Welcome to the SCoRe Lab Google Summer of Code (GSoC) 2019 project ideas page. We are a dynamic and enthusiastic nonprofit research group pioneering in Internet of Things (IoT), Embedded Systems, Computer Security, Software Tools and 'Wireless Adhoc and Sensor Networks' and is one of the best groups in South Asia. This is the 4th time that we are participating in the GSoC, we will use this page to develop possible project ideas that have on the above mentioned areas. Please note that anyone who is interested can participate in this process. You do not have to be a GSoC student or mentor to suggest possible project ideas. You can also talk to us about possible project ideas and we are happy to improve or heip you with them. Please keep in mind that projects need to be realistically something that is able to be functionally completed by a student working full time for about eight weeks. Thanks!
Mailing list: score-community@googlegroups.com
Gitter Channel: https://gitter.im/scorelab/
There are some important guidelines to submit ideas, please read these carefully before adding your ideas;:
“The recent decade has witnessed the birth of social media ecosystems that brings social organizations, media content and various stakeholders together, and now it appears significant advantages of comprehensiveness, diversity and wisdom that provide users with higher quality of experiences. Meanwhile, social media ecosystems suffer from security, privacy and trustworthiness threats. How to leverage the power of intelligent crowds to improve the ecosystem’s efficacy and efficiency, as well as ensure its security and privacy become burning and challenging issues.”
Expected Results: This project is to implement a reactive UI interface to show news-items published in low-credible web-sources (specially in Sri Lanka). Also, there should be a component to seek the opinion of volunteers about the veracity of published claims. This will help to spread the true-accuracy of the claims across a broad community, and create a socially-clean echo-chambers.“The recent decade has witnessed the birth of social media ecosystems that brings social organizations, media content and various stakeholders together, and now it appears significant advantages of comprehensiveness, diversity and wisdom that provide users with higher quality of experiences. Meanwhile, social media ecosystems suffer from security, privacy and trustworthiness threats. How to leverage the power of intelligent crowds to improve the ecosystem’s efficacy and efficiency, as well as ensure its security and privacy become burning and challenging issues.”
Expected Results: This project aims to implement the back-end of the Fact-checking platform mentioned in Project 1. This will be a NodeJS API that will serve for the requests of the React frontend. The scope of the project also includes, writing unit tests for the endpoints and making a documentation.As of now Bassa is only capable of downloading files from URLs, magnet links but still file upload feature is something which is missing for version 1 release. Also, with having a lot of files and user activity on Bassa, file management should be implemented. For this task, you have to implement file upload feature in Bassa and have to implement file ACLs as it’s core feature.
Expected Results: At the end of your summer, we expect that you will able to make file management as good as Google Drive or any personal file storage systems. Also, users should be able to share their local files on Bassa by uploading it to server.Right now, we have some shell scripts to install bassa in some environments, We need to complete them and make installing Bassa an easy task. Users should be able to install bassa on Debian(apt/apt-get) based, Arch(pacman) based and CentoOS(yum) based Linux OSs. Currently, the shell scripts can identify the different environments and use the correct installation script. Second part of this project is to bring 'aria2c' into docker environment. RIght now, 'aria2c' runs on system environment which we want to run as a docker container. Then complete the Kuberneted scripts to deploy all these dockers on a Kubenetes cluster.
Expected Results: At the end of your summer, we expect that you will make Bassa installable on any Linux based OS. Also, aria2c will run as a separate service in Kubenetes cluster.Bassa is built with AngularJs, Python, Flask, Gulp, Bower and more. Nowsince the requirements re finalized and we are sure of the features, we are thinking moving out of MVP to s stable release. However, right now, we are on AngularJs which is not much supportive. So we want to shift the whole codebase to React, ideally to the latest version of React. So the things we want to bring with React is that;
Currently, Senz server is implemented in scala and it uses mongodb as the database server. Implement a admin panel to let the users to create projects in the server and control their devices from the web interface.
Expected Results:Implement a Node.js module to use in node.js applications to give the ability to act as a Senz device and communicate with the Senz server. The module should work as a message parser between the application and the server.
Expected Results: At the end of your summer, we expect that you will create a node.js module.. And users should be able to install and use the module in their node.js projects to communicate with the Senz server.The requirement for the project originated with the need to label thousands of images of elephants. However the project was generalized to label not just elephant images, but any animal in general. The web application should allow the users to to upload batches of images and classify them. It will also have the features to run classifications against a trained model.
Expected Results:The requirement for the project originated with the need to label thousands of images of elephants. However the project was generalized to label not just elephant images, but any animal in general. The web application should allow the users to to upload batches of images and classify them. It will also have the features to run classifications against a trained model.
Expected Results:Dunner is a task runner tool like Grunt but used Docker images as CircleCI does. You can define tasks and steps of the tasks in your `.dunner.yaml` file and then run these steps with `Dunner do taskname`. We have several features planned in our road map, we need you to complete them one issue by one. See the list of features planned for v0.1 and v1.0 below.
TensorMap will be a web application that will allow the users to create machine learning algorithms visually. TensorMap will support reverse engineering of the visual layout to a Tensorflow implementation in preferred languages. The goal of the project is to let the beginners play with machine learning algorithms in tensorflow without less background knowledge about the library.
Expected Results:Since DroneSym is an open source application supporting users to track their drone fleet, we have to even provide options to plug in other open source alternatives for firebase. To support users to be able to scale and use the other best, open source and cost effective resources. No doubt, Firebase is one of the best option for realtime databases, auth etc. but it's not so scalable when coming to cost effectiveness. We should definitely come up with a solution and design a model to provide plugin options to at least two other alternative to Firebase.
Expected Results:Currently, we are using the generated jHipster UI for OpenIoE. We need to implement a customized user interface for providing a better user experience. Angular or React can be used.
Expected Results:Currently, OpenIOE does not implement any security mechanisms for publishing or subscribing to any registered sensors in the backend. In order to support more clients, MQTT authentication and GUID based URL routing can be used.
Expected Results:Implement an analyzing framework which can provide users important information about Ethereum platform. This must utilize existing GraphQL schema to answer the queries. Eg;
Chainkeeper is a web-based application which can be used to retrieve Bitcoin blockchain data via API support from BlockSci core blockchain data. In analytics perspectives, this approach is highly inefficient due to some constraints. Therefore, needs to build a library for ChainKeeper which acts as data and analytical interface for blockchain to retrieve relevant data by writing queries. There should be blockchain supportable classes such as Blockchain, Blocks, Transactions, Input, Output and Address with range support. This library needs to support python with more optimization techniques.
Expected Results:Bitcoin blockchain is a huge data structure with 180+GB in size. Due to this huge size available Bitcoin parsers take several hours to parse the entire blockchain. As an example BlockSci parser takes 11 hours with an 8GB cache. Because of that most of the available Bitcoin parsers are inefficient on memory constrained devices. The goal of this project is to design and implement a Bitcoin parser(may support forks of Bitcoin as well) which can use available memory efficiently to reduce blockchain parsing time on memory constrained devices.
Expected Results:Androphsy(OpenMF) is an opensource forensic tool for Android smartphones that helps digital forensic investigator throughout the life cycle of digital forensic investigation. Services provided by Androphsy includes.