# A Synergistic Elixir-EDA-MQTT Framework for Advanced Smart Transportation Systems
## 3 Architecture Design
### Key Components in the Proposed EDA-MQTT Framework  
The proposed framework using EDA and MQTT broker for smart transportation comprises five key components, as shown in Figure 1.  
* EMQX Broker: The core messaging hub facilitating event-driven communication. It receives events from various clients (user interface client, vehicle client, traffic management service, location and infrastructure monitoring service) and is responsible for accurately forwarding these messages to other clients that have subscribed to them.
* User Interface Client (edge computing component): Serves as the event producer and event consumer. It represents the interface for all end-users, from pedestrians to vehicle operators. It publishes events like traffic congestion reports and listens to updates like route optimizations or transportation schedules.  
Figure 1: The components in the proposed framework.  
Vehicle Client (edge computing component): Mainly serves as the event producer. It caters to all transportation modes, from cars to buses in the edge. This component handles transport-specific events like maintenance alerts, vehicle statuses, and location data.
* Traffic Management Service (hybrid cloud and edge computing component): This service functions as a critical decision-making engine within our framework, operating both at the edge and in the cloud to leverage the strengths of each environment.
* Edge Deployment: At the edge, the Traffic Management Service focuses on real-time data processing and swift decision making. This proximity to the data sources allows for immediate responses to dynamic traffic conditions, such as adjusting traffic signals to alleviate congestion or responding to unexpected incidents like accidents or road closures. The edge-based component ensures minimal latency and maximizes the responsiveness of the traffic system.
* Cloud Deployment: In the cloud, the Traffic Management Service undertakes a more comprehensive role. Utilizing the cloud's extensive computational power and vast data storage capabilities, it conducts complex analyses of traffic patterns, predictions of future trends, and development of long-term traffic strategies. The cloud-based service also performs validation and verification of the decisions made at the edge, ensuring overall system accuracy and reliability.
* Location and Infrastructure Monitoring Service (cloud computing component): This service continuously monitors events published by edge servers, facilitating a global analysis of the accumulated data. It rapidly responds to and computes related services, integrating insights from across the network. Additionally, this service is responsible for storing data, ensuring that valuable information is retained for long-term analysis and strategic planning.  
Compared to other architectural paradigms, our EDA stands out for its event-focused and asynchronous nature. It contrasts with synchronous patterns like model-view-controller (MVC) and modularity-emphasizing microservices, which can sometimes involve synchronous calls. Our architecture also shares parallels with the event sourcing pattern but emphasizes reactive event handling rather than mere event logging.  
Capitalizing on EDA's inherent strengths and MQTT protocol, our architecture strives for scalability, instantaneous responsiveness, and fault resilience, making it suitable for the ever-evolving needs of smart transportation systems.