The Google Summer of Code 2020 is just about over. During the summer, I investigated improving different aspects of the enviroCar Android app. It was a very amazing learning experience. In this final blog post, I’d like to wrap up and summarize my achievements during the second half of the Google Summer of Code 2020.
It’s been some fun time working on the enviroCar Android App. In this midterm blog post, I will give an overview of the achievements I’ve reached since the start of the coding phase to the work done until the start of the midterm evaluation.
The overarching goal of the project is to improve the car selection process in the enviroCar Android app by integrating previously defined datasets of vehicles. This is app side implementation. For more information about this project, feel free to read the introductory blog post. The following blog post highlights the core tasks and achievements during the first four weeks of this project.
During Google Summer of Code 2020, I will be working on an enviroCar Android app, which is one of the 52° North GSoC projects. The project is based on sustainable mobility. The main goal of the enviroCar app is to collect track data and analyze data to reduce the costs of running a car and to advance effective traffic planning.
The question is, is this data dependent on the car type? Of course yes! The data is fully dependent on the car type because of different engine displacement and power, which in term lead to different CO2 emissions. Currently, enviroCar app is flexible for creating artificial types of cars with user-defined attribute values, like adding engine displacement and power value to any undefined or nonexistent value.
Currently, the Android application for enviroCar can record tracks only when it is connected to the OBD-II adapter through Bluetooth. The enviroCar app will be of no use to the user, if he/she does not have a working OBD-II adapter or if Bluetooth is not working on the user’s mobile phone. This limits the usage of the app to a great extent. The main goal of this project is to add plain GPS-based recording of a track to the enviroCar Android application. This will increase the usability of the enviroCar app and simultaneously increase the collection of data on the enviroCar server. It is also equally important to automate the GPS-based track, for which Activity Recognition features can be used.