EG is the celebration of the American entertainment industry. Since 1984, Richard Saul Wurman has created extraordinary gatherings about learning and understanding. EG is a rich extension of these ideas – [...]]]> Dan Ariely, a professor of behavioral economics at Duke University, presents examples of cognitive illusions that help illustrate why humans make predictably irrational decisions.

EG is the celebration of the American entertainment industry. Since 1984, Richard Saul Wurman has created extraordinary gatherings about learning and understanding. EG is a rich extension of these ideas – a conference that explores the attitude of understanding in music, film, television, radio, technology, advertising, gaming, interactivity and the web – The Entertainment Gathering

http://www.youtube.com/watch?v=JhjUJTw2i1M

Dan Ariely is the Alfred P. Sloan Professor of Behavioral Economics at MIT Sloan School of Management. He also holds an appointment at the MIT Media Lab where he is the head of the eRationality research group. He is considered to be one of the leading behavioral economists. Currently, Ariely is serving as a Visiting Professor at the Duke University, Fuqua School of Business where he is teaching a course based upon his findings in Predictably Irrational.

Ariely was an undergraduate at Tel Aviv University and received a Ph.D. and M.A. in cognitive psychology from the University of North Carolina at Chapel Hill, and a Ph.D. in business from Duke University. His research focuses on discovering and measuring how people make decisions. He models the human decision making process and in particular the irrational decisions that we all make every day.

Ariely is the author of the book, Predictably Irrational: The Hidden Forces That Shape Our Decisions, which was published on February 21, 2008 by HarperCollins.

http://www.youtube.com/watch?v=VO6XEQIsCoM

Hours into our conversation I was perplexed at the lack of proactive [...]]]> In my last post I put forth the idea of using the unique capabilities and UX of the iPhone to help track defects in railways, which came about after my initial conversations with a friend from the railroad industry.

Hours into our conversation I was perplexed at the lack of proactive monitoring of the today’s bridges used by trains for transport.

Should a uniquely located bridge collapse, an energy crisis could ensue as a result of the coal fields in the northeast/midwest being severed from the southwest.

I looked at several existing methods and solutions used today to address this issue and drew from each to conclude in a refined approach to monitoring the health of railway bridges.

There were basically 3 design considerations which needed to be met:

1. Easy to deploy
2. Low Maintenance
3. Long Term

The system had to be easily deploy-able were an electrician in the field could install the components of the solution. Obviously low maintenance is also key, reducing the total cost of ownership and Long Term reducing the need for personnel to visit these bridges.

Application Requirements:

In order to monitor the health of a structure, vibrations of the structure need to be gathered and analyzed to develop a baseline under normal conditions. Subsequent measurements of vibrations can then be compared to the baseline to determine if an anomaly exists.

To accomplish this requirement sensors (3-axis accelerometers) are placed throughout the span of the bridge collecting data. The frequency components of interest range between 0.25-20Hz, the measurements would need to take place 40 secs before and after the passage of the train and time synchronization between the sensors would also be a factor to take into account.

Existing approaches use technology such as Solar panels to supply power in remote areas, GSM for data transmission, GPS for time synchronization and a star topology for the sensors to communicate to a head node which would collect and transmit the data for analysis.

There are multiple problems here since solar panels are expensive, prone to theft, vandalism and damage; GSM data transmission isn’t always viable when there isn’t network coverage in remoter areas and relying on a head node to collect and transmit the data would be like putting all your eggs in one basket. If the head node failed, the system would stop working.

The techniques I came across with basically fell into 2 categories: Existing bridges and new bridges.

I focused on existing bridges since there are very sophisticated things being done with new bridges. Today engineers are embedding sensors and fiber in the concrete while the bridges are being built in order to take measurements, but this approach is obviously not viable for existing bridges.

The methods in use for existing bridges included visual inspection, wired solutions which were bulky, expensive and time consuming to setup and a few wireless solutions some of which were proprietary, not scalable and interesting work from India.

In summary there are several challenges in deploying such a solution at sometimes remote and hostile locations. A lack of power which calls for alternate sources of energy, a way to effectively and reliably collect and transmit the data for analysis and keeping installation and maintenance costs low.

Since the train comes and goes, so can the data collected by the sensors. The train would activate the standby sensors as it approaches the bridge and then collect the data buffered by the sensors after passing the bridge. This approach would deal with the transmission of data limitations while at the same time eliminating the need of power for this component of the system. The train would carry the data and uploaded it to a collection station.

http://www.youtube.com/watch?v=PVH1K1Eocz0

To deal with reliability and power requirements the linear path Star Topology would be dropped in favor of a Mesh Network which provides TRUE self-organizing and self-healing properties. On top of the Mesh Network, TSMP (Time Synchronized Mesh Protocol) would be used providing more than 99.9% reliability and the lowest power consumption per delivered packet.

The key for achieving maximum reliability is to use channel hopping, in which each packet is sent on a different channel. In this case, transient failures in links on a given channel are handled gracefully, and persistent link failures that develop after the site survey do not destabilize the network.

Sensors of this type using this approach can last 7-10 years on a small battery meeting the application requirements.

Now to raise some money, build a working prototype and demo it to the Railway companies.

The existing EHR system had a hardware failure and the vendor was [...]]]> Last year I was recruited to find an Electronic Healthcare Records System (EHR) for a doctor who had just gone through a foiled implementation. I am always intrigued by being exposed to new sectors of technology and learning systems inside out.

The existing EHR system had a hardware failure and the vendor was asking for over $10,000 to recover the patient data. This combined with high maintenance and licensing fees proved to be too much for the doctor.

A consultant came in and sold the doctor on a hosted EHR system he had developed, unfortunately expectations were not set and the doctor was expecting his patient data to be available on this new system. Once it became apparent that there would be an additional cost in the thousands to recover and import this data into the new system the relationship went south.

This particular project was not only a technical but also a customer service challenge. Right from the start I made sure that the expectations were set and began looking at the possible solutions.

Amongst the many options available including traditional vendors, open source, home-grown systems, etc. (Tolven Healthcare, PatientOS, OpenEMR, Clearhealth, Abraxas, Medworks & Pulse)

I was looking to implement something that not only met the requirements (demographics, Medical history, Medications & allergies, Immunization status, Laboratory test results, Radiology images and Billing) of the client but was also scalable as a potential business. I ruled out the traditional EHR systems because of their high capital expenditure, ongoing costs, and approved VAR requirements. The open source solutions seemed very attractive but I was looking for something that did not require an on-site server thus it had to be hosted and using the cloud made it scalable.

So it came down to hosting an open-source package or using someone who had already done the legwork and I didn’t want to support this long term so the search turned 2 or 3 new cloud service providers of which only one I found to be mature enough to recommend; Practice Fusion.

Practice Fusion provides a free, web-based Electronic Medical Record (EMR) system to physicians. With charting, scheduling, e-prescribing, billing, lab integrations, referral letters, unlimited support and a Personal Health Record for patients, Practice Fusion’s EMR addresses the complex needs of today’s healthcare providers and disrupts the health IT status quo.

Although this did not turn out to be a passive income generator which I always have as a goal, it turned out to be a very educational and the platform for other ideas and projects.