A lightweight yet comprehensive open-source smart city platform architecture that serves as a bridge between theoretical research and practical deployment, reducing barriers to entry and accelerating the development of smarter, more sustainable urban systems is proposed.
Abstract
The rapid growth of smart cities has highlighted the need for robust, flexible, and cost-effective platforms that can support the integration and management of Internet of Things (IoT) devices, data streams, and analytics pipelines. However, recent studies have revealed a significant gap in the availability of open-source IoT platforms tailored for smart cities, creating a barrier for researchers and developers seeking to experiment, innovate, and validate connected urban applications. This article proposes a lightweight yet comprehensive open-source smart city platform architecture to address this gap. By integrating essential components such as real-time data ingestion, big data storage, messaging protocols, and data analytics, the platform offers a solid foundation for developing and testing smart city solutions. The architecture focuses on modularity, interoperability, and scalability, ensuring that the system can grow alongside the demands of urban environments. We aim to foster an open, collaborative ecosystem where researchers and developers can freely access, modify, and enhance the platform, driving forward the next generation of smart city innovations. The proposed solution serves as a bridge between theoretical research and practical deployment, reducing barriers to entry and accelerating the development of smarter, more sustainable urban systems.
The results show that heterogeneous IoT services can be hosted on modest local infrastructure while maintaining logical separation between Living Lab data and services, and offers a practical model for higher-education institutions and community-oriented renewable-energy initiatives in resource-constrained environments.
Abstract:
Smart cities leverage emerging technologies to enhance urban living, improve resource efficiency, and enable sustainable development. Among these technologies, the Internet of Things (IoT) plays a pivotal role by connecting physical devices, sensors, and systems to collect and exchange real-time data. This interconnected infrastructure enables intelligent monitoring and management of urban services such as transportation, energy distribution, waste management, water supply, and public safety. IoT-based smart city systems facilitate data-driven decision-making, reduce operational costs, and improve service delivery to citizens. By integrating cloud computing, edge computing, and advanced analytics, cities can respond dynamically to changing conditions and optimize resource utilization. Despite its advantages, challenges such as data security, interoperability, scalability, and privacy concerns must be addressed for successful implementation. Overall, IoT-enabled smart city infrastructure represents a transformative approach to building efficient, resilient, and citizen-centric urban environments.
Keywords: Smart City, Internet of Things (IoT), Urban Infrastructure, Sensor Networks, Real-time Data, Cloud Computing, Edge Computing, Smart Governance, Data Analytics, Sustainable Development.
G. Nagarjuna, Gudikandula Sai Krishna, K. Rakshitha· International Scientific Jou...· 0 citations
The rapid growth of the Internet of Things (IoT) has significantly accelerated the development of smart home systems, enabling automation, energy efficiency, and enhanced user experience. However, the lack of interoperability among heterogeneous devices and platforms remains a major challenge, resulting in fragmented ecosystems and limited scalability. To address these issues, the Matter protocol has emerged as a unified, IP-based connectivity standard for smart home environments. This paper presents a comprehensive study of the Matter protocol, including its architecture, communication mechanisms, and security model. A practical IoT-based smart home system is designed and implemented using ESP32 platforms and the Matter SDK. The system integrates multiple devices such as smart lighting, switches, smart plugs, and environmental sensors, supporting crossplatform interaction across different ecosystems. Experimental evaluation is conducted under real-world conditions, focusing on interoperability, latency, system stability, and security. The results show that the proposed system achieves reliable crossplatform compatibility, stable network performance, low communication latency, and secure device authentication. Additionally, the system maintains core functionality even under limited network conditions, demonstrating strong robustness. These findings confirm that the Matter protocol is a promising solution for building scalable, secure, and interoperable next-generation smart home systems.
Nghia Duong Tan, H. Manh, P. N. Huu et al.· 2026 11th International Conf...· 0 citations
In recent years, the development of smart cities has gained considerable attention due to the growing need for sustainable and efficient resource management. As urbanization accelerates, cities are facing increasing challenges in managing resources such as energy, water, waste, and transportation. This paper explores the integration of Internet of Things (IoT) technologies and data analytics in improving resource management within smart cities. By leveraging IoT devices, real-time data collection, and advanced data analytics techniques, cities can optimize resource allocation, reduce waste, and enhance citizen engagement. Through various case studies, the paper highlights the impact of IoT-driven solutions on urban services, including smart grids, water conservation, waste management, and traffic control. While the integration of IoT and data analytics presents significant opportunities, the paper also addresses key challenges, such as data privacy, security, and system integration. Finally, the paper discusses future trends and opportunities for creating smarter, more sustainable cities through the convergence of IoT and data analytics.
S. Verma, Priya Kapoor· International Journal of Eme...· 0 citations
An overview of the IoT architecture is provided, comparing leading IoT platform such as AWS and Microsoft Azure vendor to understand the overall architecture of these platforms and explore their main cores for potential customization in developing a proprietary IoT platform.
Sothea Phann· International Journal of Fut...· 1 citation
: Smart city systems increasingly depend on data analytics and visualization to support informed and timely decision making in complex urban environments. However, existing middleware solutions predominantly focus on data acquisition and communication, while analytical processing and visualization are typically delegated to external applications, resulting in increased development complexity, reduced reusability, and fragmented system architectures. This study presents analytics and visualization-centric middleware named “Service-Oriented Middleware for Smart City Applications” (SOMSCA), in which these capabilities are embedded directly within the middleware layer. SOMSCA adopts a service-oriented approach, exposing analytics and visualization functionalities as reusable platform services, and incorporates a data-type-oriented visualization strategy along with a template-assisted dash-boarding mechanism to enable dynamic and flexible application development. To validate the proposed approach, a prototype implementation is developed using React, FastAPI, MySQL, and TimescaleDB and evaluated using air-quality data collected from the London Air Quality Network, comprising more than one million observations across multiple pollutants and monitoring locations. The implementation supports real-time, historical, and aggregated analytical services together with dynamic dashboard generation. The results demonstrate the practical feasibility of middleware-integrated analytics and visualization through reusable service creation, flexible dashboard configuration, and interactive environmental monitoring capabilities. These findings highlight the potential of middleware-level intelligence to simplify application development and support data-driven decision making in smart city environment.
Zulfiqar Ali, A. Mahmood, S. Khatoon et al.· Computers, Materials & C...· 0 citations
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