Dublin City Council

About: Dublin City Council is a government organization based out in Dublin, Ireland. It is known for research contribution in the topics: Crowdsourcing & Handover. The organization has 31 authors who have published 31 publications receiving 607 citations. The organization is also known as: Comhairle Cathrach Bhaile Átha Cliath.

Modifying pedestrian behaviour

Abstract: The paper reports on research using a new type of pedestrian waiting countdown timer to influence pedestrian behaviour at signalised pedestrian crossings in Dublin. The aim was to evaluate the impact of the timers on pedestrian crossing behaviour and in particular to see if it had any impact on the number of illegal crossings (during red man--do not walk signal). The timers inform the pedestrian how many seconds they have to wait until the green man appears. Two surveys were used to evaluate the impact: an attitude survey to evaluate the perception of the users and a video survey to estimate quantitatively the impacts on pedestrian behaviour but also to evaluate the awareness levels of the pedestrians towards the countdown timers. Some of the results include observance of more compliant behaviour by females and that pedestrians tend to overestimate their waiting time. Before the timers were installed 65% of pedestrians started to cross during the green man and amber phases but this rose to 76% after the timers were installed.

Heterogeneous Stream Processing and Crowdsourcing for Urban Traffic Management

Abstract: Urban trac gathers increasing interest as cities become bigger, crowded and \smart". We present a system for heterogeneous stream processing and crowdsourcing supporting intelligent urban trac management. Complex events related to trac congestion (trends) are detected from heterogeneous sources involving xed sensors mounted on intersections and mobile sensors mounted on public transport vehicles. To deal with data veracity, a crowdsourcing component handles and resolves sensor disagreement. Furthermore, to deal with data sparsity, a trac modelling component oers information in areas with low sensor coverage. We demonstrate the system with a real-world use-case from Dublin city, Ireland.

Intelligent Urban Data Monitoring for Smart Cities

Abstract: Urban data management is already an essential element of modern cities. The authorities can build on the variety of automatically generated information and develop intelligent services that improve citizens daily life, save environmental resources or aid in coping with emergencies. From a data mining perspective, urban data introduce a lot of challenges. Data volume, velocity and veracity are some obvious obstacles. However, there are even more issues of equal importance like data quality, resilience, privacy and security. In this paper we describe the development of a set of techniques and frameworks that aim at effective and efficient urban data management in real settings. To do this, we collaborated with the city of Dublin and worked on real problems and data. Our solutions were integrated in a system that was evaluated and is currently utilized by the city.