¼¼°è ÀÚÀ²Çü ÀÛ¹° °ü¸® ½ÃÀå
Autonomous Crop Management
»óǰÄÚµå : 1536120
¸®¼­Ä¡»ç : Global Industry Analysts, Inc.
¹ßÇàÀÏ : 2024³â 08¿ù
ÆäÀÌÁö Á¤º¸ : ¿µ¹® 376 Pages
 ¶óÀ̼±½º & °¡°Ý (ºÎ°¡¼¼ º°µµ)
US $ 5,850 £Ü 8,263,000
PDF (Single User License) help
PDF º¸°í¼­¸¦ 1¸í¸¸ ÀÌ¿ëÇÒ ¼ö ÀÖ´Â ¶óÀ̼±½ºÀÔ´Ï´Ù. Àμâ´Â °¡´ÉÇϸç Àμ⹰ÀÇ ÀÌ¿ë ¹üÀ§´Â PDF ÀÌ¿ë ¹üÀ§¿Í µ¿ÀÏÇÕ´Ï´Ù.
US $ 17,550 £Ü 24,789,000
PDF (Global License to Company and its Fully-owned Subsidiaries) help
PDF º¸°í¼­¸¦ µ¿ÀÏ ±â¾÷ÀÇ ¸ðµç ºÐÀÌ ÀÌ¿ëÇÒ ¼ö ÀÖ´Â ¶óÀ̼±½ºÀÔ´Ï´Ù. Àμâ´Â °¡´ÉÇϸç Àμ⹰ÀÇ ÀÌ¿ë ¹üÀ§´Â PDF ÀÌ¿ë ¹üÀ§¿Í µ¿ÀÏÇÕ´Ï´Ù.


Çѱ۸ñÂ÷

ÀÚÀ²Çü ÀÛ¹° °ü¸® ¼¼°è ½ÃÀåÀº 2030³â±îÁö 50¾ï ´Þ·¯¿¡ À̸¦ °ÍÀ¸·Î ¿¹»ó

2023³â¿¡ 19¾ï ´Þ·¯·Î ÃßÁ¤µÇ´Â ÀÚÀ²Çü ÀÛ¹° °ü¸® ¼¼°è ½ÃÀåÀº 2030³â¿¡´Â 50¾ï ´Þ·¯¿¡ À̸£°í, ºÐ¼® ±â°£ 2023-2030³âÀÇ CAGRÀº 14.8%·Î ¼ºÀåÇÒ °ÍÀ¸·Î ¿¹ÃøµË´Ï´Ù. ÀÌ º¸°í¼­¿¡¼­ ºÐ¼®ÇÑ ºÎ¹® Áß ÇϳªÀÎ ÀÚÀ²Çü ÀÛ¹° °ü¸® ¼ÒÇÁÆ®¿þ¾î´Â CAGR 14.4%·Î ¼ºÀåÀ» Áö¼ÓÇϰí, ºÐ¼® ±â°£ Á¾·á ½Ã 32¾ï ´Þ·¯¿¡ ´ÞÇÒ °ÍÀ¸·Î ¿¹ÃøµË´Ï´Ù. ÀÚÀ²Çü ÀÛ¹° °ü¸® ¼­ºñ½º ºÐ¾ßÀÇ ¼ºÀå·üÀº ºÐ¼® ±â°£ µ¿¾È CAGR 15.6%·Î ÃßÁ¤µË´Ï´Ù.

¹Ì±¹ ½ÃÀåÀº 5¾ï 1,750¸¸ ´Þ·¯, Áß±¹Àº CAGR 19.6%·Î ¼ºÀå ¿¹Ãø

¹Ì±¹ ÀÚÀ²Çü ÀÛ¹° °ü¸® ½ÃÀåÀº 2023³â 5¾ï 1,750¸¸ ´Þ·¯·Î ÃßÁ¤µË´Ï´Ù. ¼¼°è 2À§ °æÁ¦´ë±¹ÀÎ Áß±¹Àº 2030³â±îÁö 11¾ï ´Þ·¯ ±Ô¸ð¿¡ À̸¦ °ÍÀ¸·Î ¿¹ÃøµÇ¸ç ºÐ¼® ±â°£ 2023-2030³âÀÇ CAGRÀº 19.6%ÀÔ´Ï´Ù. ±âŸ ÁÖ¸ñÇÒ ¸¸ÇÑ Áö¿ªº° ½ÃÀåÀ¸·Î´Â ÀϺ»°ú ij³ª´Ù°¡ ÀÖÀ¸¸ç, ºÐ¼® ±â°£ Áß CAGRÀº °¢°¢ 11.2%¿Í 13.0%·Î ¿¹ÃøµÇ°í ÀÖ½À´Ï´Ù. À¯·´¿¡¼­´Â µ¶ÀÏÀÌ CAGR 11.8%·Î ¼ºÀåÇÒ °ÍÀ¸·Î ¿¹ÃøµË´Ï´Ù.

¼¼°è ÀÚÀ²Çü ÀÛ¹° °ü¸® ½ÃÀå - ÁÖ¿ä µ¿Çâ°ú ÃËÁø¿äÀÎ ¿ä¾à

ÀÚÀ²Çü ÀÛ¹° °ü¸®´Â ÀΰøÁö´É(AI), ¸Ó½Å·¯´×, ·Îº¿°øÇÐÀ» Ȱ¿ëÇÏ¿© ÀÛ¹°»ý»êÀÇ È¿À²¼º°ú Áö¼Ó°¡´É¼ºÀ» ³ôÀÌ´Â ³ó¾÷±â¼úÀÇ º¯ÇõÀû Áøº¸¸¦ »ó¡ÇÕ´Ï´Ù. ÀÌ Çõ½ÅÀûÀÎ Á¢±Ù ¹æ½ÄÀº ÀÚµ¿ Æ®·¢ÅÍ, ÀÛ¹° ¸ð´ÏÅ͸µ µå·Ð, ·Îº¿ ¼öÈ®±â µî ´Ù¾çÇÑ ½Ã½ºÅÛÀ» Æ÷ÇÔÇÕ´Ï´Ù. ÀÌ ½Ã½ºÅÛÀº ¼¾¼­¿Í µ¥ÀÌÅÍ ºÐ¼®ÀÇ Á¶ÇÕÀ» Ȱ¿ëÇÏ¿© ÀÛ¹°ÀÇ °Ç°­ »óÅÂ, Åä¾ç »óÅ ¹× ȯ°æ ¿äÀÎÀ» Àü·Ê ¾ø´Â Á¤È®µµ·Î ¸ð´ÏÅ͸µÇÕ´Ï´Ù. ÀÌ »ó¼¼ÇÑ ¸ð´ÏÅ͸µÀ» ÅëÇØ ¹°, ºñ·á ¹× ³ó¾àÀÇ Á¤È®ÇÑ ºÐ»êÀ» °¡´ÉÇÏ°Ô ÇÏ¿© ÀÚ¿ø Ȱ¿ëÀ» ÃÖÀûÈ­ÇÒ »Ó¸¸ ¾Æ´Ï¶ó ³¶ºñ¸¦ ¾ø¾Ö°í ºñ¿ëÀ» Àý°¨ÇÒ ¼ö ÀÖ½À´Ï´Ù. ¿¹¸¦ µé¾î, ÀÚµ¿ Æ®·¢ÅÍ´Â °æÀÛ, ½É±â, »ìÆ÷ µîÀÇ ÀÛ¾÷À» ³ôÀº Á¤¹Ðµµ·Î ¼öÇàÇÒ ¼ö ÀÖÀ¸¸ç, ¸ÖƼ½ºÆåÆ®·³ Ä«¸Þ¶ó¸¦ žÀçÇÑ µå·ÐÀº ³ÐÀº ¹çÀ» Á¶»çÇÏ¿© À°¾ÈÀ¸·Î´Â º¸ÀÌÁö ¾Ê´Â ¹®Á¦¸¦ °ËÃâÇÒ ¼ö ÀÖ½À´Ï´Ù. ·Îº¿ ¼öÈ®±â´Â °úÀÏ ¹× ä¼Ò¸¦ ÃÖ¼ÒÇÑÀÇ ÇÇÇØ·Î ¼öÈ®ÇÒ ¼ö ÀÖ¾î °íǰÁúÀÇ ³ó»ê¹°À» È®º¸Çϰí ÀΰǺñ¸¦ Àý°¨ÇÒ ¼ö ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ ±â¼úÀ» ÅëÇÕÇÔÀ¸·Î½á ³óÀÛ¹°Àº ÇÊ¿äÇÒ ¶§ ÇÊ¿äÇÑ Ä¡·á¸¦ ¹ÞÀ» ¼ö ÀÖ¾î ¼öÀ²ÀÌ Çâ»óµÇ°í ³óÀå ÀüüÀÇ »ý»ê¼ºÀÌ Çâ»óµË´Ï´Ù.

ÀÚÀ²Çü ÀÛ¹° °ü¸®ÀÇ Áß¿äÇÑ ¿ä¼Ò´Â Á¤¹Ð ³ó¾÷ÀÔ´Ï´Ù. ÀÌ ¹æ¹ýÀº GPS ±â¼ú°ú IoT(»ç¹° ÀÎÅͳÝ) ÀåÄ¡¸¦ Ȱ¿ëÇÏ¿© ÇöÀå¿¡¼­ ½Ç½Ã°£ µ¥ÀÌÅ͸¦ ¼öÁýÇÕ´Ï´Ù. ±×¸®°í °í±Þ ¾Ë°í¸®ÁòÀÌ ÀÌ µ¥ÀÌÅ͸¦ ºÐ¼®ÇÏ°í ½Ç¿ëÀûÀÎ ÅëÂû·ÂÀ» Á¦°øÇÔÀ¸·Î½á ³óºÎ´Â ÀÛ¹°ºÎÅÍ ¼öÈ®±îÁö ÀÛ¹° °ü¸®ÀÇ ¸ðµç Ãø¸é¿¡ ´ëÇÑ Á¤º¸¸¦ ¹ÙÅÁÀ¸·Î ÀÇ»ç °áÁ¤À» ³»¸± ¼ö ÀÖ½À´Ï´Ù. ¿¹¸¦ µé¾î, ¹«ÀÎ Ç×°ø±â´Â ¹çÀÇ »ó°øÀ» ºñÇàÇÏ°í °í±Þ À̹ÌÁö ó¸® ±â¼úÀ» »ç¿ëÇÏ¿© ÀÛ¹°ÀÇ »ó¼¼ÇÑ À̹ÌÁö¸¦ ÃÔ¿µÇÒ ¼ö ÀÖ½À´Ï´Ù. ÀÌ À̹ÌÁö´Â ÀΰøÁö´ÉÀ» »ç¿ëÇÏ¿© 󸮵Ǿî Áúº´°ú ÇØÃæÀÇ ¹ß»ý, ¿µ¾ç ºÎÁ·ÀÇ Â¡Èĸ¦ Á¶±â¿¡ ½Äº°Çϰí Àû½Ã¿¡ Àû±ØÀûÀÎ °³ÀÔÀÌ °¡´ÉÇÕ´Ï´Ù. ÀÚÀ²ÁÖÇà Æ®·¢ÅÍ ¹× »ìÆ÷±â¿Í °°Àº ÀÚÀ²ÁÖÇà Â÷·®Àº AI¸¦ »ç¿ëÇÏ¿© Á¤È®ÇÏ°Ô ¹çÀ» Ž»öÇÏ°í ¹ß¾ÆÀ²°ú ÀÛ¹°ÀÇ ±ÕÀϼºÀ» ±Ø´ëÈ­Çϱâ À§ÇØ ÃÖÀûÀÇ ±íÀÌ¿Í °£°ÝÀ¸·Î ¾¾¾ÑÀ» ½É½À´Ï´Ù. ÀÌ Á¤È®µµ°¡ ³ôÀ¸¸é ºñ·á¿Í ³ó¾àÀ» °úµµÇÏ°Ô »ç¿ëÇÒ Çʿ䰡 ÁÙ¾îµé°í À¯Ãâ°ú Åä¾çÀÇ ¿­È­¸¦ ÃÖ¼ÒÈ­ÇÏ¿© ȯ°æ¿¡ ±â¿©ÇÕ´Ï´Ù. ¶ÇÇÑ ÀÌ ½Ã½ºÅÛÀº 24½Ã°£ µ¿¾È ´Ù¾çÇÑ ±â»ó Á¶°Ç¿¡¼­ ÀÛµ¿ÇÒ ¼ö ÀÖÀ¸¹Ç·Î ÀÛ¹°ÀÇ °Ç°­ À¯Áö ¹× ¼öÀ²À» ±Ø´ëÈ­ÇÏ´Â µ¥ ÇʼöÀûÀÎ ÀÛ¾÷À» ºü¸£°í È¿À²ÀûÀ¸·Î ¿Ï·áÇÒ ¼ö ÀÖ½À´Ï´Ù.

ÀÚÀ²Çü ÀÛ¹° °ü¸® ½ÃÀåÀÇ ¼ºÀåÀº ¿©·¯ ¿äÀο¡ ÀÇÇØ ¹ß»ýÇÕ´Ï´Ù. ù°, ¼¼°è Àα¸ Áõ°¡¿Í ÀÌ¿¡ µû¸¥ ½Ä·® ¼ö¿ä Áõ°¡·Î ³ó¾÷ ºÎ¹®Àº ½Ä·® ¾Èº¸¸¦ º¸ÀåÇϱâ À§ÇØ º¸´Ù È¿À²ÀûÀ̰í È®Àå °¡´ÉÇÑ ±â¼úÀ» µµÀÔÇÒ Çʿ䰡 ÀÖ½À´Ï´Ù. µÑ°, ÀΰǺñ »ó½Â°ú ¼÷·ÃµÈ ³ó¾÷ ³ëµ¿ÀÚ ºÎÁ·Àº ÀÚµ¿È­¸¦ ¸Å·ÂÀûÀ̰í ÇÊ¿äÇÑ ´ë¾ÈÀ¸·Î »ï°í ÀÖ½À´Ï´Ù. ¼Â°, AI¿Í ·Îº¿ °øÇÐÀÇ ¹ßÀüÀ¸·Î ÀÚÀ² ½Ã½ºÅÛÀÇ ½Å·Ú¼º, È¿À²¼º, ºñ¿ë È¿À²¼ºÀÌ Çâ»óµÇ°í ³óºÎ¿¡ µµÀÔÀÌ ÁøÇàµÇ°í ÀÖ½À´Ï´Ù. ³Ý°, Áö¼Ó °¡´ÉÇÑ ³ó¾÷ °üÇàÀÇ Çʿ伺¿¡ ´ëÇÑ ÀνÄÀÌ ³ô¾ÆÁö°í ÀÖÀ¸¸ç, ȯ°æ¿¡ ¹ÌÄ¡´Â ¿µÇâÀ» ¾ïÁ¦Çϸ鼭 »ý»ê¼ºÀ» Çâ»ó½ÃŰ´Â ±â¼úÀÇ µµÀÔÀÌ ÃËÁøµÇ°í ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ °üÇà¿¡´Â Á¤È®ÇÑ ÅõÀÔ ÀÚÀçÀÇ »ìÆ÷, ¹° »ç¿ë·®ÀÇ »è°¨, È­Çй°ÁúÀÇ À¯Ãâ ÃÖ¼ÒÈ­ µîÀÌ Æ÷ÇԵ˴ϴÙ. °Ô´Ù°¡, Çö´ëÀûÀÎ ³ó¾÷ °üÇàÀ» ÃËÁøÇϱâ À§ÇÑ Á¤ºÎÀÇ ÀÌ´Ï¼ÅÆ¼ºê¿Í º¸Á¶±ÝÀº ³óºÎµéÀÌ ÀÚÀ² ±â¼ú¿¡ ÅõÀÚÇϱâ À§ÇÑ °æÁ¦Àû Àμ¾Æ¼ºê°¡ µÇ°í ÀÖ½À´Ï´Ù. ÀÌ·¯ÇÑ ¿øµ¿·ÂÀº ÃÑü·Î¼­, ³ó¾÷ÀÇ ¹Ì·¡¸¦ Çü¼ºÇϴµ¥ À־ ÀÚÀ²Çü ÀÛ¹° °ü¸®°¡ ¿Ï¼öÇÏ´Â ¿ªÇÒÀÇ Á߿伺À» ºÎ°¢Çϰí ÀÖ½À´Ï´Ù. ½Ä·®¾Èº¸, Áö¼Ó°¡´É¼º, °æÁ¦¼º µîÀÇ °úÁ¦¿¡ ÀÓÇÔÀ¸·Î½á ÀÚÀ²Çü ÀÛ¹° °ü¸®´Â Çö´ë³ó¾÷ÀÇ Ãʼ®ÀÌ µÇ¾î 21¼¼±â ¼ö¿ä¿¡ ºÎÀÀÇÏ´Â ³ó¾÷À» ½ÇÇöÇÕ´Ï´Ù.

Á¶»ç ´ë»ó ±â¾÷ ¿¹(Àü 43°Ç)

¸ñÂ÷

Á¦1Àå Á¶»ç ¹æ¹ý

Á¦2Àå ÁÖ¿ä ¿ä¾à

Á¦3Àå ½ÃÀå ºÐ¼®

Á¦4Àå °æÀï

JHS
¿µ¹® ¸ñÂ÷

¿µ¹®¸ñÂ÷

Global Autonomous Crop Management Market to Reach US$5.0 Billion by 2030

The global market for Autonomous Crop Management estimated at US$1.9 Billion in the year 2023, is expected to reach US$5.0 Billion by 2030, growing at a CAGR of 14.8% over the analysis period 2023-2030. Autonomous Crop Management Software, one of the segments analyzed in the report, is expected to record a 14.4% CAGR and reach US$3.2 Billion by the end of the analysis period. Growth in the Autonomous Crop Management Services segment is estimated at 15.6% CAGR over the analysis period.

The U.S. Market is Estimated at US$517.5 Million While China is Forecast to Grow at 19.6% CAGR

The Autonomous Crop Management market in the U.S. is estimated at US$517.5 Million in the year 2023. China, the world's second largest economy, is forecast to reach a projected market size of US$1.1 Billion by the year 2030 trailing a CAGR of 19.6% over the analysis period 2023-2030. Among the other noteworthy geographic markets are Japan and Canada, each forecast to grow at a CAGR of 11.2% and 13.0% respectively over the analysis period. Within Europe, Germany is forecast to grow at approximately 11.8% CAGR.

Global Autonomous Crop Management Market - Key Trends and Drivers Summarized

Autonomous crop management represents a transformative advancement in agricultural technology, leveraging artificial intelligence (AI), machine learning, and robotics to enhance crop production efficiency and sustainability. This innovative approach encompasses a variety of systems, including automated tractors, drones for crop monitoring, and robotic harvesters. These systems utilize a combination of sensors and data analytics to monitor crop health, soil conditions, and environmental factors with unprecedented precision. This detailed monitoring enables the precise application of water, fertilizers, and pesticides, which not only optimizes resource use but also reduces waste and lowers costs. For instance, automated tractors can perform tasks such as plowing, planting, and spraying with high accuracy, while drones equipped with multispectral cameras can survey large fields to detect issues that are not visible to the naked eye. Robotic harvesters can pick fruits and vegetables with minimal damage, ensuring higher quality produce and reducing labor costs. The integration of these technologies ensures that crops receive the exact care they need at the right time, enhancing yields and improving overall farm productivity.

A critical component of autonomous crop management is precision agriculture. This approach utilizes GPS technology and IoT (Internet of Things) devices to gather real-time data from the field. Advanced algorithms then analyze this data to provide actionable insights, enabling farmers to make informed decisions about every aspect of crop management, from planting to harvesting. For instance, drones can fly over fields and use advanced imaging technologies to capture detailed images of crops. These images are processed using AI to identify signs of disease, pest infestations, or nutrient deficiencies early, allowing for timely and targeted interventions. Autonomous vehicles, such as self-driving tractors and sprayers, use AI to navigate fields with high precision, planting seeds at optimal depths and spacing to maximize germination rates and crop uniformity. This precision reduces the need for excessive use of fertilizers and pesticides, which benefits the environment by minimizing runoff and soil degradation. Moreover, these systems can operate around the clock and in various weather conditions, ensuring that tasks are completed promptly and efficiently, which is crucial for maintaining crop health and maximizing yields.

The growth in the autonomous crop management market is driven by several factors. First, the increasing global population and the corresponding demand for food are pushing the agricultural sector to adopt more efficient and scalable technologies to ensure food security. Second, rising labor costs and a shortage of skilled farm workers are making automation an attractive and necessary alternative. Third, advancements in AI and robotics are making autonomous systems more reliable, efficient, and cost-effective, thereby increasing their adoption among farmers. Fourth, there is a growing awareness of the need for sustainable farming practices, which is encouraging the adoption of technologies that can enhance productivity while reducing environmental impacts. These practices include precise application of inputs, reduced water usage, and minimal chemical runoff. Additionally, government initiatives and subsidies aimed at promoting modern agricultural practices are providing financial incentives for farmers to invest in autonomous technologies. These drivers collectively underscore the crucial role of autonomous crop management in shaping the future of agriculture. By addressing the challenges of food security, sustainability, and economic viability, autonomous crop management is set to become a cornerstone of modern farming, ensuring that agricultural practices can meet the demands of the 21st century.

Select Competitors (Total 43 Featured) -

TABLE OF CONTENTS

I. METHODOLOGY

II. EXECUTIVE SUMMARY

III. MARKET ANALYSIS

IV. COMPETITION

(ÁÖ)±Û·Î¹úÀÎÆ÷¸ÞÀÌ¼Ç 02-2025-2992 kr-info@giikorea.co.kr
¨Ï Copyright Global Information, Inc. All rights reserved.
PC¹öÀü º¸±â