Multi-thematic Real-time Sensing of Cities

1. Multi-thematic Real-time Sensing of Cities Ms. Leonie Troy under the supervision of Dr. Ronan Farrell, National University of Ireland Maynooth Email: ltroy@eeng.nuim.ie 3. Car park Data Analysis and Results 1. Objective • Data for eleven car parks was captured and analysed to view and predict future trends. • This graphs below depict the fullness of the car parks over a time period (09:00 – 13:00) on Wednesdays and Thursdays in July. • From the graphs it can be seen that similar patterns arise at a given time period for all four graphs. • This technique was applied to car parks over a number of weeks during June and July – all yielding the same results. • From this predictions can be made towards the fullness of car parks at a give time on certain days. • The same analysis was applied to the car parks for weekends but as the trends of the graphs showed no correlation. The main objective of this research is to contribute towards a “Smarter Dublin” by the exploration of different city-wide datasets. The focus is on moving towards a sustainable future with regard to road traffic, environmental conditions and citizen activity. This work will examine the novel application of clustering of datasets and modelling techniques to predict future trends. The central theme of this research is the interoperability of datasets which would otherwise be disconnected in time and space. This project proposes to explore the challenges of sensing a city, using a variety of existing in-situ sensors and potential new deployments. This project will engage with data collection, spatial data analyses, data interpretation and data feature extraction and visualization. 2. Interoperability • There is an increasing need to develop systems by combining components that are written in different languages that can run on different kinds of machines (1). • Interoperability allows for Geographic Information Systems (GIS’s) to work with each other the data needs to be shared and the systems need to be interoperable. Interoperability will also allow other data to be integrated into a system in the future. • According to (2) the three aspects of interoperability involve: • 1. Technical - linking computer systems, defining interfaces and data formats. • 2. Semantic - ensuring that the information being exchanged is understandable by all users. • 3. Organizational - allowing the processes to cooperate and ensuring • that the architectures are in place to support the data. • The advancement of new technologies have lead to the further investigation • into interoperability. In previous years interoperability would have been compromised by slow processing power of a PC, no standard interchange file formats, slow speed Application Programming Interfaces (API’s) and small database systems. • Some of the interoperability standards include [3], [4]: • IEEE • Organization for the Advancement of Structured Information • Standards (OASIS). • Semantic Web • International Organization of Standardization (ISO) • American National Standard Association (ANSI) • Group on Earth Observations (GEO) • Open Geospatial Consortium (OGC) • World Wide Web Consortium (W3C) 4. Conclusions and Future Work • This work will examine the impact of data capture and transport on data quality, timing, and spatial uncertainty for different data sets, extrapolate from available data to minimize time and space uncertainties. It will investigate novel clustering methods making joint use of geographical proximity, spatial interaction, and network-induced similarities to uncover relationships (community structures) in temporally evolving networked spatial data. This project will engage with the spatial data analysis and visualisation activities. • Future Work includes: • Modeling the relationships between the data. Develop suitable algorithms that can highlight events, anomalies and information that could be extracted from the data i.e. what is the data telling us. • Explore interactions between different types of data e.g. waste, water, weather and cell phone data. Analyse tools that allow cross correlation for data sets with different spatio temporal characteristics. • Provide outputs to represent the data. Develop tools to enhance functionality and allow multiple types of data to be web accessible. • Identify potential commercial opportunities through the active research with • the partnership company/companies. References [1] W. R. R. Jack C. Wileden, Alexander L. Wolf and P. L. Tan, “Specification Level Interoperability,” 1991. [2] J. G. Alejandra Cechich, Lorenzo Madrid and J. Kesan, “Interoperability Frameworks for Electronic Governance - Panel Discussion,” Available online at: portal.acm.org. Last visited on 7th April 2010, 2008. [3] A. Fioravanti, G. Fico and M. Arredondo “Integration of Heterogeneous Biomedical Sensors into an ISO/IEEE 11073 Compliant Application ”, 2010 [4] A. Woolf, R. Cramer, M. Gutierrez, et al. “Standards-Based Data Interoperability in the Cimate Sciences ”, 2005. Research presented in this poster was funded by a Strategic Research Cluster Grant (07/SRC/I1168) by Science Foundation Ireland under the National Development Plan. The authors gratefully acknowledge this support.