Major advances in telecommunications and the Internet of Things have given
rise to numerous smart city scenarios in which smart services are provided.
What was once a dream for the future has now become reality. However, the need
to provide these smart services quickly, efficiently, in an interoperable
manner and in real time is a cutting-edge technological challenge. Although
some software architectures offer solutions in this area, these are often
limited in terms of reusability and maintenance by independent modules,
involving the need for system downtime when maintaining or evolving, as well as
by a lack of standards in terms of the interoperability of their interface. In
this paper, we propose a fully reusable microservice architecture, standardized
through the use of the Web of things paradigm, and with high efficiency in
real-time data processing, supported by complex event processing techniques. To
illustrate the proposal, we present a fully reusable implementation of the
microservices necessary for the deployment of the architecture in the field of
air quality monitoring and alerting in smart ports. The performance evaluation
of this architecture shows excellent results.

通过使用物联网的 Web 模式和复杂事件处理技术，本文提出了一种完全可重用的微服务架构，用于智能港口空气质量监测和警报部署，并展示了该架构的出色性能评估结果。

用于实时物联网数据处理的微服务架构：智能港口的可重用物联网方法

A microservice architecture for real-time IoT data processing: A  reusable Web of things approach for smart ports

Designing domain models and software architectures represents a significant
challenge in software development, as the resulting architectures play a vital
role in fulfilling the system's quality of service. Due to time pressure,
architects often model only one architecture based on their known limited
domain understanding, patterns, and experience instead of thoroughly analyzing
the domain and evaluating multiple candidates, selecting the best fitting.
Existing approaches try to generate domain models based on requirements, but
still require time-consuming manual effort to achieve good results. Therefore,
in this vision paper, we propose a method to generate software architecture
candidates semi-automatically based on requirements using artificial
intelligence techniques. We further envision an automatic evaluation and
trade-off analysis of the generated architecture candidates using, e.g., the
architecture trade-off analysis method combined with large language models and
quantitative analyses. To evaluate this approach, we aim to analyze the quality
of the generated architecture models and the efficiency and effectiveness of
our proposed process by conducting qualitative studies.

使用人工智能技术基于需求半自动生成软件架构候选方案，并通过定量分析和架构权衡分析方法进行自动评估和交叉分析，以提高生成架构模型的质量、效率和有效性。