Visual Analytics: the journey so far ..

A bunch of International MBA students : diverse in terms of countries of origin, diverse in terms of languages they speak, diverse in terms of professional backgrounds they come from - when this lot of ours came together in Group C and ventured into this exciting journey of exploring the latest happenings in an upcoming technology of Visual Analytics, we discovered so many things.

We understood how Visual Analytics works, we explored its applications in numerous sectors, we wondered on how it is helping many people from athletes to scientists alike, what are the possible challenges with this technology and what pros and cons it presents.

When we came across this information, we shared it on this blog, and we made every effort to make this blog accessible and visible to as many people as we can.

We added Plus-One's on Google-Plus, we shared the posts on our Facebook profiles, we created a facebook page [https://www.facebook.com/seeie] to promote it all at one place.

But, that was not the only thing we did.

We also played with the free Analytics tool made available by Google in form of Google Webmasters. In here, we submitted our blog website for indexing, and for Google bots to crawl around it.
This configuration gave us the Search keywords, which we used to label our posts with. This site also provided us with special tags to insert into the HTML of our blog for Search Engine Optimization [S.E.O.].

We think results of this entire effort by the group - to explore and post about different aspects of Visual Analytics, to publicize what we posted on Google Plus and Facebook, and to use modern day technology of web analytics and search engine optimization to make the blog more visible in Google searches - are paying off eventually. In around two months time, our viewership has already crossed 1700 mark and the count in on the rise everyday.

Before we conclude this journey so far, here are a couple of snapshots of the SEO and web analytics tool that we deployed. Who knows, may be some day our readers can try these settings themselves and benefit from these tools just like we did :-)

Person of Interest - the workings of Video Analytics

Up to now, we have discussed quite a few interesting applications and points on visual analytics. But we have received some feedback asking to explain how it works. So here goes!

The basis of visual analytics, a practice of using computers to identify things or people of interest without an operator or a person having to view the video, are mathematical algorithms that monitor, analyze and manage big volumes of video. This means that video inputs are digitally analyzed and transformed into data that help people take decisions. It can be real time to help alert to specific incidents that could happen, such as an illegal suspect fleeing the country, and so on, or they can be post-event, looking incidents that have already occurred, for example a bombing or a fire in a store.

VA can happen in the centre, for example a central monitoring station, at the "edge", built into cameras which is ideal to locate live happenings, or as a combination of both. The optimal place to locate post-event analytics is on a central server as it is possible to search a large amount of recorded video for events, however this requires network capacity and processing power. But the main point on VA is that it works on motion detection and pattern recognition.

Motion Detection is basically examining each pixel in a given frame to detect the slightest movement. Pattern Recognition, on the other hand, recognizes specific patterns within a frame. These patterns or objects can be programmed and i.e, should a change happen or an object go missing the software immediately recognizes and sounds an alert.

The most common used types of video analytics used is violation of perimeters and recognition of license plates. Not only can this be used in surveillance, but in retail segment market analysis, to measure the number of people that pass in a given time (footfall), gender counting, shelf space effectiveness, and so on.

A fun and different way to see a little bit of VA in action, is watching a series called Person of Interest. It's just a TV show... but is it really?

Sources:
http://www.mistralsolutions.com/hs-downloads/tech-briefs/aug09-article-1.html
http://www.addic7ed.com/serie/Person_of_Interest/2/22/God_Mode
http://alexandra135.deviantart.com/art/Person-of-Interest-349555095

Visual Analytics aid Supply Chain Management (SCM)

The changing marvels we see in today’s globalized world are brought about by major social and economic change agents like the web 2.0, the financial platforms utilizing Swift technology, and an increasing integration of world economies through outsourcing practices, major logistics industry overhauls and the barriers of language being minimized. Behind the scenes of this new world is a management discipline that continues to play a vital role in the success, growth, and versatility of a firm in the global economy. The field of supply chain management continues to increase in complexity as capabilities are shipped around the world and developed in more niche geographical locations like manufacturing personal computer chips in China, etc. 

Depending on the industry, supply chain management can be very complex. For example, industries like aerospace, automobile manufacturing, and medical device manufacturers can have numerous tiers of suppliers all over the world that are susceptible to risks including weather changes, government stability/regulation, and economic factors like shortages of key resources. Supply chain managers are beginning to find immense value in the use of Visual Analytics because it makes a complex discipline more visible, and thus makes it easier to analyze.

This is an exciting blend of practices and is being spearheaded by researchers at the Supply Chain Responsiveness SCRiP institute at Cranfield School of Management the UK. Last June, SCRiP hosted a talk showcasing the progressive practice of visual analytics in supply chain management using two case studies in the British American Tobacco Company and Shell’s lubricant division. To follow these developments you can access documents and research on the SCRiP website listed below.

http://www.som.cranfield.ac.uk/som/scrip

http://alumni.som.cranfield.ac.uk/public/Event.aspx?Id=740

 

Visual Analytics tells the Story Right !

In the United States, Florida, the Florida Department of Juvenile Justice ("DJJ") is using visual analytics to present a clearer and more precise picture of children in the justice system and the effectiveness of the state’s innovative reform efforts. Isn't it amazing to see that government authorities are currently going for real innovative solutions!

The state’s Juvenile Justice Information System is one of the largest juvenile databases in the country, generating millions of lines of data about juvenile arrests, recidivism and reform outcomes.

To provide this information to stakeholders, DJJ had published annual, lengthy reports or posted  Microsoft Excel files online.  Nonetheless, department officials could not correct errors or add information to the reports once they were published, prompting the search for an interactive presentation tool that was both easy to update and learn.

Additionally, the department wanted a tool to help tell its juvenile justice reform story with data visualizations that would illustrate how giving a “civil citation” to first offenders had reduced recidivism in areas where it was actively encouraged.

Visual Analytics: Integrating with every thread of our life !!

In today's world, all the application areas where large information spaces have to be processed and analyzed, visual analytics can play a pivotal role.

In line with this utility of visual analytics, major fields/sectors that are either using visual analytics  or are candidates for using it for their advantage include:
physics, astronomy, climate control, catastrophe and emergency management, terrorism informatics, border protection, investigation support, computer tomography in field of medicine, ultrasound imaging, sequencing of DNA and other biological data, human genome study, study of protein cells, combinatorial chemistry with tens of millions of compounds, financial data analysis, stock exchange trades analysis, credit card usage analysis, monitoring efficiency of prison systems, traffic light systems, airport traffic control; analysis of player data, games history, sports team analysis and much more.

The point here is that Visual Analytics is no longer constrained to being that "trendy new thing" out there for geeks to try; It is a integrating itself in every sphere of life as we know it - from DNA research to finance sector to climate control to sports to social media to crime control and monitoring. You think of a field/sector and I am sure you will find a news about how this field is getting benefited by visual analytics.

Just recently, TCS, a major technology company announced how it is using visual analytics and big data analysis to predict the future of IT industry and the trends of future.

And what do this integration of visual analytics with various aspects of our life mean? Well, to start with technological implications, remember the buzzword of 'High Performance Computing' that I had mentioned in one of my previous posts? Well, for starters, this would not be just the cool thing which is deployed only by major investment banks; it will be a necessity for every sector.

And to generalize, It is a mathematical fact that more samples you process for getting your regression model, the lower is the error value associated and no matter what sector you belong to, you have to admit that there is so much data now available to be processed and analyzed. In today's world, this 'big data' goes hand-in-hand with the various visual analytics tools, when it comes to using this data and putting it for use. I mean, along with all the other advantages that this association of visual analytics and the large volume of data will bring to your sector, you won't mind that 'added' accuracy in predictions of trends you care about most, would you? :-)