The Internet of Things (IoT) has emerged as a fundamental technological paradigm for developing smart environments across domains, such as smart homes, smart cities, transportation systems, agriculture, and environmental monitoring. By interconnecting sensors, embedded systems, and intelligent services through communication networks, IoT architectures facilitate the collection, processing, and analysis of large volumes of contextual data.
Recent technological advances—particularly in edge computing, artificial intelligence, distributed systems, and embedded platforms—have significantly transformed the design and deployment of IoT systems. Traditional cloud-centric architectures are progressively evolving toward edge–cloud collaborative models, allowing computation and data processing to occur closer to devices. This paradigm improves latency, reduces bandwidth consumption, and enhances privacy protection while enabling real-time decision making.
However, the development of IoT architectures for smart environments continues to face several challenges, including system scalability, interoperability among heterogeneous devices, cybersecurity threats, energy efficiency, and reliable data management. Addressing these challenges requires innovative mechanisms, architectural approaches, and application-driven implementations that support increasingly complex distributed systems.
The Special Issue “IoT Architecture for Smart Environments: Mechanisms, Approaches, and Applications” was launched to explore these emerging challenges and opportunities. It aims to gather research contributions on novel IoT architectures, frameworks, and applications that advance the development of intelligent and interconnected environments.
Following a rigorous peer-review process, ten papers were accepted for publication in this Special Issue. These contributions cover a wide range of topics, including edge artificial intelligence, explainable machine learning, embedded systems programming frameworks, smart agriculture solutions, cybersecurity architectures, and intelligent environmental monitoring systems.
The following sections summarize the contributions to this Special Issue and discuss emerging research trends and future directions for IoT architectures in smart environments.
The papers included in this Special Issue reflect the multidisciplinary nature of IoT research, combining advances in embedded systems, networking, artificial intelligence, cybersecurity, and distributed computing.
Several contributions focus on edge intelligence and distributed processing, highlighting the increasing importance of performing data analysis closer to IoT devices. Other papers address the design of software frameworks and system architectures that facilitate the development and deployment of IoT solutions. Security and trust are also addressed through the exploration of blockchain-based mechanisms and secure communication infrastructures.
Additionally, the Special Issue includes several application-driven IoT implementations, demonstrating how these architectures can be applied in real-world scenarios such as smart homes, agriculture, autonomous transportation, and environmental monitoring.
Together, these works provide valuable insights into current trends and technological developments shaping the evolution of IoT-enabled smart environments.
Several papers in this Special Issue investigate the integration of artificial intelligence and machine learning within IoT architectures.
Reis et al. propose an edge-based artificial intelligence solution for anomaly detection in smart home environments, enabling real-time monitoring, and improving responsiveness while preserving user privacy by processing data locally [1].
Another contribution explores explainable machine learning techniques and proposes an IoT-supported framework for estimating shaft power in maritime systems. The approach improves interpretability while enabling predictive performance analysis for green shipping applications [2].
Embedded systems development is addressed by researchers who present a C-based framework for low-cost real-time embedded systems, designed to simplify firmware development for IoT devices while maintaining efficiency and scalability [3].
Cybersecurity in smart environments is explored through the development of an IoT platform to support research into and the assessment of cybersecurity mechanisms in smart rural environments, addressing challenges such as connectivity limitations and infrastructure constraints [4].
IoT technologies also play a crucial role in smart agriculture, as demonstrated by a microservice-based system that detects animal intrusion using edge computing mechanisms. This approach enables real-time detection while reducing latency and communication overhead [5].
Security challenges in connected transportation systems are addressed through a blockchain-based architecture that enhances the safety of autonomous vehicles by securing communication between vehicles and artificial intelligence systems [6].
Another practical implementation focuses on the monitoring of liquefied petroleum gas (LPG) levels in domestic stationary tanks using IoT sensors. The proposed system enables data sharing with filling plants to optimize distribution routes and improve operational efficiency [7].
The dynamic management of IoT-enabled embedded systems is investigated through a framework that supports runtime reconfiguration and on-the-fly system adaptation, enabling greater flexibility in complex IoT deployments [8].
Energy efficiency in dense IoT environments is addressed through a distributed edge computing architecture that reduces computational overhead and optimizes resource usage in large-scale IoT networks [9].
Finally, one contribution explores techniques for optimizing IoT video data using dimensionality reduction methods that enable efficient deep learning processing on edge devices, improving performance in resource-constrained environments [10].
Despite the rapid growth of IoT technologies, several research challenges remain. Many existing IoT deployments still rely heavily on centralized cloud infrastructures, which may introduce latency, increase network traffic, and raise privacy concerns. Several papers in this Special Issue address this challenge by proposing edge-based architectures that distribute computation closer to devices.
Another important challenge relates to system interoperability and development complexity. The frameworks presented in this Special Issue contribute toward simplifying the development of IoT systems while enabling integration across heterogeneous platforms and communication protocols.
Security and trust remain critical issues in IoT ecosystems. The contributions addressing cybersecurity testing platforms and blockchain-based communication mechanisms highlight the importance of developing secure and trustworthy infrastructures for large-scale IoT deployments.
Finally, real-world deployments often face domain-specific constraints such as limited connectivity, energy limitations, or environmental conditions. The application-oriented studies presented in this Special Issue demonstrate how tailored architectural solutions can address these constraints in practical environments.
The contributions in this Special Issue highlight several promising directions for future research.
One key direction is the increasing integration of artificial intelligence at the edge, enabling IoT devices to perform advanced analytics locally. Advances in lightweight machine learning models, federated learning, and hardware accelerators will likely play a central role in this evolution.
Another important area is the development of adaptive, self-configuring IoT architectures that dynamically adjust system behavior to environmental conditions or application requirements.
Security and privacy will continue to be central concerns. Future research may focus on decentralized trust frameworks, blockchain-based security mechanisms, and privacy-preserving data processing techniques.
Furthermore, improving interoperability and standardization across heterogeneous IoT platforms will be essential for enabling large-scale deployments of smart environments.
Finally, the integration of IoT with emerging paradigms such as digital twins, cyber–physical systems, and next-generation communication networks may further enhance the capabilities of intelligent environments.
This Special Issue presents a collection of research contributions that advance the understanding and development of IoT architectures for smart environments. The accepted papers demonstrate innovative approaches that integrate edge computing, artificial intelligence, secure communication mechanisms, and application-specific architectures.
The diversity of applications presented—from smart homes and agriculture to transportation systems and environmental monitoring—illustrates the broad impact of IoT technologies across multiple domains. At the same time, the contributions highlight ongoing challenges related to scalability, interoperability, security, and efficient data processing.
We hope that this Special Issue will stimulate further research and collaboration in the field of IoT architectures and contribute to the continued development of intelligent, interconnected environments.
Acknowledgments
The guest editors wish to thank all the contributing authors, the reviewers for their professional and valuable help with the review assignments, and the exceptional editorial support from the Future Internet journal at every stage of the publication process of this Special Issue.
Conflicts of Interest
The authors declare no conflicts of interest.
References
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