ODOT Event Streaming Platform: Real-Time Transportation Data Integration
Ohio’s vision for an Event Streaming Platform (ESP) was to create a real-time transportation data platform that connects disparate data sources statewide, enabling faster crash detection, earlier warnings for dangerous road conditions, and better insights when decisions matter most. At its core, the ESP was designed to modernize how transportation data is collected, shared, and applied statewide.
Trihydro led the development of the ESP and focused on building a real-time data exchange that allows the state to publish and consume real-time data under one platform without having to go through extensive code changes for each new data set. These efforts now provide Ohio Department of Transportation (ODOT) with near real‑time access to transportation data and the ability to transform that data into actionable tools that support faster response, improved safety, and informed decision‑making.
How ODOT’s Event Streaming Platform Works
Trihydro, in collaboration with Etch GIS, designed and developed ODOT’s ESP to bring transportation data from multiple sources into a centralized environment where it can be accessed and shared in near real time. Instead of relying on manual data requests or building custom connections for each new dataset, the ESP allows approved data sources to continuously publish information to the platform.
Users can then discover and subscribe to the data streams they need and choose how to use that information, including through dashboards, maps, databases, and other applications. The platform manages the flow of data behind the scenes, making it easier to connect new data sources and deliver current information to the people and systems that rely on it.
By streamlining how transportation data is shared and accessed, the ESP reduces technical and administrative barriers while giving ODOT and its partners a scalable foundation for traffic operations, safety analysis, and future transportation applications.
Real-Time Transportation Data Integration
Trihydro designed the ESP to be adaptable as transportation needs, data sources, and technologies continue to evolve. Instead of building a system that only works for a fixed set of data inputs, the platform was designed so that new data sources and future applications can be added without rebuilding the system.
To support this flexibility, Trihydro developed the underlying system architecture that allows users to publish data, discover available datasets, consume data sets, and visualize information in a consistent way. The team also implemented the technical infrastructure that supports secure, reliable system operations and designed a user interface that allows staff to configure and manage data streams through a web-based environment.
Transportation Data Access and Discovery
The ESP includes intuitive tools that allow ODOT staff and external partners to manage data connections through simple configuration screens rather than custom software development. As new data sources become available, they can be added to the system with minimal effort, and the platform automatically adapts to support them.
For users who are primarily interested in accessing data, Trihydro developed a Discovery Dashboard that makes it easy to search for available data streams, understand how they can be used, and subscribe to those streams. These tools support broader access to transportation data while reducing administrative effort and technical barriers.
Real-Time Data for Crash Prediction and Mitigation
Building on the ESP foundation, Trihydro supported ODOT’s initial safety analytics applications, focused on crash detection, prediction, and mitigation. Beginning in 2024, an effort led by Etch and supported by Trihydro contributed to a multidisciplinary effort to develop machine-learning models that use both historical and real-time ESP data to assess the probability of crashes on specific roadway segments.
The models integrate data from multiple sources, including vehicle manufacturers, navigation application providers, and vehicles equipped with cellular vehicle-to-everything (C-V2X) technology. The project demonstrated that combining live data streams with ODOT’s existing datasets can support proactive safety strategies, helping agencies respond earlier and deploy measures to reduce crash risk.
Improving Transportation Safety with Real-Time Data
Through the development of ODOT’s Event Streaming Platform and its initial safety analytics applications, Trihydro delivered a flexible, statewide foundation for real-time transportation data sharing and analysis. The platform enables public and private stakeholders to access, subscribe to, and apply transportation datasets without manual data requests, supporting faster insights and more responsive operations.
By pairing the ESP’s live data streams with historical transportation datasets, Trihydro helped demonstrate how real-time analytics can be used to move beyond reactive crash response toward predictive safety strategies. Early modeling efforts showed that integrating vehicle, navigation, and C-V2X data can reliably estimate crash risk on specific roadway segments, allowing agencies to identify and mitigate safety concerns before incidents occur.
Together, these efforts position ODOT to expand advanced transportation and safety applications statewide. The scalable, data-driven architecture supports future use cases in traffic management, operations, and business intelligence, while establishing a framework for continuous improvement as new data sources and technologies are introduced.
