Tukko - Traffic Visualizer
WIMMA Lab 2023 IoTitude created Tukko - Traffic Visualizer, an assigment given by Combitech. Tukko utilizes data from digitraffic API, and improves upon it by unifying the scattered info across multiple endpoints into our own much simpler API. We also gather data long term, which can later be shown to users to check for recent anomalies.
This data is then shown in a React based user interface, with mapping tools by Leaflet utilizing multiple plugins such as Geoman and Cluster markers. Utilizing custom icons, popups and tooltips, Tukko strives to convey information intuitively. For the more interested users, more in depth information is available. Development for Tukko followed best practices by utilizing a very strict ruleset maintained by Typescript and ESLint. Tukko is a complete product, but our team had many ideas left unfulfilled due to time constraints.
Demo video
Website
Github for frontend
Github for backend
Our stack:
Repositories for the frontend and the backend with instructions on how to set up your production or development environment are available on GitHub.
Quick Menu
| Link | Description |
|---|---|
| Release Note | Version 1.5 chickpea_botatte-release |
| Requirement Specification | The wide requirement specification for Tukko |
| Test Results | Test Cases and Test Results |
| Backend Swagger | Documentation for the Backend API |
| Team Introduction | Introduction of team IoTitude 2023 |
Assignments for 2023
Our main assignment for the summer is a project commissioned by Combitech Oy. We are developing an open-source service called Traffic Visualizer, which utilizes public traffic APIs, particularly Digitraffic. This service provides data visualizations on a map, allowing users to select vehicle types and various timescales.
In addition, we have created the SKILL-db API, which integrates with the SKILL (Skills Framework for the Information Age) skill framework data. The framework data is stored in a PostgreSQL database, and other projects can access it through REST requests.
The technologies employed in our project include:
- Tukko - Traffic Visualizer: React, TypeScript, NodeJS, Docker, Kubernetes, CI/CD GitLab, Vite, REST, Leaflet.js, and Digitraffic APIs.
- SKILL-db API: NodeJS, PostgreSQL, TypeScript, Swagger, REST, and Docker.
- Testing: Robot Framework, Selenium, JMeter etc.
By utilizing these technologies, we aim to deliver a robust and user-friendly traffic visualizing service and ensure smooth integration with the skill framework through our SKILL-db API for Skill Collector
Team
| Name | Description | Company / entity Task Responsibilities | |
|---|---|---|---|
| Reima Parviainen | Team Leader | IoTitude / Lead the project and handle test planning | |
| Justus Hänninen | Junior Developer | IoTitude / Backend, TypeScript, SKILL-db API | |
| Hai Nguyen | Junior Developer | IoTitude / Backend, API, Data visualization, GitLab Pipeline | |
| Ilia Chichkanov | Junior Developer | IoTitude / Backend, SKILL-db API | |
| Olli Kainu | Junior Developer | IoTitude / Frontend | |
| Otto Nordling | Junior Developer / Tester | IoTitude / Testing | |
| Alan Ousi | Junior Developer / Tester | IoTitude / Testing |
