Glimpse of Tomorrow

“Ouch! That hurt!”

So exclaimed one user of the University of Pennsylvania’s Tactile Gaming Vest (TGV) during yesterday’s demos at the IEEE Haptics Symposium, in Waltham, Mass.

As conference participants steered their character in a shoot-em-up computer video game based on Half-Life 2, the vest variously smacked them and vibrated as they themselves got shot. Sometimes it smarted, depending on how tight the vest was on the user, or if the “shots” hit right on the collar bone. For me it was more like a series of surprise punches.

Here is another example of the evolution of interface. Imagine this in conjunction with the Project Natal solution where you are moving into position dodging bullets in Call of Duty 6. You are ducking and firing but your not quite quick enough and you feel the "virtual" bullet hit you. Now thats interactive!

Let's now gear up and start playing Madden All Stars and Lawrence Taylor breaks through the O-line and crunch you feel it.

Wii boxing body blow body blow you feel it all.

Pretty cool -do you feel me?

When Nintendo's Wii game console debuted in November 2006, its motion-sensing handheld "Wiimotes" got players off the couch and onto their feet. Now Microsoft is trying to outdo its competitor by eliminating the controller altogether: It has revealed details of how it developed Project Natal, which gives Xbox 360 players the ability to manipulate on-screen characters via natural body movements.

The machine-learning technology will enable players to do things such as kick a digital soccer ball or swat a handball in their living rooms simply by mimicking the motion . "Instead of a controller, your body becomes the game input," says Alex Kipman, Microsoft's director of incubation for Xbox 360.

The power of combined voice recognition and visual acuity will radically change our interface. This technology makes virtual worlds are real consumer option. No more clunky interface where you right click a pie wheel to perform a task. A keyboard short cut or mouse click gets replaced with the natural gesture of shaking hands. This is going open the doors to the metaverse and make it an inviting place for the masses.

The next steps come when the machine in the room not only see's us but interacts with us. The AI reaches a point where it realizes what is going on in the room and can interact appropriately . When the XBOX gets a personality and becomes an ear for our daily chatter and provides good advice based on the technosocial profile assessment of the situation.

This is a huge win for Microsoft and the quest to dominate the living room. The power to extend the capacity of hardware with a camera system and software is amazing and the fun we will all have will easy any uneasy feelings about the machine watching us.

Probably not.

Yet people often dole out all kinds of personal information on the Internet that allows such identifying data to be deduced. Services like Facebook, Twitter and Flickr are oceans of personal minutiae — birthday greetings sent and received, school and work gossip, photos of family vacations, and movies watched.

Computer scientists and policy experts say that such seemingly innocuous bits of self-revelation can increasingly be collected and reassembled by computers to help create a picture of a person’s identity, sometimes down to the Social Security number.

“Technology has rendered the conventional definition of personally identifiable information obsolete,” said Maneesha Mithal, associate director of the Federal Trade Commission’s privacy division. “You can find out who an individual is without it.”

In a class project at the Massachusetts Institute of Technology that received some attention last year, Carter Jernigan and Behram Mistree analyzed more than 4,000 Facebook profiles of students, including links to friends who said they were gay. The pair was able to predict, with 78 percent accuracy, whether a profile belonged to a gay male.

So far, this type of powerful data mining, which relies on sophisticated statistical correlations, is mostly in the realm of university researchers, not identity thieves and marketers.

But the F.T.C. is worried that rules to protect privacy have not kept up with technology. The agency is convening on Wednesday the third of three workshops on the issue.

Its concerns are hardly far-fetched. Last fall, Netflix awarded $1 million to a team of statisticians and computer scientists who won a three-year contest to analyze the movie rental history of 500,000 subscribers and improve the predictive accuracy of Netflix’s recommendation software by at least 10 percent.

On Friday, Netflix said that it was shelving plans for a second contest — bowing to privacy concerns raised by the F.T.C. and a private litigant. In 2008, a pair of researchers at the University of Texas showed that the customer data released for that first contest, despite being stripped of names and other direct identifying information, could often be “de-anonymized” by statistically analyzing an individual’s distinctive pattern of movie ratings and recommendations.

In social networks, people can increase their defenses against identification by adopting tight privacy controls on information in personal profiles. Yet an individual’s actions, researchers say, are rarely enough to protect privacy in the interconnected world of the Internet.

You may not disclose personal information, but your online friends and colleagues may do it for you, referring to your school or employer, gender, location and interests. Patterns of social communication, researchers say, are revealing.

“Personal privacy is no longer an individual thing,” said Harold Abelson, the computer science professor at M.I.T. “In today’s online world, what your mother told you is true, only more so: people really can judge you by your friends.”

Collected together, the pool of information about each individual can form a distinctive “social signature,” researchers say.

The power of computers to identify people from social patterns alone was demonstrated last year in a study by the same pair of researchers that cracked Netflix’s anonymous database: Vitaly Shmatikov, an associate professor of computer science at the University of Texas, and Arvind Narayanan, now a researcher at Stanford University.

By examining correlations between various online accounts, the scientists showed that they could identify more than 30 percent of the users of both Twitter, the microblogging service, and Flickr, an online photo-sharing service, even though the accounts had been stripped of identifying information like account names and e-mail addresses.

“When you link these large data sets together, a small slice of our behavior and the structure of our social networks can be identifying,” Mr. Shmatikov said.

Even more unnerving to privacy advocates is the work of two researchers from Carnegie Mellon University. In a paper published last year, Alessandro Acquisti and Ralph Gross reported that they could accurately predict the full, nine-digit Social Security numbers for 8.5 percent of the people born in the United States between 1989 and 2003 — nearly five million individuals.

Social Security numbers are prized by identity thieves because they are used both as identifiers and to authenticate banking, credit card and other transactions.

The Carnegie Mellon researchers used publicly available information from many sources, including profiles on social networks, to narrow their search for two pieces of data crucial to identifying people — birthdates and city or state of birth.

That helped them figure out the first three digits of each Social Security number, which the government had assigned by location. The remaining six digits had been assigned through methods the government didn’t disclose, although they were related to when the person applied for the number. The researchers used projections about those applications as well as other public data, like the Social Security numbers of dead people, and then ran repeated cycles of statistical correlation and inference to partly re-engineer the government’s number-assignment system.

To be sure, the work by Mr. Acquisti and Mr. Gross suggests a potential, not actual, risk. But unpublished research by them explores how criminals could use similar techniques for large-scale identity-theft schemes.

More generally, privacy advocates worry that the new frontiers of data collection, brokering and mining, are largely unregulated. They fear “online redlining,” where products and services are offered to some consumers and not others based on statistical inferences and predictions about individuals and their behavior.

The F.T.C. and Congress are weighing steps like tighter industry requirements and the creation of a “do not track” list, similar to the federal “do not call” list, to stop online monitoring.

But Jon Kleinberg, a professor of computer science at Cornell University who studies social networks, is skeptical that rules will have much impact. His advice: “When you’re doing stuff online, you should behave as if you’re doing it in public — because increasingly, it is.”

In our always on constantly recorded world privacy is hard to find.

Everyone needs to start thinking about this. I now the mortal coil and your finite existence is a topic some people avoid but things have forever changed.

I wonder what Ben Franklin’s FaceBook page would have looked like?

I am currently watching We Live in Public and it is making me think about how we will die in public as well. The implications of a digitization of a life into a series of bits that gets backed up in the cloud. Can “immortality” be purchased with enough cash to create that infinite back up plan? Does our social foot print influence the future AI and pattern behaviors of our digital selves?

As we speed to a life and death in public what does the test of time do to the nature of man? How to we as a culture deal with a life span where our first steps are being recored on the iPhone and end when the nanites can no longer receive a signal from our neural receptors?

At that point we all become digital natives.

Just another glimpse of tomorrow.

Using the human collective to fix our broken reality. Using a gaming experiences to tackle heavy topics like human rights, poverty, disaster relief and others. You have 10 missions and 10 quests to bring about the best case scenarios for the future. Jane wants people to change real life habits as a result of playing these games. This game world experience is more of an open collaborative environment as in comparison to the idea of cheating off someone in the classroom.

Here is hoping we can evolve education to include these new tools.

Great transmedia touchpoint.. ideas bubbling. Nice use of QR codes to extend the AR capacity beyond geo-localization.

Another mobile AR application. They are doing some interesting AR gaming @SXSW - check out www.scavengar.com. This space is getting very fun!

This shows some applications of DecaWave's ScenSor IC, an IEEE 802.15.4a UWB (ultra wide band) standard compliant RF (Radio Frequency) transceiver that enables precision RTLS (Real Time Location Systems) applications. The ScenSor is also applicable to Wireless Sensor (Mesh) Networks (WSN) where it delivers higher-speed and lower-power data transfer compared to other 802.15.4 PHY implementations as used by ZigBee, 6LoWPAN, and proprietary WSN. The ScenSor enables thing-to-thing (T2T) communications bringing the vision of an Internet of things (IoT) closer to reality.

For more information see http://www.decawave.com/

In the video:
(1) Precise distance measurements are used to determine proximity and... (a) enable/disable devices (LapTop), (b) find lost items (Laptop and Teddy Bear), (c) enable access (opening door for doctor), (d) identify nearby patient info and so download correct records to doctor, (e) advise of approaching friends....
(2) An in-store location application guides shopper to the goods she desires
(3) proximity of tagged clothing, prompts suggestion of available matching shoes.
(4) Information transfer capability is seen as patient data is loaded.

Items are tagged with active RF devices using the ScenSor transceiver. This allows precise times of message sending and arrival to be measured, from which the time-of-flight can be calculated to yield a distance accurate to 10cm between peer devices without any other infrastructure.

With a fixed infra-structure of "Anchors" in a shop, factory or warehouse, range measurements can be combined to yield 3D location, or, with synchronised Anchors, TDOA (Time Difference of Arrival) can be used to locate items whose tags simply transmit an identifing blink message periodically. This is a low-power solution allowing operation with a small coin size battery for many years or perhaps indefinitely using energy-harvesting technology.

Category:  Science & Technology

Tags: 

UWB  RF  RTLS  802.15.4a  DecaWave  Time-Of-Flight  TDOA  Active-RFID  T2T  Thing-to-Thing  WSN  Internet-of-things  IoT 

Finally I will never loose my keys again. Now where did I put my phone.