Progress 06/01/09 to 01/31/10
Outputs
OUTPUTS: The objective of this Phase I SBIR project was to demonstrate the feasibility of developing a mathematically sound software algorithm, based on Constrained Optimization (CO), which would accurately suggest tower locations for networks of wireless radios within a given geographical region, using specified radio characteristics and property ownership constraints. A secondary goal was to make that algorithm accessible and useful to inexperienced users from a website. We accomplished these goals by breaking the project into three major task areas: 1) algorithmic development, 2) data gathering and normalization, and 3) integration and user interface (UI) development. Dr. David Aadland of the University of Wyoming Economics Department successfully developed and tested the Constrained Optimization algorithm using Gauss and Wolfram Mathematica, first on sample data and then on data which was successfully compiled during the data gathering phase of the project. The data gathering and normalization tasks were the responsibility of Principal Investigator (PI) Crile Carvey, who utilized the original subset of data provided by the Wyoming Geographic Information Science Center and Albany County, WY to develop a test database with enough detail and variety to test the "edge cases" of the solution. These data were then processed through the CO algorithm for validation. The Mathematica version of the algorithm successfully processed the data and generated sets of tower locations and topographical displays. Progressing to the third task area, the PI developed software routines to feed parameters into, and retrieve results from, the Mathematica "engine". The PI also investigated other methods of performing the CO algorithm by translating it into the C# programming language. Finally, moving into the UI development aspect of the project, the PI evaluated several candidate UI architectures and developed a Silverlight-based implementation that leverages Bing maps to collect user input and display output tower locations (as calculated by the algorithm) on an interactive map. This implementation was published to a prototype website for evaluation. We plan to make this prototype website publicly accessible in the next phase of this project. PI Carvey is involved in preliminary commercialization discussions with Microsoft and Wolfram, and has documented alternative solutions for bringing the finished product to market. PI Carvey will submit a workshop abstract at the "GIS in the Rockies" Conference in September, 2010 and will also present a Poster Session at the conference on this research. PARTICIPANTS: Crile Carvey was the Principal Investigator, responsible for data acquisition, data normalization, User Interface Design and Implementation, and Project Management. David Aadland, PhD, was responsible for the development of the Constrained Optimization algorithm. TARGET AUDIENCES: Not relevant to this project. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.
Impacts
Through this research, we have learned that it is feasible to use a Constrained Optimization (CO) algorithm to generate an optimal set of tower sites across a given geographical region. This makes us confident that a further Phase II will result in a useful software tool to assist with the building out of Rural America's broadband infrastructure. We have found that academically-oriented software tools such as Mathematica are capable of solving our optimization problem, but perform poorly but given large data sets. We have found that Microsoft's Silverlight and Solver products are appropriate software tools with which to develop a commercial product based on the results of our research, and believe that moving the CO calculation to a simpler .NET based calculation engine will mitigate the performance issues. As a result of interacting with rural residents that we came into contact with during the course of our research, we learned not to take anything for granted with regards to public perception of broadband issues. People who have adequate broadband connectivity generally assume that everyone with an email address is equally able to download bandwidth-intensive documents, stream music and watch video. Similarly, those who have poor Internet capacity (satellite, dial-up, or none at all), can be either unaware of, or dismissive of things that they are unable to do online due to their inferior or non-existent connections. We learned that it helps to "show and tell" what broadband offers when talking to people who have been without it. Many rural residents who are employed in urban areas are aware of what they're missing without broadband, but those without non-rural computer access are unaware of specific things they could do with broadband. Those with broadband access "in town" were skeptical that they'd ever be able to participate fully from their rural home computer. Even more striking was to discover the divide between smartphone users and those who cannot use advanced cell phone features due to limited connectivity. In the course of Phase I, we became aware of the potential impact our product could make on wireless cell phone coverage across rural America, simultaneous to its impact on Internet broadband. What our product will be able to do for broadband Internet connectivity, it will also do to enhance wireless cell phone capabilities for those who do not currently have it because of distance from a line-of-sight signal. Indeed, the two media are converging as people use cell phones for data access and use Internet connections for voice. From a practical viewpoint, a cell tower just uses a different kind of radio.
Publications
- No publications reported this period
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