Sensor & Data flood

센서 및 데이터 홍수

우리는 월드 와이드 웹(World Wide Web)으로부터 인간을 위해 생성된 엄청난 양의 데이를 가지게 되었으며, 최근에는 온라인을 사용하면서 인간을 위해 생성된 것이 아닌 기기간의 소통을 위해 생성된 데이터가 더 많아지게 되었다. 센서(sensor) 뒤에 감춰진 기술은 새로운 것이 아니지만, 웹에서 이들 간의 연결은 새로운 것이었다.

얼마 지나지 않아 물리적 센서에 의해 생성되는 비동영상 데이터가

인터넷 통신량(traffic)의 20%를 차지할 것으로 추정된다

요즘은 3축 자기탐지기가 설치된 모바일 폰이나 스마트폰을 구입할 수 있다. 스마트폰은 운영체제를 가지고 있으며 개인 프로그램을 실행시킬 수 있다. 따라서, 몇 개의 코드 라인을 가지고 자기탐지기에서 발생하는 초당 수백 개의 휴대폰은 이미 자체적으로 동신시스템이 설치되어 있다 따라서 사람들이 당신이 만든 프로그램을 설치하고 실행할 수 있도록 확산시키는 것이 가능하다면, 당신은 매우 적은 투자로 많은 양의 자기탐지 데이터를 얻을 수 있다. 스마트폰은 자기탐지기 외에도 요레이트 자이로(yaw rate gyros) 센서, 3축 가속도(three-axis acelerometer ) 센서 온도(temperature) 센서GPS 수신기 (GPS receivers) 둥다른세서의 데이터도 대량으로운반한다.

데이터를 판독하는 것이 가능하다.'모바일 컴퓨팅과 센서 생성 데이터(sensor-generated data)라는 두 가지 동향은 미래에
우리가 다량의 데이터를 가지게 될 것이라는 것을 의미한다.

---

Here is a huge amount of information available online. And its volume is growing at lightning speed. Each minute on average, more than 200 million emails move across the Internet (though most are spam). Twitter users post more than 300,000 new tweets. People across the globe share more than 38,000 Instagrams. YouTube users upload another 100 hours of video. Google processes more than 3.6 millionwebsearches. And 2.2 million things on Facebook get a “like” or a comment.

For example, biologists collect enormous numbers of measurements on millions of cells and everything inside them. Astronomers fill banks of hard drives with observations of stars, galaxies and energy in deep space. Earth scientists assemble detailed snapshots of weather, including patterns of winds and waves throughout the world.

Computers housed in enormous data farms handle the work for search engines such as Google. The company operates lots of computers and data centers. This image shows a network room at a Google data center in Council Bluffs, Iowa. There, routers and switches connect the location to other data centers around the world. Google/Connie Zhou

Online data offer more than just a record of our time. Researchers build computer programs to analyze, organize and process those data. Then statisticians search for patterns and connections in those data to predict the future.

For instance, companies sift through data about what people spend their money on and when. That helps them find new ways to sell more products. In the 2012 U.S. presidential election, statisticians analyzed polling data to accurately predict the outcome in each state. Earth scientists track and analyze weather data over time to help predict, prepare for and perhaps even prevent catastrophic changes in climate. Information gleaned from big data can even identify disease outbreaks in time to impose quarantines that will prevent an epidemic.

Experts say big data also could completely change education, health care and many other fields. Some studies point to even stranger potential uses, such as identifying a criminal before a crime is committed. That’s an idea explored in movies such as Minority Report.

Yet what we’ve been describing is no movie. It’s life in today’s Information Age.

Stores gain from big data

The big leaps forward in data collection and use have created opportunities for a new kind of researcher. Experts like Patil, who work with big data, often call themselves data scientists. In many ways, the staggering volume of data being collected is less important than what data scientists do with it. It’s their job to find value — useful information — buried within it.

Manufacturers and advertisers have been quick to use such information to make more money.

1. Almost a decade ago, researchers at Walmart found that sales of strawberry Pop-Tarts increased by seven times when people learned a hurricane was on its way. Right before the storm hit, beer became the store's top-selling item, a company official told The New York Times. East Coast Walmart stores now stock up on both items before hurricane season.

2.  in the early 2000s, statisticians at Target, a department-store company, identified more than 20 lotions and other products that women tend to buy shortly after learning they are pregnant.

The company tracked those purchases among customers who paid with a credit card. It now can predict a woman’s due date within a short range. And it may send her ads and coupons for things that new parents need, such as a baby stroller or crib, according to a 2012 New York Times article.

3. Police too are investigating the value of big data. Some cities with high crime rates and overworked police officers now make predictions. Using past crime data, they have begun figuring out where and when patrols would be most useful in preventing future crime.

Personal health, personal learning

Data on health can run very deep. Physicians generally start by collecting data about a person’s general health. Scientists may then probe much deeper, gathering more complex data — such as about a person's blood or tissues..

1. Biochemists can collect data on the genes and the proteins that those genes instruct a cell to produce. Hide and other computational biologists then analyze vast stores of those data from particular types of cells — and from vast numbers of people. They’re scouting for patterns that pop up again and again.
2. A certain protein, for instance, may appear only in people with breast cancer. Does that mean it plays an important role in causing the disease? To test that, biologists might develop a drug to block that protein from being made or used.

Some researchers are finding ways to process patient data and create information useful in improving health care. Those data go beyond just blood pressure, temperature and pulse measurements. They can include details on the activity of a patient’s cells. boggy22/iStockphoto

According to the computer company IBM, 90 percent of all recorded data was created in just the last two years. Most of those data are stored on computer hard drives, phones and other digital devices. What about traditional libraries? Sources such as books and audiocassettes contain less than two percent of all stored information, according to Big Data. It’s a 2013 book by Viktor Mayer-Schönbergerand Kenneth Cukier.

https://www.sciencenewsforstudents.org/article/data-flood