One doesn’t have to look too far to see the Digital Divide … it exist right here in New Hampshire, USA.  The effects can be profound.  Lack of high speed infrastructure impacts research, distance learning, business development and a myriad of other benefits that the Internet can provide to needy rural communities.  All one needs to do is travel shy 1 hour north to get a glimpse of the Internet Dirt Road.  High speed Internet is not an option for many communities … it just doesn’t exist.  And carriers will not support it.  Rural America was not “electrified” nor “wired for phones” because of the “free market”.  In the past, if utilities wanted to do business they had to serve the whole state.  What happened?

Perhaps the AWS-3 auctions coming next year might be a solution (http://www.usatoday.com/tech/wireless/2008-12-01-free-broadband_N.htm?loc=interstitialskip) to take this country from the 15th most connected country to the 14th?  –>

http://www.informationweek.com/news/services/data/showArticle.jhtml?articleID=207801621

Note from this article the USA pays far more for Internet than the superior services offered in Europe and Asia.

I recently set up several reading lists on Amazon - check them out here.

Andrew Kun

In our research for our KLAS Project, Mark Taipan and I ran across a few interesting articles on Wi-Fi indoor location systems, specifically ones which utilize RFID. One of the most informative research papers was the Sensor-Assisted Wi-Fi Indoor Location System for Adapting to Environmental Dynamics. This paper dealt with adding RFID sensors to a Wi-Fi indoor location system in order to add accuracy. The researchers realized that Wi-Fi location systems are highly susceptible to accuracy variances due to “environmental changes” (e.g. open vs. closed doors, humans absorbing/blocking the signal, and even to changes in humidity). Therefore the system was tested in various cases, with a radio map created for each. The researchers then added RFID sensors to the system to measure the different conditions (e.g. the humidity, how many doors were open vs. closed, etc.). This data was then used to determine which radio map would provide the greatest accuracy for the system at any given time. Because of this adaptation, the system was able to gain overall better accuracy and was less susceptible to these “environmental changes”.

This idea has helped us better understand the concerns and cautions of working with 802.11 Wi-Fi and the accuracy issues that surround it. We therefore recognize that these are issues for which we will have to deal with and thus we plan on compensating for them, either in the manner that was outlined in this paper, or in some other way.

Matthew Lape