[TAKEN]Intrusion Detection System
Development of an Intrusion Detection System for wearable devices using Federation Learning
Subject: Artificial Intelligence
[TAKEN]AI-Powered Credit Scoring for the Unbanked
Develop an alternative credit scoring system that evaluates creditworthiness for individuals without traditional credit history using alternative data signals such as utility bill payment regularity, mobile phone top-up patterns, social network trust analysis.
Continual Model-based Reinforcement Learning – No longer available
Model-based reinforcement learning (MBRL) is emerging as a powerful paradigm for building intelligent agents capable of operating in the physical world. Most existing MBRL algorithms assume that the environment is stationary, i.e., that its behaviour doesn’t change so that the learnt world model and the strategies than depend on it remain optimal over time. But … Read more
Assessing the Use of Replay for Continual Reinforcement Learning – No longer available
Human imagination allows people both to relive past events and to simulate future possibilities, in some sense, to see the world as it is not [1]. In fact, the ability to simulate events in our minds is also crucial to reliving past events allowing some elements of the event to be memorized and gaps to … Read more
Mitigating Bus Bunching using Reinforcement Learning – No longer available
An ideal bus route would offer highly predictable inter-bus arrival times to travellers, in particular, overcoming the well-known ‘bus bunching’ phenomenon – “I waited ages then three came together!”. There are many sources of variability in journey times such as traffic conditions, the impact of traffic lights, and interference between buses themselves, e.g., queueing at … Read more
Improving Urban Travel-time Reliability with Connected and Automated Vehicles and Reinforcement Learning – No longer available
Poor travel-time reliability (TTR) in our cities means that travel times for the same journey are both highly variable and unpredictable, and also gives rise to similar negative impacts on the environment and the economy as does traffic congestion. Being able to offer a high degree of TTR is therefore highly desirable for travellers and … Read more
Slot-based Motorway Driving for Connected and Automated Vehicles – No longer available
The Research Ireland funded ClearWay1 project is investigating new models of road management is which each vehicle is allocated a so-called ‘slot’ in which to travel for the duration of its journey. Adherence to travelling in its allocated slot ensures congestion-free travel from source to destination for each vehicle (in the absence of unexpected events). … Read more
ML-powered Parking Assistance System – No longer available
Parking in busy locations eg at large-scale events (such as concerts and mass-participation sporting events) or in shopping centres at busy times (eg during ‘Christmas shopping’) often results in traffic congestion in surrounding areas (see, for example, [1], for an extreme example!). This may arise due to vehicles searching for, entering, and leaving parking spaces … Read more
Swarm Intelligence for Travel Time Reliability – No longer available
Poor travel-time reliability, meaning that travel times for the same journey are highly variable and unpredictable, gives rise to similar negative impacts on the environment and the economy as does traffic congestion. Moreover, being able to offer a high degree of travel-time reliability will facilitate the uptake of sustainable road transportation including future public, shared, … Read more
Improving Road Transportation Resilience using LLMs and Agentic AI – No longer available
Mobility is the lifeblood of human connectedness and economic progress, and roads are a critical component of the transportation system for both people and goods. Unfortunately, roads are potentially vulnerable to medium- to long-term disruptions (ie, lasting hours to days) due to extreme weather, infrastructure failures, accidents, maintenance, and unexpected demand all resulting in high … Read more