Instrumented Interconnecteds Intelligent
Archive for August, 2012

By Scott Burnett
Director, Global Consumer Electronics

Ever since I graduated from college in 1981 and began my professional career by selling analog magnetic recording tape to movie studios and music companies, the promise of digital technology has been in the wind. That was the year of the IBM Personal Computer. Each technical advance since then–the CD, the DVD, laptops, mp3 players, interactive TV, smartphones, tablets—has helped enable a convergence of computing, communications and entertainment for the consumer.

Today, finally, the long-anticipated digital convergence is fundamentally in place. Thanks to innovations in cloud computing and mobility people have just about all the computing, communications and entertainment we want where and when we want it.

But it still isn’t easy to meld all of these capabilities together. Some possibilities are more difficult to fulfill than they should be. For instance, how many people can do something as seemingly simple as setting up a recording on their TV DVR when they’re not home using their smartphone?
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By Stephen Hammer, IBM Interactive Leader

The 2012 US Open tennis tournament is here and fans are gearing up to watch the world’s best tennis players compete over the next two weeks. For the avid tennis fan, keeping track of everything happening at the tournament is quite an undertaking.

I’ve worked at IBM for 15 years, and I’ve collaborated with sports organizations throughout my tenure. I’ve witnessed a lot of changes at the US Open during this time—from tournament location to acrylic courts—but what I have found consistent over this period is how existing technologies are transformed for these big events. This year’s US Open will continue this trend with the introduction of several Official US Open apps developed by IBM.

Remember when instant messaging (think AOL) was popular because for the first time people were able to instantly connect and communicate with one another? You may even recall the wide interest in posting photographs online during the 90s. Over the years, these concepts have evolved and are now the underpinning of social channels used around the world. We now have Twitter, Flickr and Instagram, which use the same interfacing technology to send short messages and share photos, but in a more user-friendly way that serves current interests.

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August 29th, 2012



By Alexander M. Schmidt, at IBM at the European level responsible for Information Management and Data Analysis projects in the Public Sector and 

Dr. Sebastian Höhn, managing director of the Institute for Security and Society at the Albert-Ludwigs-University Freiburg

Sometimes crime investigations are slowed or even brought to a standstill because of unexpected challenges. While data protection and privacy are important values in the German Constitution, to protect German citizens, can sometimes hamper the fight against crime. The restrictive situation creates hurdles for optimizing solutions regarding resolving and even preventing crimes.

Since the offenders do not care about the borders of the states inside of Germany, the criminal investigation has to operate across borders. In federal Germany, where the police law are the responsibility of each state, the data exchange between the states is a particular challenge. To combat this, The Centre for Security and Society at the University of Freiburg has identified the legal requirements of federal data exchange and IBM has established a Crime Information Platform that promotes the exchange of data across states while still meeting these legal requirements. Another focus is the exploration of current social changes and their impact on the police’s investigative techniques, such as the increasing virtualization of how people communicate and share information in a digitized world.

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The IBM Crime Information Platform provides an analytics solution to facilitate the investigative work of police officers across state boundaries. It helps to analyze document records and file data, and at the same time, guarantees compliance with different data-protection policies.

With Germany’s federal structure, IBM has the chance to clarify socio-political and legal issues that need to be considered for the development of security technologies. By combining various data sources in the Crime Information Platform, the offenders are identified more efficiently and still conform to state and federal laws. The goal of the cooperation between the Centre for Security and Society and IBM is to investigate legal and social issues of security technology in different application scenarios.

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August 28th, 2012

By Lauren States, CTO, IBM Cloud Computing and Growth Initiatives

For major sporting events, Big Data via the cloud is a game changer — literally.

This week, nearly 700,000 people will descend on the U.S. Tennis Center in New York to watch the world’s best players compete in the 2012 U.S. Open. But this year, millions of fans catching the action on their PC, tablet or smartphone may actually have the best seat in the house.

Thanks to Big Data, predictive analytics and cloud computing, fans from around the world will have access to real-time insight based on millions of data points – illustrating each player’s keys to winning the match.

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Now that’s a real advantage over simply sitting courtside keeping an eye on the scoreboard. So what’s the takeaway for business and government?

From Wimbledon to U.S. Open Golf, Roland Garros to U.S. Open Tennis, we see distinct parallels between the IT needs of big events and those of the enterprise. In fact, it’s often said that sports is a metaphor for life – but in some ways, sports is a metaphor for business as well.

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by Deepak Advani, IBM Vice President, Business Analytics

Do you remember when you bought your first e-reader?  Was the decision influenced by a digital or TV ad? Or did someone you trust, perhaps a family member or colleague at work, offer you advice and perhaps a quick demo of their device? How fast was the progression from awareness to consideration to purchase to loyalty?

Once upon a time, marketers sold to broad demographics such as “women, 18-34.” But now through insights gleaned from Big Data and predictive analytics, companies can get closer to the customer down to the point of the individual – whether a company has 500 customers, or five million.

From digital marketing and mobile commerce, to websites and social media, marketers are inundated — some say paralyzed — by data amassed from consumers via searches, purchase histories, price-scanning apps on mobile phones, Facebook “likes” and comments on Twitter. Combine that with data about in-store traffic, conversations with call centers and updates from suppliers, and today’s marketers confront a daily cacophony of data waiting to be sifted for nuggets of intelligence they can act upon to boost their business.

Big Data is creating a world of changing conventions in the C-suite. The CIO used to make all the IT decisions.  Now we are seeing that more CMOs are in the driver’s seat.  In fact Gartner Inc. says that by 2017 the CMO will have greater influence over the IT budget than the CIO.

As part of IBM’s effort to reach CMOs and spur a broader conversation about how technology is transforming marketing, we’re trying something a little bit different.  IBM is using the US Open to premier two TV spots about marketing.  They both highlight the need to treat customers as individuals. Here’s one called “Chief Executive Customer”:

Given the age of the digitally empowered consumer, companies need to start paying attention to a whole new set of metrics in this new world. They need to understand who their brand advocates and detractors are, and what shapes their attitudes and drives their behavior. They need to keep track of near-advocates, and what type of interactions will turn them into advocates. Similarly they need to keep a close eye on near-detractors, and what type of actions can reduce the probability of them turning into active and vocal detractors.

The good news is that algorithms can help companies understand and predict customer behavior. This type of customer analytics builds propensity models for each customer to determine the next best action they can take — at every touch point — such as call centers, web sites, branch offices and retail stores.

A telco company used this approach to turn 23% of its detractors into promoters. A financial services company used this approach to turn its call center into a revenue producing channel, which generated €30 million in 12 months. These examples demonstrate that the outcomes driven through the adoption of customer analytics are significant and are starting to go mainstream.

More organizations will learn how to shape their products and strategies based on such individual propensities without eroding customer trust, which in this brave new world will be a more important currency than ever before.

We hope you’ll check out Smarter Planet Facebook Friday with Deepak on September 7.  He’ll discuss how Big Data and predictive analytics are not only transforming the world of sporting events like the US Open, but how sports are evolving as a metaphor for business. 

Here’s a video of Deepak talking about how marketers can better understand their customers as individuals:

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August 28th, 2012

By Jean Noel Le Foll, General Manager, CFAO Technologies

Brazil, Russia, India, China, Turkey, South Africa and Mexico are the fastest growing markets for computer equipment, making up 14% of the global IT market. The regions increasing their IT purchases the most are the Middle East, Eastern Europe and Africa, according to Forrester Research. A growing list of companies in these emerging economies is relying on the IBM System z mainframe to build their infrastructures.

The Ministry of Senegal brought all of its import and export processes from across the country on-line with System z, and is now recovering 30% of Gross National Product, which amounts to two billion Senegalese francs in customs revenue every day. In the process, the Ministry increased the performance of its systems by 70%, reduced power consumption by 20% and cut operating costs by 30%.

Customs officers in Senegal and their partners now have real-time access to information across all of the country’s border checkpoints. They can check to see if the correct duty has been paid on shipments of goods coming through the country’s main border checkpoints This is a vast improvement over the Ministry’s previous system, which was limited to two border checkpoints. The Ministry of Senegal is using technology to apply critical information to boost the country’s economic growth.

My company, CFAO, also worked with the government in Cameroon to help them build their infrastructure on the mainframe. In Cameroon, the Cameroon Ministry of Finance is using a System z mainframe to help with smarter banking and modernize the payroll processes for government employees in the country. The new system is helping to increase the security of the Ministry’s payroll system and improve the efficiency of processes such as generating pay slips.

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by Rick Singer, VP, Sponsorship Marketing, IBM

The end of summer brings one of the most popular global sports events of the year — the US Open.

More than 700,000 fans are expected to attend the matches at the USTA’s Billie Jean King National Tennis Center in  Queens, making the US Open the most-attended, single sports event in the world. Even more viewers are expected to watch this year’s tournament on TV, topping the 53 million viewers who tuned in last year on CBS and ESPN.

And a record number of fans are expected to follow the US Open matches on their mobile devices, or seek out the latest match results, news or live streaming of tennis matches at on their computers at work or at home. We’re expecting to easily top the 15.5 million visitors who caught the action last year via the tournament’s website. These are big numbers all around.

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You might not realize, however, that major sporting events like the US Open are not only exciting to watch and follow, but are also a living lab for how “big data” can translate into big business. This year, the USTA is using business analytics to improve the experience for everyone: fans, tennis players, event organizers and broadcasters.

We’re all asking the same questions about the 2012 Open. What does Sam Stouser have to do to repeat last year’s women’s victory, or how can past winners Serena Williams and Maria Sharapova reign again? What can we expect from the men’s side? With Rafa Nadal sidelined by injury, will past US Open winners Novak Djokovic or Roger Federer win the men’s title? Or will Andy Murray break through, fresh from winning his gold medal at the Olympic Games in London. How can each of them outplay the others to bring home the trophy?

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By Christopher Conradi, Business Analytics, IBM

If you own a car in North America, you’re told to change the oil every 3,700 miles or six months. This applies whether you are living in Florida, driving peacefully to work, or living in Minnesota with frequent subzero temperatures in the winter. In Scandanavia, where I live, we change the oil in our vehicles less frequently because of concern about the environment.

But no matter what schedule you use, the point is that old-fashioned service manuals are not smart. Cars are used in different ways, and should therefore be serviced in different ways. And the same goes for any type of machinery.

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Just because machines start out the same way doesn’t mean we should service them the same way. To determine how often we get vehicles serviced, we need to consider the environment in which the machines operate, and how they are being used. The trick, off course, is to figure out just that: where and how are they being used?

It all starts with collecting data. Sensors are becoming increasingly sophisticated. Using heat cameras, we can detect wear inside a ball bearing. Microphones can help us detect the slightest change in frequency of a motor and with accelerometers, which are small sensors that measure acceleration, we can record motion of robotic arms that will give away inconsistencies.

These sensors work much like the nervous system in our body. Each sensor on it’s own is somewhat useful, but when you start combining the sensory data from multiple sources along with statistics and previous recordings, you really start to leverage the potential. Feeling the ground tremble, hearing a train horn, and seeing that you are standing on train tracks, are of little value on their own, but combining the information might prove life saving. With such input, you know that taking one step to the side is smarter than running along the tracks.

This is what we call predictive maintenance. Measuring, in real-time, how machines are doing and combining it with statistics and knowledge to fix things before they break, not after. This gives customers the chance to plan for down time, and do repairs before faulty parts affects others. In many cases, they can limit repairs to a few dollars instead of thousands.

This can also be applied to the products already sold. A car manufacturer could put sensors in its  cars, which would report on how the car is performing. This would give us a large dataset to find faults and errors, which would help evolve future products or make the servicing the cars smarter. In other words, letting the customer know that a part is about to break before it actually does.

On a smarter planet, we will stop treating cars — or machines — as a homogenous group. Since each one is used differently, it should be serviced by looking at the health of each part, and not when the booklet tells you it’s due for servicing.


Please continue the conversation with Chris on Friday, September 12 on IBM’s People for a Smarter Planet Facebook to learn more on predictive maintenance.  

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Editor’s Note: This Friday (August 24), be sure to join us for an interactive Smarter Friday conversation about Smarter Cities Challenge on Facebook throughout the business day (New York time). Please Tweet to #SmarterCities.

Nearly four years into the Smarter Planet journey, IBMers have undertaken more than 2,000 engagements with governments and businesses aimed helping them use cutting-edge technologies to make their systems for getting things done work better. These encounters are all over the map, geographically and figuratively. But important lessons are being learned. And, in particular, one interesting pattern is emerging. For organizations of all types, good outcomes depend on addressing the yin and yang of building a smarter planet: a combination of improvisation and preparedness–or long term planning.

Improvisation: In the realm of smarter planet problems and solutions, there’s so much variability that no single blueprint will fit every overtly similar situation. Organizations have to be flexible and creative to get stuff done. They can’t let the need for a master plan or budget-tightening pressures paralyze them.

Preparedness: While creative fixes can help city leaders manage their systems for the short-term, the longer-term vitality of cities, countries and organizations depends on leaders adopting a mission and a strategy for achieving it. But even that’s not enough. They have to anticipate the challenges to come–everything from next year’s big storm to the impacts of climate change to the next big financial shock–and build resilient systems capable of withstanding them.

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By Richard Silberman, Writer/Researcher, IBM Communications

Ruhong Zhou, Ph.D., conducts groundbreaking avian flu research on IBM Blue Gene

The next time an avian flu scare strikes — as it did in 2004 and likely will again — the world may be better prepared thanks to the work of Ruhong Zhou, research staff scientist and manager of the Soft Matter Theory and Simulation Group at IBM’s Thomas J. Watson Research Center.

Zhou and his team have been using an IBM Blue Gene supercomputer to anticipate genetic changes in the H5N1 influenza virus (commonly known as avian or bird flu) that might pose a serious threat to human health. Although H5N1 rarely infects the human population, when it does it has an extremely high mortality rate.

In a recent breakthrough, Zhou was able to computationally identify the single mutation in H5N1 that, should it occur, would debilitate antibodies in our immune system from fighting off this deadly flu. Armed with this information, pharmaceutical companies could design a vaccine that would compensate for this mutation and allow people to develop the necessary antibodies to combat H5N1 if they contract it.

“By isolating and anticipating this mutation, we can be proactive in creating a vaccine before the next avian flu outbreak strikes — potentially saving lives and even helping prevent a global pandemic,” Zhou said.

Taking the guesswork out of vaccine design

Influenza can undergo various mutations over a short time period, so trying to predict exactly how a flu strain will mutate next is the first step in vaccine development. It is too costly and time-intensive, however, to do this type of upfront research by trial and error in a traditional lab setting, so Zhou uses computer simulations to do his work.

Blue Gene provides the computational power to rapidly and efficiently simulate mutations at the atomic level so scientists can now predict a mutation with great accuracy and take much of the guesswork out of vaccine design.

Zhou simulated over 100 single and double mutations of H5N1’s hemagglutinin (HA) protein on Blue Gene in order to pinpoint the single, antibody-suppressing mutation he sought. Using all of Blue Gene’s 8,000 processors, it took two days to model each mutation. By comparison, it would take 8,000 days — or 22 years — to run each model on a laptop or desktop computer with a dual CPU.

“We could have never done our research without Blue Gene,” said Zhou, who has a Ph.D. in chemistry from Columbia University, where he currently teaches graduate level courses. “High performance computing of this sort is enabling a new era of breakthroughs in life science and holds great promise for advances in personalized medicine as well.”

Avian flu is an ongoing threat and has the potential to erupt into a pandemic someday. Zhou's work will help the world be better prepared and potentially save lives.

A proactive approach to preventing pandemics

For Zhou, who recently published his findings in Biophysical Journal, this breakthrough is particularly meaningful because of the real promise it holds for public health.

“As scientists, we often do some basic research just for our own curiosity — and achieving the results is gratification enough,” Zhou said. “But this is not just for our own interest; this is something very, very important to human society.”

Along with his avian flu research, Zhou has been using Blue Gene for the past six years to model genetic variations and predict mutations in other influenza strains, including swine flu (H1N1) and Hong Kong flu (H3N2). Zhou hopes the ability to anticipate mutations will prompt the medical community to start preparing preemptive vaccines well ahead of flu outbreaks, rather than responding after the fact (and after lives have been lost), which is the usual practice.

“We need to move from a reactive model of vaccine development to a proactive one,” Zhou said. “Our ability to accurately predict what mutations will happen next should give pharmaceutical companies the confidence to invest in vaccine production early enough to mount a strong defense against a virus and prevent a pandemic.”

Partnerships with government agencies like the Centers for Disease Control (CDC) and with pharmaceutical companies that want to use Zhou’s research to guide vaccine design are essential to realizing the full potential of Zhou’s work.

“With the right funding model and partnerships we can continue to explore influenza strains as well as other infectious diseases, such as HIV,” Zhou said. “I firmly believe that together we can develop better vaccines that will have a profound impact on society’s health and well-being.”

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