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Code: AC1
Title: Analytics and visualisation of public transport in Ireland
Various APIs exist that provide live and forecasted data about public transport modes in Ireland (buses,
trains, Luas). This project will explore how this data can be captured, analysed, and presented in a
dashboard for analysing services, exploring trends, and developing insights.
Proposition: continue traintracker esque project, redo from scratch but include buses, trains, luases
Code: KY4
Title: Data Dashboard
Description: This project will initially identify a required data service (e.g., citizen service, energy
consumption service, food sourcing service, marine service etc.) and provide an interactive dashboard
for public access and use of this data. The project will identify the relevant data required and develop
an effective data management service for accessing and querying this data, and design a dashboard
to visualise, interact with and explore this data.
Code: MM04
Title: Discrete Simulation of Irish Elections
The Irish general election process is complex by international standards, with a single transferrable
vote and multi-seat constituencies with differing numbers of seats. As such, it poses an interesting
challenge for simulation. Some of our past research in probabilistic data mining could be adapted for
this application.
Code: KY5
Title: Language Learning (or other education) App
Description: This project involves the planning, design, implementation and testing of a mobile (or Web-
based) app to support language learning for a particular group (e.g., specific age cohort casual holiday
makers language for business needs, foreign students etc.). Initial research will identify other apps in
this space as well as best practice language learning pedagogy, and enable identification of the core
requirements. The app will then be iteratively designed (incorporating auditory elements, challenges
and other gamified elements etc.) and tested.
Code: MS5
Title: Software Synthesiser
Synthesizers use various methods to generate electronic sounds. Among the most popular waveform
synthesis techniques are subtractive synthesis, additive synthesis, wavetable synthesis, frequency
modulation synthesis, phase distortion synthesis, physical modelling synthesis and sample-based
synthesis. The aim of this project is to prototype a software synth, based on the aforementioned
methods or any suitable combination, either as a standalone application, or integrated into dedicated
hardware like for example a Raspberry Pi.
Code: MA1
Title: Secure File Sharing System Using Blockchain Technology
This project will create a platform where users can securely upload, share, and access files. Key
features include user authentication with public-private key pairs, file encryption for confidentiality,
blockchain integration for tamper-proof transaction logging, fine-grained access control, and
cryptographic hash functions for file integrity. Decentralized storage solutions like InterPlanetary File
System (IPFS) will ensure file availability and redundancy.
Code: MA4
Title: Facial Expressions Recognizer and person tracker
The three most usable expressions will be recognized in this system, such as whether the person is
smiling, sad, or shocked. Raspi Camera will be used to get live images and then the software system
is designed first to detect and read a person’s face. The system then computes o various facial
parameters of the person’s face. Upon detecting and registering these parameters, the system
compares these parameters with default expressions for human sadness, smile, and human
expressions. Based on these statistics the system concludes the person’s emotional state. And also
we can track the person’s identity too by their names.
Code: MA5
Title: Image forgery Detector using Machine learning/Hashing
As social networking services have grown in popularity, the volume of image data has increased.
Furthermore, image processing software such as Adobe Photoshop has made it possible to edit
images. Inciting violence and spreading false information can be accomplished with doctored images.
This image forgery detection project allows students to detect even the slightest signs of forgery in an
image. Two methods can be deployed in this project. (1) image classification through machine learning
algorithms, and (2) hashing technique can be implemented to check that either image is forged or not.
Code: MA10
Title: Passcode generator and strength checker tool
In cybersecurity, strong passcode generation is key to surpassing guessing attacks on your accounts.
Passcode strength is one of the essential elements. This passcode must include alphabets, digits, and
different symbols. In this project, students will generate passcodes using different images, too. You
would also create a tool to check its strength, informing you if it is secure to utilize.