¸ñ·Ï

Home

åǥÁö

Æø¹ßÀû ¼ºÀå ÀÓ°èÄ¡¿¡ µµ´ÞÇÏ°í ÀÖ´Â »ç¹°ÀÎÅͳÝ

»ç¹°ÀÎÅÍ³Ý ½ÃÀåÀÌ ³ª³¯ÀÌ ´õ Ä¿Áö°í ÀÖ´Ù. ¼ÒºñÀڵ鿡°Ô´Â Æí¸®ÇÏ°í °¡Ä¡ÀÖ´Â Á¦Ç°°ú ½Ã½ºÅÛÀ» Á¦°øÇÏ°í, ±â¾÷µé¿¡°Ô´Â »õ·Î¿î ¼öÀÍÀÇ ¿øõÀ» Á¦°øÇÒ Å¼¼´Ù. ÇöÀç ¾î¶² ±â¼úÀÌ µîÀåÇß°í, ..






The Internet of Things  Reaches Critical Mass
 
According to the Gartner Group, the number of Internet-connected gadgets in use will reach 8.7 billion by year-end 2017. While consumer Internet of Things solutions comprised 63% of the global market in 2016, IoT-related spending at the enterprise-level is growing rapidly, especially in manufacturing, transportation and utilities.


In 2016, the world¡¯s leading manufacturing companies including General Electric and Bosch invested $178 billion in IoT projects dealing with manufacturing operations, predictive maintenance and asset management. In 2017, IoT-related enterprise technology spending will reach $273 billion. General Electric, for example, uses Cisco¡¯s networking infrastructure to securely store, transmit and analyze equipment performance data collected through the GE Brilliant Manufacturing Suite. The company has recently deployed the so-called ¡°Brilliant solution¡± at a California factory and increased its productivity by 25%. Analysis by the Motley Fool estimates that a 1% average increase in the worldwide productivity of manufacturing companies would result in $10-to-15 trillion in global GDP growth.


Similarly, IoT spending by transportation companies reached $78 billion in 2016. Where did the money go? $55.9 billion (or 72% of the total) was spent on ¡°smart-freight monitoring solutions.¡± By enhancing ¡°dumb¡± objects (including vehicles, refrigerators and even bulk goods) with RFID tags and Zeg- Bee sensors, enterprises are able to collect machinery, personnel and cargo data, identify inefficiencies and subsequently reduce operating expenses. Did it pay off? 70% of logistics companies that have already initiat- ed IoT projects generated a 30% increase in productivity and order processing efficiency. Cisco believes that the impact of the Internet of Things on logistics and supply chain businesses can reach $1.9 trillion by 2025. And,


Utilities spent $69 billion globally on IoT in 2016. This spending was dominated by so- called ¡°Smart Grid solutions¡± ($57.8 billion). For instance, General Electric¡¯s Digital Pow- er Plant solution enables wind farms and power plants to generate electricity with re- al-time control, and little to no environmental impact. According to GE¡¯s estimates, the system can help the average gas-powered plants reduce operating costs by at least $50 million a year. By switching to smart grids, the USA can save up to $42 billion in energy costs during the first year, as well as reaping other IoT benefits such as the real-time control over energy bills, large-scale off-peak charging of electric vehicles and the growing utilization of renewable energy.
 
But the cost-saving opportunities don¡¯t stop there. IoT solutions for healthcare, retail, banking, insurance and consumer electronics will save even more. And of course, Consumer spending on money-saving ¡°Smart Home solutions,¡± will top $63 billion by 2020.


________________________________________


However, the biggest story of 2017 and beyond is that the highest-leverage, most innovative IoT opportunities will be revenue-driven rather than cost-driven. For instance, R-Style Lab, a firm ded- icated to identifying IoT opportunities for clients, estimates that as soon 2018, the global revenue-re- lated impact of IoT could be as high as $4.6 trillion. Obviously, much of this value will accrue to end-us- ers in the form of ¡°consumer surplus.¡± But the im- pact on business profits will be very significant.


This $4.6 trillion in ¡°IoT revenue enhancement¡± in 2025 will impact virtually every economic sec- tor. According to R-Style Lab it will break down as follows: Banking $154 billion, Manufacturing $913 billion, Retail $326 billion, Healthcare $313 billion, Transportation $325 billion, Utilities $201 billion, Government $570 billion, and the remaining $1.8 trillion will be spread over a wide range of service industries.


Consider the home automation market. Accord- ing to Pavel Shylenok, CTO at R-Style Lab, 90% of modern Smart Home systems are all about con- necting air conditioning and lighting systems to a smartphone app and doesn¡¯t really make the home, ¡°smart.¡± The focus is almost solely on saving mon- ey. On the other hand, genuine Smart Home sys- tems should incorporate Artificial Intelligence algo- rithms and be able to learn a home owner¡¯s habits, thus requiring little management on his part.


________________________________________


For, both consumer and business markets, IoT business opportunities will increasingly arise from ¡°turning data into money.¡± this is particularly evi- dent in the manufacturing sector. Back in 2015, Tata Consulting Services surveyed 3,645 companies and found that the largest IoT driven revenue increas- es were in manufacturing. 79% of manufacturers indicated using IoT solutions in the workplace and they reported an average 28.5% increase in revenue growth related to IoT. Next was financial services with a 17.7% increase in revenues, followed by me- dia and entertainment at 17.4%. The car industry had the lowest revenue gain, with a 9.9% increase. Across all sectors, companies reported average IoT-driven revenue growth of 15.6%.


Consider the case of Predictive Maintenance. The so-called Equipment as a Service business may represent the future of the Industrial Internet of Things. In this example, original equipment manufacturers enhance agriculture, construction and mining equipment with sensors and provide associated services including remote diagnostics and prompt repair. The company that delivers this capability first and best will be able to create a significant competitive advantage over the competitors. Provided the company learns to collect and process user-generated data effectively and non-intrusively, so-called ¡°IoT as a Service¡± can enhance the revenues of any connected business solution.


Given this trend, we offer the following forecasts for your consideration.
 
First, in order to develop an effective IoT monetization strategy, companies will focus on three activities:


1. Collect data on a connected gadget¡¯s usage, analyze it and make the findings available to the end customer;
2. Study user feedback and adjust product structure at  the  feature  level,  often using configurable offerings; and
3. Offer flexible consumption of an IoT solution.
 
Second, in 2018, worldwide IOT investments will focus on four primary functions: product monitoring, customer monitoring, supply chain monitoring and premises monitoring.


Some of these solutions are unexpected. For instance, product monitoring IOT embedded in vehicles is making it easier for lenders to repossess vehicles, in case of default.
 
Third, between now and 2025, a wide-range of IoT solutions will transform retailing.


Consider nine of the emerging opportunities and the companies pioneering them.


1. Beacon- and sensor-based   analytics. The companies in this group provide hard- ware and software solutions to help stores track visitors, optimize staff time, control discounts, monitor promotions, etc. Euclid Analytics, for example, provides an analytics platform which monitors the visitors and determines how promotions affect traffic in the store;


2. Beacon-based marketing. The solutions from this group of companies also tracks the customers, but uses this data for market- ing purposes. For example, Estimote sends ¡°push notifications¡± about products or pro- motions to the phones of buyers who are 2018 Projected Budget for loT Initiatives by Core loT Business Area nearby. Kimetric¡¯s sensors visually track and use the age of buyers, their gender and clothing styles to present them with an individual marketing proposal;


3. Beacon analytics and marketing. The solutions from this group of companies are aimed at correlating internal analytics and marketing research;


4. Inventory tracking. QueueHop develops special sensors that are designed to pro- tect goods from theft. Sensors automatical- ly unclip off the goods after their purchase. Another startup, Cosy develops robots that monitor products using specialized indoor mapping software;


5. Indoor mapping. These startups create (e.g. iCartogram, Indoora, and Aisle411 ) detailed maps of shops and shopping malls. This al- lows retailers to help shoppers find the right products and get information about current discounts or promotions;


6. Service robots. Startups Simbe Robotics and Fellow Robots are developing robots that will help customers quickly find products and ensure the shelves stay stocked. Fellow Robots plans to launch LoweBot in eleven Lowes stores this fall;


7. Loss prevention. Gatekeeper uses RFID tags with automatic wheel locking, so that retailers do not release shopping carts with- out paid purchases;


8. At-home shopping buttons. Startups Kwik and Hiku offer specialized devices that allow users to order different products directly from home. Similar to the Amazon One-Click buttons, Kwik enables customers to re-order products with a single click, while the Hiku device can scan bar codes to identify goods for re-ordering, and can also recognize the voices of users; and


9. Smart dressing rooms. Letting shoppers re- quest new items from the ¡°sales floor,¡± adjust lighting in the fitting rooms, and see outfit recommendations is a reality now. Oak Labs created an interactive, touchscreen mirror which (with the help of RFID tags) can determine which goods the buyer brought into the room and then recommend related products. The startup already works successfully with the sales network of Polo Ralph Lauren shops.


These applications are only the beginning. As IOT becomes cheaper and more ubiquitous, the human imagination is the only limit.


References


1. Gartner.com. February 7, 2017. Gartner Says 8.4 Billion Connected ¡°Things¡± Will Be in Use in 2017, Up 31 Percent From 2016 http://www.gartner.com/newsroom/id/3598917


2. R-Stylelab.com. May 18, 2017. Andrei Klubnikin. IoT in Business: from Cost Reduction to Revenue Growth. http://r-stylelab.com/company/blog/iot/iot-in-business-from-cost-reduction-to-revenue-growth


3. DHL.com. April 15, 2015. DHL and Cisco Internet of Things Trend Report http://www.dhl.com/en/about_us/logistics_insights/dhl_trend_research/internet_of_things.html#.WdTs0zDdkUE


4. Computerweekly.com. 22 Jul 2015. Cliff Saran. Investment in the internet of things boosts revenue for manufacturers. http://www.computerweekly.com/news/4500250349/Investment-in-IOT-drives-revenue-boost-for-manufacturers


5. R-Stylelab.com. June 19, 2017 Maxim Lyashko. Internet of Things in Retail: Meet Smartstores. http://r-stylelab.com/sciencemag.org/sites/default/files/styles/inline__699w__no_aspect/public/GG_AI_JB.png?itok=7DCjrahK









»ç¹°ÀÎÅÍ³Ý ½ÃÀåÀÌ ³ª³¯ÀÌ ´õ Ä¿Áö°í ÀÖ´Ù. ¼ÒºñÀڵ鿡°Ô´Â Æí¸®ÇÏ°í °¡Ä¡ÀÖ´Â Á¦Ç°°ú ½Ã½ºÅÛÀ» Á¦°øÇÏ°í, ±â¾÷µé¿¡°Ô´Â »õ·Î¿î ¼öÀÍÀÇ ¿øõÀ» Á¦°øÇÒ Å¼¼´Ù. ÇöÀç ¾î¶² ±â¼úÀÌ µîÀåÇß°í, ¾ÕÀ¸·Î ¾î¶² ±â¾÷µéÀÌ ÀÌ ±â¼úÀ» ÅëÇØ ¼º°øÀ» ±¸°¡ÇÒ °ÍÀΰ¡?


°¡Æ®³Ê ±×·ì(Gartner Group)¿¡ µû¸£¸é 2017³â ¿¬¸» ±âÁØ ÇöÀç »ç¿ë ÁßÀÎ ÀÎÅÍ³Ý ¿¬°á µµ±¸(gadgets)ÀÇ ¼ö´Â ¾à 87¾ï °³¿¡ ¾Æ¸¥´Ù. 2016³â¿¡ ¼ÒºñÀÚ¿ë »ç¹°ÀÎÅͳÝ(Internet of Things, IoT) ¼Ö·ç¼ÇÀº Àü ¼¼°è ½ÃÀåÀÇ 63ÆÛ¼¾Æ®¸¦ Â÷ÁöÇß´Ù. ÇÏÁö¸¸ »ç¹°ÀÎÅÍ³Ý °ü·Ã ºñÁî´Ï½º ¿µ¿ªÀÇ ÁöÃâÀÌ Æ¯È÷, Á¦Á¶¿Í ¿î¼Û, À¯Æ¿¸®Æ¼ ºÐ¾ß¿¡¼­ ¸Å¿ì ºü¸£°Ô ¼ºÀåÇÏ°í ÀÖ´Ù.


2016³â Á¦³Ê·² ÀÏ·ºÆ®¸¯(General Electric, GE)°ú º¸½¬(Bosch)¸¦ Æ÷ÇÔÇÑ ¼¼°è ÃÖ°íÀÇ Á¦Á¶ ±â¾÷µéÀº Á¦Á¶ ÀÛ¾÷, ¿¹Ãø À¯Áö º¸¼ö, ÀÚ»ê °ü¸®¸¦ ´Ù·ç´Â »ç¹°ÀÎÅÍ³Ý ÇÁ·ÎÁ§Æ®¿¡ 1,780¾ï ´Þ·¯¸¦ ÅõÀÚÇß´Ù. 2017³â, »ç¹°ÀÎÅÍ³Ý °ü·Ã ºñÁî´Ï½º ±â¼ú ÁöÃâÀº 2,730¾ï ´Þ·¯¿¡ À̸£·¶´Ù. ¿¹¸¦ µé¾î, GE´Â ½Ã½ºÄÚÀÇ ³×Æ®¿öÅ· ÀÎÇÁ¶ó¸¦ »ç¿ëÇÏ¿© GE ºê¸±¸®¾ðÆ® ¸Æ´ºÆÑó¸µ ½ºÀ§Æ®(Brilliant Manufacturing Suite)¸¦ ÅëÇØ ¼öÁýµÈ Àåºñ ¼º´É µ¥ÀÌÅ͸¦ ¾ÈÀüÇÏ°Ô ÀúÀå, Àü¼ÛÇÏ°í ºÐ¼®Çß´Ù. ÀÌ È¸»ç´Â Ãֱ٠Ķ¸®Æ÷´Ï¾Æ °øÀå¿¡ ¼ÒÀ§ ÀÌ ºê¶ö¸®¾ðÆ® ¼Ö·ç¼ÇÀ» ¹èÄ¡ÇÏ¿© »ý»ê¼ºÀ» 25ÆÛ¼¾Æ® Çâ»ó½ÃÄ×´Ù. ¹Ì±¹ ±ÝÀ¶ Àü¹®¸Åü ¡º¸ðƲ¸® Ç®(Motley Fool)¡»ÀÇ ºÐ¼®¿¡ µû¸£¸é Àü ¼¼°è Á¦Á¶ ±â¾÷ »ý»ê¼ºÀÌ Æò±Õ 1ÆÛ¼¾Æ® Áõ°¡Çϸé Àü ¼¼°è GDP ¼ºÀå¿¡ 10¡­15 Á¶ ´Þ·¯°¡ ´õ ¹ß»ýÇÒ °ÍÀ¸·Î ¿¹»óµÈ´Ù.


¸¶Âù°¡Áö·Î, ¿î¼Û ȸ»çµéÀÌ »ç¹°ÀÎÅͳݿ¡ ¾´ ÁöÃâÀº 2016³â ±âÁØ 780¾ï ´Þ·¯¿¡ ´ÞÇß´Ù. ÀÌ·¯ÇÑ µ·Àº ¾îµð·Î ÇâÇßÀ»±î? 559¾ï ´Þ·¯, Áï Àüü ÁöÃâÀÇ 73ÆÛ¼¾Æ®°¡ ¡®½º¸¶Æ® È­¹° ¸ð´ÏÅ͸µ ¼Ö·ç¼Ç¡¯¿¡ ÅõÀԵƴÙ. ÀÚµ¿Â÷, ³ÃÀå°í ½ÉÁö¾î ¹úÅ© µîÀÇ »óÇ°¿¡ RFID ÅÂ±×¿Í Áö±×ºñ(Zegbee) ¼¾¼­¸¦ »ç¿ëÇÏ¿©, »ç¾÷ÀÚµéÀº ±â°è ¹× Àοø, È­¹° µ¥ÀÌÅ͸¦ ¼öÁýÇÒ ¼ö ÀÖ¾ú°í, ºñÈ¿À²ÀûÀÎ °ÍµéÀ» È®ÀÎÇÑ ÈÄ, ¿î¿µºñ¿ëÀ» ÁÙÀÏ ¼ö ÀÖ¾ú´Ù. ±×·¸´Ù¸é ÀÌ·¯ÇÑ ¼³Ä¡ºñ¿ëÀÌ ÃæºÐÇÑ °ª¾îÄ¡¸¦  ÇßÀ»±î? »ç¹°ÀÎÅÍ³Ý ÇÁ·ÎÁ§Æ®¸¦ ½ÃÀÛÇÑ ¹°·ù ȸ»çµéÀÇ 70ÆÛ¼¾Æ®´Â »ý»ê¼º°ú ÁÖ¹® ó¸® È¿À²¼ºÀ» 30ÆÛ¼¾Æ® Çâ»ó½ÃÄ×´Ù. ½Ã½ºÄÚ´Â ¹°·ù¿Í °ø±Þ üÀο¡ ´ëÇÑ »ç¹°ÀÎÅͳÝÀÇ ¿µÇâÀ» ±ÝÀüÀ¸·Î ȯ»êÇϸé 2025³â ¾à 17Á¶ ´Þ·¯¿¡ À̸¦ ¼ö ÀÖ´Ù°í ÆÇ´ÜÇÏ°í ÀÖ´Ù.


À¯Æ¿¸®Æ¼´Â ¾î¶³±î? Àü ¼¼°èÀûÀ¸·Î »ç¹°ÀÎÅÍ³Ý ½ÃÀå¿¡¼­ 2016³âÀ» ±âÁØÀ¸·Î À¯Æ¿¸®Æ¼¿¡ ÁöÃâµÈ ±Ý¾×¸¸ ¾à 690¾ï ´Þ·¯´Ù. ÀÌ ÁöÃâÀº ¼ÒÀ§ ¡®½º¸¶Æ® ±×¸®µå ¼Ö·ç¼Ç(Smart Grid Solution)ÀÌ ÁÖµµÇß´Ù. ¿¹¸¦ µé¾î, GEÀÇ µðÁöÅÐ ÆÄ¿ö Ç÷£Æ®(Digital Power Plant) ¼Ö·ç¼ÇÀ» »ç¿ëÇϸé dz·Â ¹ßÀü¼Ò µîÀÇ °¢ ¹ßÀü¼Ò¸¦ ½Ç½Ã°£À¸·Î Á¦¾îÇÒ ¼ö ÀÖ°í, ȯ°æ¿¡ ¾î¶² ¿µÇâµµ ¹ÌÄ¡Áö ¾Ê°í Àü·ÂÀ» »ý»êÇÒ ¼ö ÀÖ´Ù. GEÀÇ ¿¹Ãø¿¡ µû¸£¸é, ÀÌ ½Ã½ºÅÛÀº Æò±ÕÀûÀÎ °¡½º ¹ßÀü¼ÒÀÇ °æ¿ì ¿î¿µºñ¿ëÀ» ¿¬°£ ÃÖ¼Ò 5õ¸¸ ´Þ·¯±îÁö Àý°¨½ÃÄÑÁØ´Ù. ½º¸¶Æ® ±×¸®µå·Î ÀüȯÇÔÀ¸·Î½á ¹Ì±¹Àº ¿¡³ÊÁö ºñ¿ë û±¸¿¡ ´ëÇÑ ½Ç½Ã°£ Á¦¾î, Àü±â ÀÚµ¿Â÷ÀÇ ´ëÇü ¿ÀÇÁ ÇÇÅ© ÃæÀü(off-peak charging), Àç»ý°¡´É ¿¡³ÊÁöÀÇ È°¿ëµµ Áõ´ë¿Í °°Àº »ç¹°ÀÎÅͳÝÀÇ ´Ù¸¥ ÇýÅÃÀ» ¾ò´Â °Í»Ó¸¸ ¾Æ´Ï¶ó ùÇØ¿¡¸¸ ÃÖ´ë 420¾ï ´Þ·¯ÀÇ ¿¡³ÊÁö ºñ¿ëÀ» Àý°¨ ÇÒ ¼ö ÀÖ´Ù.


±×·¯³ª ºñ¿ë Àý°¨ ±âȸ´Â °Å±â¼­ ¸ØÃßÁö ¾Ê´Â´Ù. ÇコÄɾî, ¼Ò¸Å, ÀºÇà, º¸Çè, ¼Òºñ °¡ÀüÁ¦Ç°¿¡ ´ëÇÑ »ç¹°ÀÎÅÍ³Ý ¼Ö·ç¼ÇÀº ÈξÀ ´õ ¸¹Àº ºñ¿ëÀ» Àý°¨½ÃÄÑÁÙ °ÍÀÌ´Ù. ¹°·Ð ºñ¿ë Àý°¨Çü ½º¸¶Æ® Ȩ ¼Ö·ç¼Ç¿¡ ´ëÇÑ ¼ÒºñÀÚ ÁöÃâÀº 2020³â±îÁö 630¾ï ´Þ·¯¸¦ ³Ñ¾î¼³ °ÍÀÌ´Ù.


±×·¯³ª ¾ÕÀ¸·ÎÀÇ °¡Àå Å« À̾߱â´Â °¡Àå ¿µÇâ·Â ÀÖ°í °¡Àå Çõ½ÅÀûÀÎ »ç¹°ÀÎÅͳÝÀÇ ±âȸ°¡ ºñ¿ë Á߽ɺ¸´Ù´Â ¼öÀÍ Áß½ÉÀ¸·Î ÁøÇàµÉ °ÍÀ̶ó´Â Á¡¿¡ ÀÖ´Ù. ¿¹¸¦ µé¾î, °í°´À» À§ÇÑ »ç¹°ÀÎÅͳÝÀÇ ±âȸ¸¦ ½Äº°ÇÏ´Â µ¥ ÁÖ·ÂÇØ¿Â ¼ÒÇÁÆ®¿þ¾î °³¹ßȸ»ç R½ºÅ¸ÀÏ·¦(R-Style Lab)Àº 2018³â¿¡ »ç¹°ÀÎÅͳݰú ¿¬°èµÈ Àü ¼¼°èÀÇ Æı޷ÂÀÌ 4Á¶ 6õ¾ï ´Þ·¯ ÀÌ»óÀ̶ó°í ºÐ¼®Çß´Ù. ºÐ¸íÈ÷ ÀÌ·¯ÇÑ °¡Ä¡ÀÇ »ó´ç ºÎºÐÀº ÃÖÁ¾ ¼ÒºñÀÚ¿¡°Ô ¼ÒºñÀÚÀ׿©(consumer surplus, ¼ÒºñÀÚµéÀÌ ¾î¶² ÀçÈ­³ª ¼­ºñ½º¿¡ ´ëÇØ ÁöºÒÇÏ°íÀÚ ÇÏ´Â °ª°ú ½ÇÁ¦·Î ±×µéÀÌ ÁöºÒÇÑ °ª°úÀÇ Â÷ÀÌ)ÀÇ ÇüÅ·Π¹ß»ýÇÒ °ÍÀÌ´Ù. ±×·¯³ª ºñÁî´Ï½º ¼öÀÍ¿¡ ´ëÇÑ ±× ¿µÇâ·ÂÀº ¸Å¿ì Àǹ̽ÉÀåÇÒ °ÍÀÌ´Ù.


2018³â »ç¹°ÀÎÅÍ³Ý ¼öÀÍ Çâ»ó¿¡ ÀÖ¾î 4Á¶ 6õ¾ï ´Þ·¯´Â ½ÇÁúÀûÀ¸·Î ¸ðµç °æÁ¦ ¿µ¿ª¿¡ ÆıÞÀ» ÁÖ´Â °ÍÀÌ´Ù. R½ºÅ¸ÀÏ·¦¿¡ µû¸£¸é, ÀÌ°ÍÀº ´ÙÀ½°ú °°ÀÌ ³ª´²Áø´Ù. ÀºÇà»ê¾÷¿¡¼­ 1,580¾ï ´Þ·¯, Á¦Á¶»ê¾÷¿¡¼­ 9,130¾ï ´Þ·¯, ¼Ò¸Å»ê¾÷¿¡¼­ 3,260¾ï ´Þ·¯, ÇコÄÉ¾î »ê¾÷¿¡¼­ 3,130¾ï ´Þ·¯, ¿î¼Û»ê¾÷¿¡¼­ 3,250¾ï ´Þ·¯, À¯Æ¿¸®Æ¼ »ê¾÷¿¡¼­ 2,010¾ï ´Þ·¯, Á¤ºÎ¿µ¿ª¿¡¼­ 5,700¾ï ´Þ·¯, ±×¸®°í 1Á¶ 8õ¾ï ´Þ·¯´Â ¼­ºñ½º »ê¾÷ÀÇ ³ÐÀº ¿µ¿ªÀ¸·Î °í¸£°Ô È®»êµÆ´Ù.


Ȩ¿ÀÅä¸ÞÀÌ¼Ç ½ÃÀåÀ» º¸ÀÚ. R½ºÅ¸ÀÏ·¦ÀÇ ÃÖ°í±â¼ú°ü¸®ÀÚ Æĺ§ ½¯·¹³ëÅ©(Shylenok)¿¡ µû¸£¸é, ¿À´Ã³¯ ½º¸¶Æ®È¨ ½Ã½ºÅÛÀÇ 90ÆÛ¼¾Æ®´Â ¿¡¾îÄÁ°ú Á¶¸í ½Ã½ºÅÛÀ» ½º¸¶Æ®Æù ¾Û¿¡ ¿¬°áÇÏ´Â °ÍÀÌ´Ù. ÇÏÁö¸¸ ½ÇÁúÀûÀ¸·Î´Â ÁýÀ» ½º¸¶Æ®ÇÏ°Ô(¶È¶ÈÇÏ°Ô) ¸¸µéÁö´Â ¾Ê´Â´Ù. ÃÊÁ¡Àº °ÅÀÇ ÀüÀûÀ¸·Î ºñ¿ë Àý°¨¿¡ ÀÖ´Ù. ¹Ý¸é, ÁøÁ¤ÇÑ ½º¸¶Æ®È¨ ½Ã½ºÅÛÀº Àΰø Áö´É ¾Ë°í¸®ÁòÀ» ÅëÇÕÇÏ´Â °ÍÀÌ´Ù. À̸¦ ÅëÇØ ÁýÀº ÁÖÀÎÀÇ ½À°üÀ» ÇнÀÇÒ ¼ö ÀÖ°í, Àû¾îµµ Àΰø Áö´ÉÀÌ ¸ÃÀº ºÎºÐ¿¡ À־ ÁÖÀÎÀº °ÅÀÇ °ü¸®ÇÒ ÇÊ¿ä°¡ ¾ø´Â °ÍÀÌ´Ù.


¼ÒºñÀÚ¿Í ºñÁî´Ï½º ½ÃÀå ¸ðµÎ¿¡¼­ »ç¹°ÀÎÅÍ³Ý ºñÁî´Ï½º ±âȸ´Â ¡®µ¥ÀÌÅ͸¦ µ·À¸·Î¡¯ ÀüȯÇÔÀ¸·Î½á Á¡Â÷ Ä¿Áú °ÍÀÌ´Ù. À̴ ƯÈ÷ Á¦Á¶ »ê¾÷ ¿µ¿ª¿¡¼­ ¾ÆÁÖ ¸íÈ®ÇÏ´Ù. 2015³â ŸŸ ÄÁ¼³Æà ¼­ºñ½º(Tata Consulting Services)°¡ 3,645 °³ÀÇ ±â¾÷À» ´ë»óÀ¸·Î ¼³¹® Á¶»ç¸¦ ½Ç½ÃÇÑ °á°ú, »ç¹°ÀÎÅͳÝÀÌ ÁÖµµÇÏ´Â °¡Àå Å« ¼öÀÍÀº Á¦Á¶ »ê¾÷¿¡ ÀÖ¾ú´ø °ÍÀ» ¾Ë¾Æ³Â´Ù. Á¦Á¶¾÷üÀÇ 79ÆÛ¼¾Æ®°¡ ÀÛ¾÷ ÇöÀå¿¡¼­ »ç¹°ÀÎÅÍ³Ý ¼Ö·ç¼ÇÀ» »ç¿ëÇß°í, »ç¹°ÀÎÅͳݰú °ü°èµÈ ¼öÀÍ ¼ºÀå¿¡ ÀÖ¾î Æò±Õ 28.5ÆÛ¼¾Æ®°¡ Áõ°¡Çß´Ù. ´ÙÀ½Àº ±ÝÀ¶ ¼­ºñ½º·Î 17.7ÆÛ¼¾Æ®°¡ Áõ°¡Çß°í, ±× ´ÙÀ½Àº ¹Ìµð¾î¿Í ¿£ÅÍÅ×ÀθÕÆ®·Î 17.5ÆÛ¼¾Æ®¸¦ ±â·ÏÇß´Ù. ÀÚµ¿Â÷ »ê¾÷Àº 9.9ÆÛ¼¾Æ®·Î °¡Àå ³·Àº ¼öÀÍ ¼ºÀåÀ» º¸¿´´Ù. ¸ðµç °æÁ¦ ¿µ¿ª¿¡ À־, ±â¾÷µéÀº »ç¹°ÀÎÅͳÝÀÌ ÁÖµµÇÏ´Â Æò±Õ ¼öÀÍ ¼ºÀåÀÌ 15.6ÆÛ¼¾Æ®¿¡ À̸¥´Ù°í ¹àÇû´Ù.


¿¹Áöº¸Àü(predictive maintenance)ÀÇ »ç·Ê¸¦ º¸ÀÚ. ¼ÒÀ§ ¸»ÇÏ´Â EAAS(Equipment as a Service, ¼­ºñ½º·ÎÀÇ Àåºñ) ºñÁî´Ï½º´Â »ê¾÷¿ë »ç¹°ÀÎÅͳÝÀÇ ¹Ì·¡¸¦ ´ëº¯ÇÒ ¼ö ÀÖ´Ù. ÀÌ »ç·Ê¿¡¼­, Àåºñ ¿øÁ¦Á¶¾÷ü´Â ¼¾¼­¸¦ ÅëÇØ ³ó¾÷¿ë, °Ç¼³¿ë, ±¤»ê¿ë ÀåºñÀÇ ¼º´ÉÀ» Çâ»ó½ÃÅ°°í, ¿ø°Ý Áø´Ü°ú ½Å¼ÓÇÑ ¼ö¸®¸¦ Æ÷ÇÔÇÏ´Â ¿¬°è ¼­ºñ½º¸¦ Á¦°øÇÑ´Ù. ÀÌ·¯ÇÑ ¿ª·®À» ÃÖÃÊ·Î ±×¸®°í ÃÖ»óÀ¸·Î Á¦°øÇÏ´Â ±â¾÷ÀÌ °æÀïÀÚ¸¦ ´É°¡ÇÏ´Â »ó´çÇÑ °æÀï ¿ìÀ§¸¦ âÃâÇÒ °ÍÀÌ´Ù. »ç¿ëÀÚ·Î ÀÎÇØ »ý¼ºµÇ´Â °¢Á¾ Á¤º¸¸¦ È¿°úÀûÀ¸·Î ±×¸®°í Àº¹ÐÇÏ°Ô ¼öÁýÇÏ°í ó¸®ÇÏ´Â ¹æ¹ýÀ» ±â¾÷ÀÌ ÇнÀÇÑ´Ù¸é, ¼ÒÀ§ ¼­ºñ½º·Î¼­ÀÇ »ç¹°ÀÎÅͳÝÀº ¸ðµç ¿¬°èµÈ ºñÁî´Ï½º ¼Ö·ç¼ÇÀÇ ¼öÀÍÀ» Çâ»ó½Ãų ¼ö ÀÖ´Ù.


ÀÌ·¯ÇÑ »ç¹°ÀÎÅͳÝÀÇ µµ·¡¿Í ¹ßÀü ¼Óµµ, ±â¼úÀ» ÅëÇØ ¿ì¸®´Â ´ÙÀ½ 3°¡Áö¸¦ ¿¹ÃøÇÒ ¼ö ÀÖ´Ù.
 
ù°, È¿°úÀûÀÎ »ç¹°ÀÎÅÍ³Ý ¼öÀÍâÃâ Àü·«À» °³¹ßÇϱâ À§ÇØ ±â¾÷µéÀº 3°¡Áö È°µ¿¿¡ ÁýÁßÇÒ °ÍÀÌ´Ù.


1. ¿¬°áµÈ µµ±¸µéÀÇ »ç¿ë¿¡¼­ µµÃâµÇ´Â Á¤º¸¸¦ ¸ðÀ¸°í ±×°ÍÀ» ºÐ¼®ÇÏ¿©, ±× ºÐ¼® °á°ú¹°À» ÃÖÁ¾ ¼ÒºñÀÚµéÀÌ »ç¿ë°¡´ÉÇϵµ·Ï ÇÒ °ÍÀÌ´Ù.

2. »ç¿ëÀÚ Çǵå¹éÀ» ¿¬±¸ÇÏ¿© Á¾Á¾ ¼³Á¤ÀÌ °¡´ÉÇÑ ±â´É ¼öÁØ¿¡¼­ Á¦Ç° ±¸Á¶ ȤÀº ±¸¼ºÀ» Á¶Á¤ÇÒ °ÍÀÌ´Ù.

3. »ç¹°ÀÎÅÍ³Ý ¼Ö·ç¼Ç¿¡ ´ëÇÑ Åº·ÂÀûÀÎ ¼Òºñ(consumption)¸¦ Á¦°øÇÒ °ÍÀÌ´Ù.
 
µÑ°, °¡±î¿î ¹Ì·¡±îÁö Àü ¼¼°èÀÇ »ç¹°ÀÎÅÍ³Ý ÅõÀÚ´Â 4°¡Áö ÁÖ¿ä ±â´É¿¡ ÁßÁ¡À» µÑ °ÍÀÌ´Ù. Á¦Ç° ¸ð´ÏÅ͸µ, °í°´ ¸ð´ÏÅ͸µ, °ø±ÞüÀÎ ¸ð´ÏÅ͸µ, °Ç¹° ¸ð´ÏÅ͸µÀÌ ±×°ÍÀÌ´Ù.


ÀÌ·¯ÇÑ ¼Ö·ç¼Ç Áß ÀϺδ ¿¹»óÄ¡ ¸øÇÑ °ÍÀÌ´Ù. ¿¹¸¦ µé¾î, ÀÚµ¿Â÷¿¡ ³»ÀåµÈ Á¦Ç° ¸ð´ÏÅ͸µ »ç¹°ÀÎÅͳÝÀº ÀÚµ¿Â÷ ¸®½º ȸ»ç°¡ °í°´ÀÇ Ã¤¹« ºÒÀÌÇà ȤÀº Â÷·®ÀÇ °áÇÔ ¹ß»ý½Ã Â÷·®À» ½Å¼ÓÇÏ°Ô ÆľÇÇÏ¿© ȸ¼ö ȤÀº ±³Ã¼¸¦ ½±°Ô ÇÒ ¼ö ÀÖµµ·Ï µµ¿òÀ» ÁÙ °ÍÀÌ´Ù.


¼Â°, ¾ÕÀ¸·Î 2025³â±îÁö, ±¤¹üÀ§ÇÑ »ç¹°ÀÎÅÍ³Ý ¼Ö·ç¼ÇÀÌ ¼Ò¸Å »ê¾÷ÀÇ ±Ù°£À» ¸ðµÎ ¹Ù²Ü °ÍÀÌ´Ù.


»õ·Î¿î ±âȸ¿Í ±× ±âȸ¸¦ Ãß±¸ÇÏ°í ÀÖ´Â ±â¾÷µéÀ» ¾Ë¾Æº¸ÀÚ.


1) ½ÅÈ£ ¹× ¼¾¼­ ±â¹Ý ºÐ¼® : ÀÌ ºÐ¾ßÀÇ ±â¾÷µéÀº Á¡Æ÷¿¡¼­ °í°´ ÃßÀû, Á÷¿øµéÀÇ ¾÷¹« ½Ã°£ ÃÖÀûÈ­, ÇÒÀÎ °ü¸®, ÇÁ·Î¸ð¼Ç ¸ð´ÏÅ͸µ µî¿¡ µµ¿òÀ» ÁÖ´Â Çϵå¿þ¾î¿Í ¼ÒÇÁÆ®¿þ¾î ¼Ö·ç¼ÇÀ» Á¦°øÇÑ´Ù. ¿¹¸¦ µé¾î À¯Å¬¸®µå ¾Ö³Î¸®Æ½½º(Euclid Analytics)´Â ¹æ¹®ÀÚ¸¦ ¸ð´ÏÅ͸µÇÏ°í ÇÁ·Î¸ð¼ÇÀÌ °í°´µé·Î ÇÏ¿©±Ý ¸ÅÁ¡À» ¾ó¸¶³ª ºÕºñ°Ô ¸¸µé¾îÁÖ´ÂÁö¸¦ ÆÇ´ÜÇÏ´Â ºÐ¼® Ç÷§ÆûÀ» Á¦°øÇÑ´Ù.


2) ½ÅÈ£ ±â¹Ý ¸¶ÄÉÆà : ÀÌ ºÐ¾ßÀÇ ±â¾÷µéÀÌ Á¦°øÇÏ´Â ¼Ö·ç¼Ç ¶ÇÇÑ °í°´À» ÃßÀûÇÏÁö¸¸ ÀÌ µ¥ÀÌÅ͸¦ ¸¶ÄÉÆà ¸ñÀûÀ¸·Î »ç¿ëÇÑ´Ù. ¿¹¸¦ µé¾î, ¿¡½ºÆ¼¸ðÆ®(Estimote)´Â ±ÙóÀÇ ±¸¸ÅÀÚ ÀüÈ­±â¿¡ Á¦Ç° ¶Ç´Â ÇÁ·Î¸ð¼Ç¿¡ ´ëÇÑ ¡®Çª½Ã ¾Ë¶÷¡¯À» º¸³½´Ù. ÄɹÌÆ®¸¯(Kimetric)ÀÇ ¼¾¼­´Â ½Ã°¢ÀûÀ¸·Î ±¸¸ÅÀÚÀÇ ¿¬·É, ¼ºº°, ÀÇ·ù ½ºÅ¸ÀÏÀ» ÃßÀûÇÏ¿© °³ÀÎ ¸ÂÃãÇü ¸¶ÄÉÆÃÀ» Á¦¾ÈÇÑ´Ù.


3) ½ÅÈ£ ºÐ¼® & ¸¶ÄÉÆà : ÀÌ ºÐ¾ßÀÇ ±â¾÷µéÀº ³»ºÎ ºÐ¼®°ú ¸¶ÄÉÆà Á¶»ç¸¦ »óÈ£ ¿¬°è½ÃÅ°´Â ¼Ö·ç¼ÇÀ» Á¦°øÇÑ´Ù.


4) Àç°í ÃßÀû : ťȩ(QueueHop)Àº µµ³­À¸·ÎºÎÅÍ Á¦Ç°À» º¸È£Çϵµ·Ï ¼³°èµÈ Ư¼ö ¼¾¼­¸¦ °³¹ßÇÑ´Ù. ÀÌ ¼¾¼­´Â ±¸¸Å ÈÄ Á¦Ç°¿¡¼­ ÀÚµ¿À¸·Î ¶³¾îÁø´Ù. ¶Ç ´Ù¸¥ ½ºÅ¸Æ®¾÷ ±â¾÷ ÄÚÁö(Cozy)´Â Àü¹®ÀûÀÎ ½Ç³» ¸ÊÇÎ(mapping) ¼Ö·ç¼ÇÀ» »ç¿ëÇÏ¿©, Á¦Ç°À» ¸ð´ÏÅ͸µÇÏ´Â ·Îº¿À» °³¹ßÇÑ´Ù.


5) ½Ç³» ¸ÊÇÎ : ¾ÆÀÌÄ«Åä±×·¥(iCartogram), Àεµ¾î¶ó(Indoora), ¾ÆÀÏ411(Aisle411)°ú °°Àº ½ºÅ¸Æ®¾÷ ±â¾÷µéÀº ¸ÅÁ¡ ³»ºÎ¿Í ¼îÇθôÀÇ »ó¼¼ Áöµµ¸¦ ¸¸µç´Ù. À̸¦ ÅëÇØ ¼Ò¸Å¾÷üµéÀº ±¸¸ÅÀÚµéÀÌ ÀûÀýÇÑ Á¦Ç°À» ã°í, ÇöÀç ÇÒÀÎÀ̳ª ÇÁ·Î¸ð¼Ç¿¡ ´ëÇÑ Á¤º¸¸¦ ¾òÀ» ¼ö ÀÖµµ·Ï ÇÒ ¼ö ÀÖ´Ù.


6) ¼­ºñ½º ·Îº¿ : ½Éºñ ·Îº¸Æ½½º(Simbe Robotics)¿Í ÆÈ·Î¿ì ·Îº¿(Fellow Robots)Àº Á¦Ç°À» »¡¸® ã¾ÆÁÖ°í Á¦Ç°µéÀÌ °¢ Áø¿­´ë¿¡ ºñ¾î ÀÖÁö ¾Êµµ·Ï °ü¸®ÇÏ´Â ·Îº¿À» °³¹ßÇß´Ù. Æç·Î¿ì ·Îº¿Àº À¯Åë¾÷ü ·Î¿ì½º(Lowe¡¯s)¸¦ À§ÇØ ·Î¿ìº¿(LoweBot)À» °³¹ßÇߴµ¥, ÀÌ ·Îº¿Àº °í°´ÀÌ ¿øÇÏ´Â »óÇ°À» ãµµ·Ï µµ¿ÍÁØ´Ù. ½Éºñ·Îº¸Æ½½º°¡ °³¹ßÇÑ Å»¸®(Tally)´Â ¸ÅÀåÀ» µ¹¾Æ´Ù´Ï¸ç Àç°í¸¦ ÆľÇÇÏ°í, ¸ÅÀå ³» Àç°í ¼öÁØ°ú °¡°Ý ¿À·ù µîÀ» Áö¼ÓÀûÀ¸·Î ¸ð´ÏÅ͸µÇÑ´Ù.


7). ¼Õ½Ç ¹æÁö : °ÔÀÌƮŰÆÛ(Gatekeeper)´Â RFID¸¦ »ç¿ëÇÏ¿© Ä«Æ®¿¡ ÀÚµ¿ ¹ÙÄû Àá±Ý ±â´ÉÀ» Á¦°øÇÑ´Ù. ¼ÒºñÀÚ°¡ °áÁ¦¸¦ ÇÏÁö ¾ÊÀ¸¸é ÀÌ ±â´ÉÀÌ È°¼ºÈ­µÇ¾î ¼îÇÎ Ä«Æ®°¡ ¿òÁ÷ÀÌÁö ¾Ê´Â´Ù.


8) °¡Á¤³»(at-home) ¼îÇÎ ¹öÆ° : ½ºÅ¸Æ®¾÷ ±â¾÷ ÄûÅ©(Kwik)¿Í È÷Äí(Hiku)´Â »ç¿ëÀÚ°¡ °¡Á¤¿¡¼­ Á÷Á¢ ´Ù¸¥ Á¦Ç°µéÀ» ÁÖ¹®ÇÒ ¼ö Àִ Ưº° ÀåÄ¡¸¦ Á¦°øÇÑ´Ù. ¾Æ¸¶Á¸(Amazon)ÀÇ ¿øŬ¸¯(One-Click) ¹öÆ°°ú ¸¶Âù°¡Áö·Î, ÄûÅ©´Â Ŭ¸¯ ÇÑ ¹øÀ¸·Î Á¦Ç°À» ÀçÁÖ¹®ÇÒ ¼ö ÀÖ°Ô ÇØÁØ´Ù. È÷ÄíÀÇ ÀåÄ¡´Â ¹ÙÄڵ带 ½ºÄµÇÏ¿© ÀçÁÖ¹®ÇÒ »óÇ°À» ½Äº°ÇÏ°í »ç¿ëÀÚÀÇ ¸ñ¼Ò¸®¸¦ ÀνÄÇÒ ¼ö ÀÖ´Ù.


9) ½º¸¶Æ® µå·¹½Ì ·ë : ±¸¸ÅÀÚ°¡ ¡®ÆǸŠ¸ÅÀ塯¿¡¼­ ¿©·¯ ¹ø¿¡ °ÉÃÄ ¿ÊÀ» ¿äûÇÏ°í, ÇÇÆà ·ë¿¡¼­ ÀÔ°í È®ÀÎÇÏ´Â °ÍÀÌ ¿À´Ã³¯ ÀÇ·ù ¼îÇÎÀÇ Çö½ÇÀÌ´Ù. ¿ÀÅ©·¦½º(Oak Labs)´Â RFID ű׸¦ È°¿ëÇÏ¿© ´ëÈ­ Çü ÅÍÄ¡½ºÅ©¸° ¹Ì·¯¸¦ Á¦ÀÛ, ±¸¸ÅÀÚ°¡ Á¦Ç°À» °¡Á® ¿Í¼­ ¾î¶² °ü·Ã Á¦Ç°°ú ÇÔ²² ÃßõÀ» ¹ÞÀ» ¼ö ÀÖ´ÂÁö °áÁ¤ÇÒ ¼ö ÀÖµµ·Ï Çß´Ù. ÀÌ¹Ì Æú·Î ¶öÇÁ ·Î·»(Polo Ralph Lauren) ¸ÅÀå¿¡¼­ ¼º°øÀûÀ¸·Î ¿î¿ëÀÌ ½ÃÀ۵ǰí ÀÖ´Ù.


ÀÌ·¯ÇÑ ÀÀ¿ë ÇÁ·Î±×·¥µéÀº »ç¹°ÀÎÅͳÝÀÇ ½ÃÀÛ¿¡ ºÒ°úÇÕ´Ï´Ù. »ç¹°ÀÎÅͳÝÀÌ ¾ÕÀ¸·Î ´õ Àú·ÅÇØÁö°í À¯ºñÄõÅͽºÈ­µÊ¿¡ µû¶ó Àΰ£ÀÇ »ó»ó·ÂÀº ±×¸¸Å­ ´õ Å©°Ô È®ÀåµÉ °ÍÀÌ´Ù.


* *

References List :


1. Gartner.com. February 7, 2017. Gartner Says 8.4 Billion Connected ¡°Things¡± Will Be in Use in 2017, Up 31 Percent From 2016
http://www.gartner.com/newsroom/id/3598917


2. R-Stylelab.com. May 18, 2017. Andrei Klubnikin. IoT in Business: from Cost Reduction to Revenue Growth.
http://r-stylelab.com/company/blog/iot/iot-in-business-from-cost-reduction-to-revenue-growth


3. DHL.com. April 15, 2015. DHL and Cisco Internet of Things Trend Report
http://www.dhl.com/en/about_us/logistics_insights/dhl_trend_research/internet_of_things.html#.WdTs0zDdkUE


4. Computerweekly.com. 22 Jul 2015. Cliff Saran. Investment in the internet of things boosts revenue for manufacturers.
http://www.computerweekly.com/news/4500250349/Investment-in-IOT-drives-revenue-boost-for-manufacturers


5. R-Stylelab.com. June 19, 2017 Maxim Lyashko. Internet of Things in Retail: Meet Smartstores.
http://r-stylelab.com/sciencemag.org/sites/default/files/styles/inline__699w__no_aspect/public/GG_AI_JB.png?itok=7DCjrahK




ÀÌÀü

¸ñ·Ï