Sensor Grid: Integration ofWireless Sensor Networks and the Grid
LCN '05 Proceedings of the The IEEE Conference on Local Computer Networks 30th Anniversary
Surface street traffic estimation
Proceedings of the 5th international conference on Mobile systems, applications and services
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Bigtable: a distributed storage system for structured data
OSDI '06 Proceedings of the 7th USENIX Symposium on Operating Systems Design and Implementation - Volume 7
A framework of sensor-cloud integration opportunities and challenges
Proceedings of the 3rd International Conference on Ubiquitous Information Management and Communication
VTrack: accurate, energy-aware road traffic delay estimation using mobile phones
Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems
Combining cloud computing and wireless sensor networks
Proceedings of the 11th International Conference on Information Integration and Web-based Applications & Services
ICSNC '10 Proceedings of the 2010 Fifth International Conference on Systems and Networks Communications
Design science in information systems research
MIS Quarterly
Using cloud computing to process intensive floating car data for urban traffic surveillance
International Journal of Geographical Information Science - Data-Intensive Geospatial Computing
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As road transport is a major sector in the economy of different countries of the world, the length of the road network as well as the number of vehicles in it is increasing at an alarming rate particularly in low-and middle-income countries. This increasing number of vehicles causes social and economic problems, like traffic accidents, road congestion and environmental pollution. To minimize these problems, the expansion of the road infrastructure is a possible solution, but its scope is limited due to social, environmental and financial constraints. For each vehicle, efficient utilization of existing road infrastructure is perceived as the best solution, and road surveillance sensor technologies have been used for this for a long time in different countries of the world. But the use of these technologies for collecting real-time data is not sufficient due to their limited coverage, expensive implementation & operation cost, and because their operation is also impacted by climate changes. The surveillance of road traffic systems largely depends on effective handling of real-time traffic data and it is usually data-intensive in nature. The absence of a framework for the integration of cellular networks and cloud computing in support of real-time road traffic monitoring and traffic management activity is a major motivation for this research work. To conduct this research I will employ design science research methodology principles. The outcome of this research will enable to develop road traffic surveillance system with minimum cost using the existing cellular infrastructure and pay-per-use based cloud computing.