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Internet of Things (IoT)

What it is and why it matters

The Internet of Things is the concept of everyday objects – from industrial machines to wearable devices – using built-in sensors to gather data and take action on that data across a network. So it’s a building that uses sensors to automatically adjust heating and lighting. Or production equipment alerting maintenance personnel to an impending failure. Simply put, the Internet of Things is the future of technology that can make our lives more efficient.

History of the Internet of Things

We’ve been fascinated with gadgets that function on a grander scale for decades (think spy movie-type stuff) – but it’s only been in the past several years that we’ve seen the IoT’s true potential. The concept evolved as wireless Internet became more pervasive, embedded sensors grew in sophistication and people began understanding that technology could be a personal tool as well as a professional one.

The term “Internet of Things” was coined in the late 1990s by entrepreneur Kevin Ashton. Ashton, who’s one of the founders of the Auto-ID Center at MIT, was part of a team that discovered how to link objects to the Internet through an RFID tag. He said he first used the phrase “Internet of Things” in a presentation he made in 1999 – and the term has stuck around ever since.

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Building a connected world through the Internet of Things

Data is everywhere – at home, at work and in practically every facet of life. This video from SAS and Intel explains how analytics is helping organizations find new solutions through streaming, always-on data.

 

Internet of Things infographic

Why is the Internet of Things important?

You might be surprised to learn how many things are connected to the Internet, and how much economic benefit we can derive from analyzing the resulting data streams. Here are some examples of the impact the IoT has on industries:

  • Intelligent transport solutions speed up traffic flows, reduce fuel consumption, prioritize vehicle repair schedules and save lives.
  • Smart electric grids more efficiently connect renewable resources, improve system reliability and charge customers based on smaller usage increments.
  • Machine monitoring sensors diagnose – and predict – pending maintenance issues, near-term part stockouts, and even prioritize maintenance crew schedules for repair equipment and regional needs.
  • Data-driven systems are being built into the infrastructure of "smart cities," making it easier for municipalities to run waste management, law enforcement and other programs more efficiently.

But also consider the IoT on a more personal level. Connected devices are making their way from business and industry to the mass market. Consider these possibilities:

  • You’re low on milk. When you’re on your way home from work, you get an alert from your refrigerator reminding you to stop by the store.
  • Your home security system, which already enables you to remotely control your locks and thermostats, can cool down your home and open your windows, based on your preferences.

Read the TDWI report, Four Use Cases Show Real-World Impact of IoT, to learn how the Internet of Things is changing how organizations work.

 

To make the Internet of Things useful, we need an Analytics of Things. This will mean new data management and integration approaches, and new ways to analyze streaming data continuously.
Thomas H. Davenport
 President's Distinguished Professor, Babson College
Co-founder and Director of Research, International Institute for Analytics
Author of Competing on Analytics and Big Data at Work

The Internet of Things in Today’s World

The impact that the IoT has had on the world has been significant – and it’s only getting started. Learn more about what people are saying.

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IoT Analytics in Practice

Three organizations – a US-based oil and gas company, a US municipality and an international truck manufacturer – discuss how IoT analytics has affected their organizations.

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Understanding Data Streams in IoT

Learn how event stream processing technology helps you acquire, understand and use real-time, streaming data to make fact-based, automated decisions.

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The Industrial Internet of Things: Secrets to Finding ROI Today

IndustryWeek interviewed 400+ manufacturing leaders about the industrial Internet of Things (IIoT). Learn how they are uncovering new opportunities for IoT technologies.

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SAS® Analytics for IoT

Integrate, analyze and visualize streaming data at the source

Learn more about SAS Analytics for IoT

Who's using it?

The IoT is more than just a convenience for consumers. It offers new sources of data and business operating models that can boost productivity in a variety of industries.

Health Care

Many people have already adopted wearable devices to help monitor exercise, sleep and other health habits – and these items are only scratching the surface of how IoT impacts health care. Patient monitoring devices, electronic records and other smart accessories can help save lives.

Manufacturing

This is one of the industries that benefits from IoT the most. Data-collecting sensors embedded in factory machinery or warehouse shelves can communicate problems or track resources in real time, making it easy to work more efficiently and keep costs down.

Retail

Both consumers and stores can benefit from IoT. Stores, for example, might use IoT for inventory tracking or security purposes. Consumers may end up with personalized shopping experiences through data collected by sensors or cameras.

Telecommunications

The telecommunications industry will be significantly impacted by the IoT since it will be charged with keeping all the data the IoT uses. Smart phones and other personal devices must be able to maintain a reliable connection to the Internet for the IoT to work effectively.

Transportation

While cars aren’t at the point of driving themselves, they’re undoubtedly more technologically advanced than ever. The IoT also impacts transportation on a larger scale: delivery companies can track their fleet using GPS solutions. And roadways can be monitored via sensors to keep them as safe as possible.

Utilities

Smart meters not only collect data automatically, they make it possible to apply analytics that can track and manage energy use. Likewise, sensors in devices such as windmills can track data and use predictive modeling to schedule downtime for more efficient energy use.

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Real-World Examples

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Smarter Cars

Andreas Mai, Director of Smart Connected Vehicles for Cisco, sheds light on the topic.

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Safer Transportation

Trucking companies use IoT to make operations safer, more efficient and economical.

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Connected Grids

Duke Energy uses advanced analytics on sensor data to anticipate customer needs.

How It Works

In IoT discussions, it’s recognized from the onset that analytics technologies are critical for turning this tide of streaming source data into informative, aware and useful knowledge. But how do we analyze data as it streams nonstop from sensors and devices? How does the process differ from other analytical methods that are common today?

In traditional analysis, data is stored and then analyzed. However, with streaming data, the models and algorithms are stored and the data passes through them for analysis. This type of analysis makes it possible to identify and examine patterns of interest as data is being created – in real time.

So before the data is stored, in the cloud or in any high-performance repository, you process it automatically. Then, you use analytics to decipher the data, all while your devices continue to emit and receive data.

With advanced analytics techniques, data stream analytics can move beyond monitoring existing conditions and evaluating thresholds to predicting future scenarios and examining complex questions.

To assess the future using these data streams, you need high-performance technologies that identify patterns in your data as they occur. Once a pattern is recognized, metrics embedded into the data stream drive automatic adjustments in connected systems or initiate alerts for immediate actions and better decisions.

Essentially, this means you can move beyond monitoring conditions and thresholds to assessing likely future events and planning for countless what-if scenarios.


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산업 분야별 IoT 도입 효과

당신이 제조업이나 통신 업계에 종사하고 있다면, 이미 IoT의 효과를 경험하고 있는 것입니다. IoT가 단지 소비자의 편익만을 위한 것이 아님은 분명합니다. 대신 IoT는 생산성과 경쟁력을 강화할 수 있는 새로운 형태의 데이터 소스와 비즈니스 운영 모델을 제공합니다.

점점 더 많은 종류의 장치와 기계와 산업 설비가 인터넷에 연결됨에 따라, 기업들을 연결하는 에코시스템이 업무 수행과 의사결정 방식을 완전히 바꾸어 놓을 것입니다. 그리고 끊임없이 생성되는 방대한 양의 데이터는 스트리밍 데이터에서 유의미한 가치를 발굴할 능력을 지닌 기업들에게 무한한 잠재력을 제공할 것입니다.

석유/가스 시추 플랫폼이 하루에 8 테라바이트의 데이터를, 그리고 항공기는 매 시간마다 40 테라바이트의 방대한 데이터를 생성한다는 사실을 알고 계셨습니까? 이것뿐이 아닙니다. 최신 자동차의 경우에는 초당 기가바이트 단위의 데이터를 만들어냅니다. 하지만 본격적인 IoT의 시대는 이제부터 시작일 뿐입니다!

이 데이터는 웨어하우스에 저장해 두었다가 나중에 분석할 수 있는 그런 유형의 데이터가 아닙니다. 데이터를 제대로 활용하려면 데이터가 조직 내로 유입되는 바로 그 순간 분석에 들어가야 합니다. 그리하여 우리는 이 분석 결과를 토대로 분석적 의사결정을 내리고, 다른 스트림과 통합하여 사물 통신(Machine-to-Machine)에 활용하고, 제어실에서 상황을 모니터하여 특이사항을 파악할 수 있습니다. 또한 스트리밍 분석을 적용, 어떤 일이 일어날지 사전에 파악하고 장애나 보안 리스크를 미리 예측하여 비용 절감 효과를 극대화할 수 있어야 합니다.

이제 여러분은 설비의 사용과 작동 상태, 그리고 각 구성요소의 성능에 이르기까지 모든 것들을 파악할 수 있습니다. 가령, 어떤 일이 벌어지고 있는지, 어떤 부분에 문제가 있는지, 그리고 유지 보수를 개선할 수 있는 방법은 무엇인지. 이 모든 것들을 즉각적인 분석 자료 피드백(data feedback)을 통해 명확히 파악할 수 있게 됩니다.

The Interent of Things infographic
IoT(Internet of Things)의 정의. 확대 이미지 보기

스트리밍 IoT 데이터의 분석 방법

IoT에 대한 논의를 종합해본 결과, 대량으로 유입되는 스트리밍 소스 데이터를 유익한—그리고 유용하고 정통한—지식으로 전환하기 위해서는 분석 기술이 반드시 필요하다는 주장이 힘을 얻고 있습니다.

그렇다면 각종 센서와 장치에서 쉴 새 없이 생성되는 데이터를 분석하려면 어떻게 해야 할까요? 그리고 이 프로세스는 일반적으로 통용되고 있는 다른 분석 기법과는 어떤 차이가 있을까요?

전통 방식의 분석의 경우 데이터를 저장한 다음에 분석이 이루어집니다. 이와 다르게 스트리밍 데이터의 경우에는 데이터가 저장된 모델과 알고리즘을 거치면서 분석이 이루어집니다. 이런 유형의 분석 기법은 데이터가 생성되는 과정에서 실시간으로 특정 패턴을 확인하고 검사할 수 있다는 장점이 있습니다.

데이터가 클라우드나 하이 퍼포먼스 리포지토리에 저장되기 전에 데이터가 자동으로 처리되므로, 사용자는 장치가 데이터를 생성하고 수신하는 동안에도 분석 기법을 이용해서 데이터를 해독할 수 있습니다.

고급 분석 기법에서는, 데이터 스트림 분석을 단순히 현재의 상황을 모니터하고 임계치를 측정하는 차원을 넘어 미래 시나리오를 예측하고 복잡한 문제를 검토하는 수준으로까지 활용할 수 있습니다.

이 같은 데이터 스트림을 이용해 미래의 상황을 평가하기 위해서는 데이터에서 패턴이 형성되는 즉시 이를 확인할 수 있는 하이 퍼포먼스 기술이 필요합니다. 패턴이 확인된 다음에는 데이터 스트림에 내장된 매트릭스(metrics)가 연결 시스템에서 자동 조정을 유도하거나 경보 시스템을 작동시켜 사용자가 즉각적인 조치를 취하고 더 나은 의사결정을 내릴 수 있도록 합니다.

궁극적으로, 사용자는 현재의 상황과 임계치를 모니터하는 수준을 넘어 발생 가능한 미래 이벤트를 미리 추정하고 매우 다양한 What-if 시나리오를 준비할 수 있습니다.

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