Journal Issues

Abstract- Today's real-time energy monitoring systems have highly complex structures that require the integration of heterogeneous and high-volume data sources such as numerous IoT devices, weather services, and energy consumption databases. The success of these systems depends not only on collecting and analyzing data but also on transforming this data into meaningful information and integrating it into decision support mechanisms. This study demonstrates how the Domain-Driven Design (DDD) approach provides an effective solution for managing this complexity. Within the scope of the study, how data from sensors and external services can be modeled under a "universe" is addressed together with DDD's Ubiquitous Language principle. This approach provides conceptual integrity between technical teams and business units in the energy sector, contributing to the system being consistent and sustainable at both design and user interface levels. Additionally, through Bounded Context structures, complex domain knowledge is divided into manageable parts, and multiple data sources are made meaningful through Rich Domain Model. In the implemented real-time energy monitoring system scenario, raw data from IoT devices and information from external weather services and prediction algorithms were processed holistically; intuitive and decision-oriented data presentation was provided with a user-friendly dashboard interface. In this process, thanks to the modeling flexibility offered by DDD, system components have achieved a reusable, sustainable, and extensible structure. In conclusion, in complex and multi-stakeholder areas such as energy management, the Domain-Driven Design approach offers strong advantages in terms of meaningful data processing, system design, stakeholder communication, and user experience.

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