resilience; intelligent buildings; smart campuses; responsive environments; intelligent water and wastewater networks; smart grids; distributed energy systems; and interconnected infrastructure.
6. Intelligent and Sustainable Urban Mobility
Intelligent transportation systems, connected and automated mobility, autonomous vehicles, electric and shared mobility, public transport intelligence, traffic prediction and optimisation, smart parking, urban logistics, pedestrian and cyclist analytics, mobility-as-a-service, vehicle-to-everything communication, multimodal transport integration, transport accessibility and intelligent mobility management.
7. Intelligent Environmental and Resource Management
AI is revolutionizing urban environmental management by transforming raw ecological data into actionable, climate-resilient strategies. Advanced machine learning models power real-time air quality forecasting, environmental analytics, and urban biodiversity tracking, enabling precise climate intelligence and targeted adaptation. In resource management, AI optimizes smart grid operations, balances renewable energy integration, and accurately forecasts urban power demand. Concurrently, intelligent algorithms streamline water resource allocation, optimize wastewater treatment systems, and drive automated waste collection, establishing efficient circular economy frameworks. By embedding sensors and predictive analytics into physical spaces, municipalities can dynamically govern green infrastructure, reduce urban carbon footprints, and protect urban ecosystems from systemic environmental shocks.
8. Human-Centred Intelligent Systems and Society
Human–AI interaction, human–computer interaction, behavioural analytics, citizen-centred intelligent services, inclusive and accessible technologies, intelligent healthcare, digital health, ambient assisted living, assistive technologies, participatory sensing, citizen science, public engagement, social computing, technology acceptance, digital inclusion and societal impacts of intelligent systems.
9. Intelligent Governance, Security and Responsible Innovation
Smart and digital governance, AI-assisted public administration, intelligent public services, evidence-based policymaking, algorithmic accountability, digital ethics, privacy-preserving computing, cybersecurity, information security, digital identity, blockchain applications, data governance, interoperability, regulatory frameworks, responsible innovation and the societal implications of automated decision-making.
10. Urban Resilience, Risk and Disaster Intelligence
Intelligent Artificial Intelligence is transforming disaster risk management and urban resilience by shifting cities from reactive crisis response to proactive, data-driven adaptation. Integrating multi-hazard forecasting, Urban Digital Twins, and spatial analytics enables intelligent prediction systems to evaluate infrastructure vulnerabilities, model climate hazards, and issue real-time early warnings before catastrophic disruptions occur.
During acute crises, emergency optimization frameworks dynamically allocate scarce resources, optimize evacuation routes, and manage emergency medical logistics under extreme uncertainty. Advanced computer vision and crisis informatics analyze crowd dynamics and sensor feeds, while natural language processing filters real-time communications to streamline multi-agency coordination. Post-disaster recovery relies on satellite-driven damage assessments and predictive modeling to prioritize reconstruction, ensuring rebuilt infrastructure withstands future environmental shocks. By embedding machine learning into urban planning, cities evolve into self-organizing, adaptive environments capable of mitigating socio-spatial inequalities and absorbing systemic stress.
ISCISO particularly encourages interdisciplinary contributions addressing the interactions and interdependencies between technological, environmental, infrastructural, economic and social systems. Research that integrates multiple intelligent technologies or demonstrates transferable approaches to complex urban and societal challenges is especially welcome.
