Today’s vehicles and on-road infrastructures are equipped with a large number of sophisticated sensory devices. These sensory devices are capable of monitoring and providing data pertaining to vehicle status, real-time traffic conditions, traffic incidents, and road crashes. Urban commuters are also carriers of sensors embedded in their mobile devices. We are deluged with a massive pool of data that has the potential to increase our understanding of our social behaviours in the transportation network. This will assist in the design of effective persuasive technology on the road to monitor and target voluntary travel behaviour change in order to support road safety, sustainable transportation, and compliance to traffic regulations. We explore the integration of mashup, knowledge discovery, business intelligence, and context-aware analysis in order to analyse the requirements for designing adaptive mobile mashups. We introduce the notion of ADAptive Mobile Mashups (ADAMM) and discuss the potential ADAMM applications for effective persuasion on the road.
@inproceedings{DBLP:conf/aina/Salim10,
author = {Flora Dilys Salim},
bibsource = {dblp computer science bibliography, https://dblp.org},
biburl = {https://dblp.org/rec/conf/aina/Salim10.bib},
booktitle = {24th IEEE International Conference on Advanced Information Networking
and Applications Workshops, WAINA 2010, Perth, Australia, 20-13
April 2010},
doi = {10.1109/WAINA.2010.32},
pages = {7--11},
publisher = {IEEE Computer Society},
timestamp = {Wed, 16 Oct 2019 14:14:48 +0200},
title = {Towards Adaptive Mobile Mashups: Opportunities for Designing Effective
Persuasive Technology on the Road},
url = {https://doi.org/10.1109/WAINA.2010.32},
year = {2010}
}
© 2021 Flora Salim - CRUISE Research Group.