PKTraffic specializes in deep public record search of traffic related data and events to provide expert analysis and support. The business model of the company is to provide insights in traffic incidents through post-processing to support safety and justice to traffic crash victims. Traffic related incidents is analyzed through an intelligent application which makes it easy to explore, analyze and visualize.

I am one of the owners and CTO (chief technology officer) of the company. I developed the front- and backend parts of the IT Solutions enabling the business model. The frontend part includes a program which can visualize data and sort through traffic crashes and the website pktraffic.com. The backend of the project includes managing a server which records and processes a large amount of data and camera footage. My main responsibility is to assure well working IT solutions and that the data is secure and of excellent quality.

I developed a mass image editing program for the Personnel Foundation of the Swedish postal service (postnordplus.com). The objective of the program is to mass edit images which requires changing the width and height, brightness, sharpness, vignette, vibrance and a bit more. The program applies all changes to the selected images. The program also included a version where the user can go through an image at a time a changing the image properties. The program enables the PostNordPlus employees to save large amount of time, specifically for images that will be uploaded to a website.

I was responsible to develop both the front- and the backend of this program, which includes a functionality for editing and working with images. I was also responsible for training of the staff using the program and I can on request support the end users when needed.

MovieBoxDB is a website that showcases movies. It is possible to search for a specific movie and observe information about that specific movie such as actors, release date, genre, score etc. The site allows users to add shows to a watchlist and a favourites list where they can store their favourite movies. The site also has score for each show, and it is possible to sort through all movies depending on multiple factors such as genre, language, release dates, region and more. The way that users are able to store their movies is by creating an account and logging in. This gives them access to edit different aspects of their profile such as bio, profile picture and name. Creating an account also gives the user access to the MovieMatcher, which is a game inspired by the dating app "Tinder", where the user swipes in one of the four directions for movies depending on whether or not they want to skip, add to favourites, add to watchlist or see more info about the movie.

Project Structure

We are following the React structure for files, which means that we utilize a public folder where we store all our imgs and our index files. Then we have a source file where our main files are, such as index.js which is our rendering module where we use ReactDOM to render. In app we render each presenter, where we use react component router. Our project follows the MVP-structure: In our source folder we have the folders css, which contains all the css files for all styles for all pages as well as the earlier mentioned index.js. and App.js files. The source folder also contains a js folder that houses all our presenters, the views folder that holds all the views for all pages. Lastly the js folder also contains general files like apiFetch, model and firebaseConfig etc.

The goal is to create an application that can through machine learning predict upcoming weather / weather phenomenon’s. The application will receive its data from a simulated IoT-device that can measure certain weather parameters such as temperature, atmospheric pressure and humidity.

This project was develop using Microsoft Azure products. The products that were used in the project are Virtual Machine (Ubuntu), SQL Database and Server, App Service (website hosting), IoT Hub (intermediate point between IoT device and database) and Storage Account.

The weather prediction application will be used by researchers and regular people. The application will be able to give the stakeholders insight in upcoming weather using a prediction model. We believe that the prediction model that will be created will be able to predict the upcoming weather accurately. But as we know our product won’t be able to predict the weather better than other weather stations. Because of this our goal is not to be better but rather offer a solution. That solution is that most weather websites only offer weather reports for entire cities. Our product will be able to offer precise weather data at a specific position using the IoT device. This will give the user a chance to choose a location where to track and predict the upcoming weather.

The purpose of the project is to automatically upload twitch clips to YouTube using both Twitch API and googles API. On the website twitch a user can “clip” a part of a livestream and upload it to the platform. These clips often get a lot of attention and attracts millions of views. With this solution using twitch API and YouTube dl makes it is possible to download popular clips from the platform and uploading the clips to YouTube using their data v3 API.

This program is a simplified version of the image editor where it is possible to automatically run for ever where it downloads images from unsplash.com, edits them to a specific width and height and adds a logo to it. It than adds a quote and a logo to the image. The image is than uploaded to Instagram. The project objective is to automate an Instagram account which would be able to run indefinitely and keep upload content which its followers could enjoy.

TvShowNetwork is a website where a user can sign up and write their own reviews/articles on film and the TV industry. Starting a new blog can be hard, especially with competing against sites that post 5-10 articles a day. Climbing the Google search ladder is harder than ever. By writers joining together they can quickly beat the bigger article websites. The objective of the project is that the writers receive a share of what their article websites have received in google AdSense. During the first year of the website launching, it had attracted approximately 166,000 visitors.

I have developed the business model, the website, and the backend of the site which includes keeping track of which and how many visitors each article author gets. The project also includes optimizing the website for SEO (search engine optimization).