Artificial Intelligence
Deep Learning Market: Focus on Medical Image Processing, 2020-2030
New York, Nov. 17, 2020 (GLOBE NEWSWIRE) — Reportlinker.com announces the release of the report “Deep Learning Market: Focus on Medical Image Processing, 2020-2030” – https://www.reportlinker.com/p05987918/?utm_source=GNW
This technology is gradually being incorporated in a variety of applications across the healthcare sector, including imaging-based medical diagnosis and data processing. Specifically concerning medical imaging, deep learning has the potential to be used to automate information processing and result interpretation for a variety of diagnostic images, such as X-rays, computed tomography scans, magnetic resonance imaging, and positron emission tomography. In this context, it is worth mentioning that the manual examination of medical images is limited, both in terms of accuracy (resulting in misdiagnosis) and throughput (leading to delays in communication of results). As a result, in situations characterized by low physician / pathologist to patient ratios, the conventional mode of operation is rendered inadequate. Experts have predicted a shortage of 10,000 to 40,000 physicians, by 2030, in the US alone. Further, it is estimated that 90% of medical data generated in hospitals is in the form of images; this puts an immense burden on radiologists and other consulting physicians related to processing such large volumes of data. In fact, according to a study published in the American Journal of Medicine, ~15% of reported medical cases in developed countries, are misdiagnosed. In addition, close to 1.5 million individuals are estimated to die each year, across the world, due to misdiagnosis. On the other hand, accurate diagnosis at an early stage has been demonstrated to allow significant cost savings for both patients and healthcare providers. In this scenario, deep learning and other artificial intelligence-based technologies are currently being developed / investigated to automate such processes.
Over time, various industry stakeholders have designed proprietary deep learning algorithms for processing of medical images. Presently, many innovators claim to have developed the means to train computers to read and triage medical images, and recognize patterns related to both temporal and spatial changes (which are not even visible to the naked eye). Experts in this field also believe that the use of deep learning can actually speed up the processing and interpretation of radiology data by 20%, reducing the rate of false positives by approximately 10%. It is also worth mentioning that in the past few years, the FDA has provided the necessary clearances and approved the use for a variety of deep learning software. Moreover, several technology-focused innovators, such as (in alphabetical order) IBM, GE Healthcare and Google, have entered into strategic alliances with big pharma players, in order to bring proprietary deep learning-based medical solutions to the market. This upcoming segment of the pharmaceutical industry that exists at the interface between medicine and information technology, has garnered the attention of prominent venture capital firms and strategic investors. In the long term, the market is anticipated witness significant growth as more machine learning based solutions are approved for use.
SCOPE OF THE REPORT
The ‘Deep Learning Market: Focus on Medical Image Processing, 2020-2030’ report features an extensive study on the current market landscape offering an informed opinion on the likely adoption of such solutions over the next decade. The study presents an in-depth analysis, highlighting the capabilities of various stakeholders engaged in this domain. In addition to other elements, the report provides:
– A detailed review of the current market landscape of deep learning solutions for medical image processing, along with information on their status of development (launched / under development), regulatory approvals (FDA, CE mark, others), type of offering (diagnostic software / tool, diagnostic software / tool + device), type of image processed (X-ray, MRI, CT, ultrasound), application area (lung infections / respiratory disorders, brain injuries / disorders, lung cancer, cardiac conditions / cardiovascular disorders, bone deformities / orthopedic disorders, breast cancer and others). In addition, it presents details of companies developing such solutions, such as their year of establishment, company size, location of headquarters and focus area (in terms of type of deployment model). Further, it highlights key features of each solution and affiliated technologies.
– An in-depth analysis of the contemporary market trends, presented using three schematic representations, including [A] a grid representation illustrating the distribution of solutions based on application area, type of image processed and type of offering and [B] an insightful map representation highlighting the geographical activity of the players.
– Elaborate profiles of key players that are engaged in the development of deep learning-based solutions intended for processing of medical images. Each company profile features a brief overview of the company (including information on year of establishment, number of employees, location of headquarters and key members of the executive team), details of their respective portfolio of solutions, recent developments and an informed future outlook.
– An analysis of the partnerships that have been inked by stakeholders in the domain, during the time period 2016-2020 (till June), covering research / development agreements, solution utilization agreements, solution integration agreements, marketing / distribution agreements, other relevant types of deals.
– An analysis of the investments made, including seed financing, venture capital financing, debt financing, grants and others, in companies that are focused on developing deep learning-based solutions intended for processing of medical images.
– An elaborate valuation analysis of companies that are involved in applying deep learning in solutions intended for processing of medical images. Further, we have built a multi-variable dependent valuation model to estimate the current valuation of a number of companies engaged in this domain.
– A clinical trial analysis of completed, ongoing and planned studies (available on ct.gov), focused on the assessment deep learning-based software solutions, based on various parameters, such as trial registration year, trial recruitment status, trial design, target therapeutic area, leading industry and non-industry players, and geographical locations of trials.
– An in-depth analysis of over 3,000 patents related to deep learning and medical images that have been filed / granted till June 2020, highlighting key trends associated with these patents, across type of patent, publication year and application year, regional applicability, CPC symbols, emerging focus areas, leading patent assignees (in terms of number of patents filed / granted), patent benchmarking and valuation.
– An insightful analysis highlighting cost saving potential associated with the use of deep learning solutions intended for processing of medical images, based on information gathered from close to 30 countries, taking into consideration various parameters, such as total number of radiologists, annual salary of radiologists, number of scans performed (across each type of image) and increase in efficiency by adoption of deep learning solutions.
– An insightful discussion on the views presented by various industry and non-industry experts present across the globe, on various portals, such as YouTube and other media platforms. The summary of insights provided by each expert is discussed across focus area, current industry status / challenges and future outlook.
One of the key objectives of this report was to estimate the existing market size and the future growth potential within the deep learning market (medical image processing segment), such as global radiology spending across countries, number of radiologists employed across different regions of globe, annual salary of radiologists, rate of adoption of deep learning-based solutions, we have developed informed estimates on the financial evolution of the market, over the period 2020-2030. The report also provides details on the likely distribution of the current and forecasted opportunity across [A] application area (lung infections / respiratory disorders, brain injuries / disorders, lung cancer, cardiac conditions / cardiovascular disorders, bone deformities / orthopedic disorders, breast cancer and others), [B] type of image processed (X-ray, MRI, CT, ultrasound) and [C] region (North America, Europe and Asia Pacific / Rest of the World). In order to account for future uncertainties and to add robustness to our forecast model, we have provided three scenarios, namely conservative, base and optimistic scenarios, representing different tracks of the industry’s growth.
The opinions and insights presented in the report were also influenced by discussions held with multiple stakeholders in this domain. The report features detailed transcripts of interviews held with the following individuals (in alphabetical order):
– Walter de Back (Research Scientist, Context Vision, Q2 2020)
– Anonymous (CEO, India-based Company, Q2 2020)
– Babak Rasolzadeh (Senior Director of Product, Arterys, Q2 2020)
– Carla Leibowitz, (Head of Strategy and Marketing, Arterys, Q2 2017)
– Mausumi Acharya, (CEO, Advenio Technosys, Q2 2017)
– Deekshith Marla, (CTO, Arya.ai) and Sanjay Bhadra, (COO, Arya.ai, Q2 2017)
All actual figures have been sourced and analyzed from publicly available information forums. Financial figures mentioned in this report are in USD, unless otherwise specified.
RESEARCH METHODOLOGY
The data presented in this report has been gathered via secondary and primary research. For all our projects, we conduct interviews with experts in the area (academia, industry, medical practice and other associations) to solicit their opinions on emerging trends in the market. This is primarily useful for us to draw out our own opinion on how the market will evolve across different regions and technology segments. Where possible, the available data has been checked for accuracy from multiple sources of information.
The secondary sources of information include
– Annual reports
– Investor presentations
– SEC filings
– Industry databases
– News releases from company websites
– Government policy documents
– Industry analysts’ views
While the focus has been on forecasting the market over the coming 10 years, the report also provides our independent view on various technological and non-commercial trends emerging in the industry. This opinion is solely based on our knowledge, research and understanding of the relevant market gathered from various secondary and primary sources of information.
KEY QUESTIONS ANSWERED
– Who are the leading developers of deep learning-based solutions for medical image processing?
– What are the key application areas for deep learning solutions designed for processing of medical images, such as X-Ray, ultrasound, CT, MRI and others?
– How many solutions based on deep learning technology for processing of medical images have been cleared by FDA or have received CE marking?
– What is the impact of COVID-19 on the demand for deep learning solutions designed for processing of medical images?
– What is the likely valuation / net worth of companies involved in this segment?
– What is the likely cost saving potential associated with the use of deep learning-based solutions for processing of medical images?
– How is the current and future opportunity likely to be distributed across key market segments?
– What is the potential usability of deep learning-based medical image processing solutions for lung scanning in COVID-19 patients?
– Which partnership models are commonly adopted by stakeholders in this industry?
– What is the overall trend of funding and investments in this domain?
– What are the opinions of key opinion leaders involved in the deep learning space?
CHAPTER OUTLINES
Chapter 2 is an executive summary of the key insights captured in our research. It offers a high-level view on the current state of deep learning in medical image processing market and its likely evolution in the short-mid term and long term.
Chapter 3 is an introductory chapter that presents details on the digital revolution in the medical industry. It elaborates on the growth of artificial intelligence and machine learning tools, such as deep learning algorithms, along with a discussion on their potential applications in solving some of the key challenges faced by the healthcare industry. The chapter also gives an overview on the rise of big data and its role in providing personalized and evidence-based care to patients. It emphasizes on the applications of deep learning in healthcare sector with detailed information on areas including personalized medicine and drug discovery, personal fitness and lifestyle management, clinical trial management and medical image processing. Additionally, it includes an analysis of contemporary trends, as observed on the Google Trends (till August 2020) and insights from the recent news articles related to deep learning and medical image processing, indicating the increasing popularity of this domain.
Chapter 4 presents a case study on two technology giants in this field, namely IBM and Google. It provides a detailed description of the initiatives being undertaken by these companies to explore the applications of deep learning in the medical field. In addition, the chapter provides a comparison of the two companies based on their respective deep learning expertise, and partnerships and acquisitions.
Chapter 5 includes a detailed analysis of the current market landscape of over 200 deep learning-based medical image processing solutions, based on status of development (launched / under development), regulatory approvals (FDA, CE marked, others), type of offering (diagnostic software / tool, diagnostic software / tool + device), type of image processed (X-ray, MRI, CT, ultrasound) and application area (lung infections / respiratory disorders, brain injuries / disorders, lung cancer, cardiac conditions / cardiovascular disorders, bone deformities / orthopedic disorders, breast cancer and others).
In addition, it presents details of companies developing such solutions, such as their year of establishment, company size, location of headquarters and focus area (in terms of type of deployment model). Further, it highlights key features of each solution and affiliated technologies. It also includes an in-depth analysis of the contemporary market trends, presented using three schematic representations, including [A] a grid representation illustrating the distribution of solutions based on application area, type of image processed and type of offering and [B] an insightful map representation highlighting the geographical activity of the players.
Chapter 6 features elaborate profiles of key players that are engaged in the development of deep learning-based solutions intended for processing of medical images. Each company profile features a brief overview of the company (including information on year of establishment, number of employees, location of headquarters and key members of the executive team), details of their respective portfolio of solutions, recent developments and an informed future outlook.
Chapter 7 features an in-depth analysis and discussion on the various partnerships that have been inked by stakeholders in the domain, during the time period between 2016 and 2020 (till June), covering research / development agreements, solution utilization agreements, solution integration agreements, marketing / distribution agreements, other relevant types of deals.
Chapter 8 includes a detailed analysis of the investments made, including seed financing, venture capital financing, debt financing, grants, and others, in companies that are focused on developing deep learning-based solutions intended for processing of medical images.
Chapter 9 is a detailed valuation analysis of companies that are involved in applying deep learning in solutions intended for processing of medical images. Further, we have built a multi-variable dependent valuation model to estimate the current valuation of a number of companies engaged in this domain.
Chapter 10 represents an elaborate clinical trial analysis of completed, ongoing and planned studies (available on ct.gov), focused on the assessment deep learning-based software solutions, based on various parameters, such as trial registration year, trial recruitment status, trial design, target therapeutic area, leading industry and non-industry players, and geographical locations of trials.
Chapter 11 includes an in-depth analysis of over 3,000 patents related to deep learning and medical images that have been filed / granted till June 2020, highlighting key trends associated with these patents, across type of patent, publication year and application year, regional applicability, CPC symbols, emerging focus areas, leading patent assignees (in terms of number of patents filed / granted), patent benchmarking and valuation.
Chapter 12 presents an insightful analysis highlighting cost saving potential associated with the use of deep learning solutions intended for processing of medical images, based on information gathered from close to 30 countries, taking into consideration various parameters, such as total number of radiologists, annual salary of radiologists, number of scans performed (across each type of image) and increase in efficiency by adoption of deep learning solutions.
Chapter 13 features an informed estimate of the existing market size and the future growth potential within the deep learning market (medical image processing segment), such as global radiology spending across countries, number of radiologists employed across different regions of globe, annual salary of radiologists, rate of adoption of deep learning-based solutions, we have developed informed estimates on the financial evolution of the market, over the period 2020-2030. The report also provides details on the likely distribution of the current and forecasted opportunity across [A] application area (lung infections / respiratory disorders, brain injuries / disorders, lung cancer, cardiac conditions / cardiovascular disorders, bone deformities / orthopedic disorders, breast cancer and others), [B] type of image processed (X-ray, MRI, CT, ultrasound) and [C] region (North America, Europe and Asia Pacific / Rest of the World). In order to account for future uncertainties and to add robustness to our forecast model, we have provided three scenarios, namely conservative, base and optimistic scenarios, representing different tracks of the industry’s growth.
Chapter 14 presents an insightful discussion on the views presented by various industry and non-industry experts present across the globe, on various portals, such as YouTube and other media platforms. The summary of insights provided by each expert is discussed across focus area, current industry status / challenges and future outlook.
Chapter 15 is a collection of interview transcripts of discussions held with various key stakeholders in this market. The chapter provides a brief overview of the companies and details of interviews held with Walter de Back (Research Scientist, ContextVision), Anonymous (CEO, India-based Company), Babak Rasolzadeh (Senior Director of Product, Arterys), Carla Leibowitz (Head of Strategy and Marketing, Arterys), Mausumi Acharya (CEO, Advenio Technosys), Deekshith Marla (CTO, Arya.ai) and Sanjay Bhadra (COO, Arya.ai).
Chapter 16 highlights the impact of COVID-19 on the overall deep learning in medical image processing market. It includes a brief discussion on the short-term and long-term impact of COVID-19 upsurge on the market opportunity for software developers. In addition, it includes a brief section on strategies and action plans that companies involved in this space have adopted in order to fight against the infection.
Chapter 17 is a summary of the overall report. It includes key takeaways related to research and analysis from the report in an infographic format.
Chapter 18 is an appendix, which provides tabulated data and numbers for all the figures provided in the report.
Chapter 19 is an appendix, which contains the list of companies and organizations mentioned in the report.
Read the full report: https://www.reportlinker.com/p05987918/?utm_source=GNW
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Artificial Intelligence
Cayman Enterprise City Publishes Socio-Economic Impact Assessment by Economist and Leading Advisor on the Caribbean, Marla Dukharan
The Impact of Cayman Enterprise City’s Socio-Economic Development Project Nears USD $1 Billion
GRAND CAYMAN, Cayman Islands, May 16, 2024 /PRNewswire/ — Cayman Enterprise City (CEC) has released a Socio-Economic Impact Assessment by Marla Dukharan. The report illustrates that CEC is increasing its impact by supporting higher earnings for Caymanians and is driving a shift towards a knowledge-based economy by focusing on high productivity sectors. The release by Dukharan reads, “Caymanian resourcefulness and private sector-led innovation have been the driving force behind the islands’ outstanding socio-economic success. Cayman Enterprise City underpins the next generation of Cayman innovation and dynamism.”
With an economic impact of USD $130 million in 2023, contributing just under USD $1 billion to the local economic activity in 12 years since inception, “CEC is helping the nation to diversify economically, in terms of sectors and jobs, ensuring locals have economic and employment opportunities that match the nation’s progress,” the report reads.
The CEC socio-economic development project is now home to 352 Special Economic Zones Companies (SEZCos), many of which are globally recognised institutions led by top executives and industry experts. “CEC member companies are providing high-value employment with salaries exceeding those typically found outside of the special economic zone,” said Charlie Kirkconnell, Chief Executive Officer at CEC. “The CEC community is fully invested in Cayman and the report illustrates that the CEC socio-economic development project is making a very significant impact on Cayman’s economy and community.”
“As CEC continues to grow, it continues to create significant employment and entrepreneurial opportunities for Caymanians and we encourage anyone that might be interested in finding out how they might get involved, whether as a member of the community and/or as a volunteer in our Enterprise Cayman non-profit organisation (NPO).”
77% of Caymanian-held jobs at CEC member companies, are in sectors with high social returns and increasing global demand. “By putting skills first and prioritizing learning, CEC is enabling new industries to take root,” the release by Dukharan reads.
CEC, through its Enterprise Cayman NPO, is a first-mover in private sector-facilitated education and training in the Caribbean, making it a leading force to boost youth participation in the economy. By offering training in specialised skills, Enterprise Cayman is helping to close the gap in higher education and earnings for Caymanians. “Through Enterprise Cayman we’ve set out to strategically support meaningful employment and entrepreneurial opportunities for Caymanians, by providing internship and mentorship opportunities, by hosting skill-building and career focused training, and by providing invaluable networking and community engagement opportunities,” said Kirkconnell.
In 2023 individuals took advantage of 4,226 opportunities to participate in education, training, and career development events and, since launching entrepreneurial programming in 2021, Enterprise Cayman has worked with 41 new Cayman-born business ventures. “We’re helping to develop a local talent pool that meets the demand of Cayman’s growing digital innovation and technology sectors while, in parallel, offering exciting opportunities for individuals to launch new business ventures within an innovative business environment,” said Kirkconnell.
With CEC’s new campus and state-of-the-art facilities, Signal House, the project “holds the promise of deep, continued economic impact,” the report concludes.
To access CEC’s economic impact assessments and Enterprise Cayman’s annual reports please visit https://www.enterprisecayman.ky/reports. For more information on how to get involved and for upcoming programmes and events visit www.enterprisecayman.ky.
Website: www.caymanenterprisecity.com LinkedIn: @CaymanEnterpriseCityTwitter: @CEC_CaymanInstagram: @CaymanEnterpriseCityFacebook: @CaymanEnterpriseCityYouTube: @ceccayman
About Cayman Enterprise City
Cayman Enterprise City (CEC) is an award-winning development project which consists of three special economic zones (SEZs) focused on attracting knowledge-based and specialised-services businesses to set up a genuine physical presence in the Cayman Islands. The zones included within CEC are Cayman Tech City, Cayman Commodities & Derivatives Centre, and Cayman Maritime & Aviation City. With a dedicated Government Authority, licensing fee concessions and guaranteed fast-track processes, CEC enables international companies to quickly and efficiently establish a Cayman Islands office, which in turn enables them to generate active business income within a tax neutral environment.
About Enterprise Cayman
Enterprise Cayman is a non-profit organisation (NPO) powered by Cayman Enterprise City in partnership with Cayman Islands’ special economic zone companies (SEZCos). The organisation, which applies the Theory of Change (TOC) methodology, provides Caymanians and residents with access to high-quality learning experiences and opportunities to develop and launch new business ventures, to pursue careers within the technology and innovation sectors, and to join a dynamic network of industry professionals. Let’s grow the next generation of Caymanian innovators and entrepreneurs with Enterprise Cayman!
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FOR MORE INFORMATION:Contact: Kaitlyn Elphinstone Email: [email protected]
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Artificial Intelligence
Strava Unveils New Chapter of Accelerated Product Development at Brand’s Flagship Event
The Company introduces increased product velocity, leveraging advancements in Artificial Intelligence, in service of its vision of a world connected through movement
LOS ANGELES, May 16, 2024 /PRNewswire/ — Strava, the leading digital community for active people with more than 125 million athletes, today showcased its latest initiatives and product developments at its annual event, Camp Strava. With the theme of Progress, Together company leaders announced how the platform will empower its global community to make progress in the way they explore, move, and connect on Strava.
“Strava is gaining momentum to realize our vision of a world connected through movement,” said Michael Martin, chief executive officer of Strava. “We are focused on two fundamental shifts to accelerate how we deliver value to 125 million people globally– building for women and leveraging Artificial Intelligence – which will unlock new community-and-partner-powered experiences across the platform.”
A New Era of Product VelocityStrava, with new leaders at the helm, is ushering in its next era of product velocity. The company listened closely to feedback from its global community and announced three of the most requested features coming to the platform by the end of the year.
The first of these updates, AI-enabled Leaderboard Integrity, will harness machine learning to automatically flag irregular, improbable, or impossible activities recorded to the platform. Trained by millions of activities, this feature allows all users on Strava to play fair and have more fun.
Additionally, the company announced a new Family Plan Subscription, the sister of the company’s Student Plan. With Family Plan, it’s easier to make a fitness commitment with your community by sharing an annual subscription with up to three other people – friends, family, or fitness family. Launching in select countries this summer, with plans to roll out globally by the end of the year, Strava’s newest annual subscription option offers the best value for groups (up to four), with a discount off the regular subscription price for each member.
Strava also implemented an updated design system, an initiative that is integral in driving a heightened pace of product innovation at the company. Through this work, Strava announced the launch of one of the company’s most requested features, Dark mode. Dark mode will improve the in-app experience for all users, reducing eye strain and improving accessibility while they record activity or scroll through the feed. Athletes can expect a rollout later this summer with options to keep their mobile settings always dark, always light, or match their device settings.
Company leaders highlighted several other features and updates to current products like Flyover, with its next iteration offering an overlay with activity stats and off-platform sharing capabilities. The overlay is available today for Strava subscribers and an off-platform sharing option will be released later this year.
Build for Her, Build for ManyStudies show that women of all ages participate in sports at a far lower rate than men, and overall, despite wanting to be active, find less time to dedicate to an active lifestyle. As the company continues on its mission to motivate people to live their best active lives, building for women on the platform will ultimately serve everyone in the Strava community. Several new features and initiatives were announced as a part of this strategic focus, which includes:
Night Heatmaps: Night Heatmaps show only activities between sundown and sunrise – so athletes can get an idea of which roads, trails, and paths are well-trafficked after hours. Since Night Heatmaps filter for after-hours routes, it can be a helpful tool for female athletes training before sunrise and after sunset.Quick Edit: For active women, having control over what is shared with the Strava community that cheers them on – like what time a run is logged – is important. Quick Edit makes it easier to make the most common edits – like activity name, and privacy settings so you can hide your start time, your map, or other workout stats.Strive for More®: The company announced a new phase of its Strive for More® initiative, created in 2022 to promote and support women in movement and sport. Today, Strava unveiled an official partnership with media company TOGETHXR to encourage more women to watch – and play – women’s sports. As part of the partnership, Strava will also donate $100,000 to the Alex Morgan Foundation, started by co-founder of TOGETHXR, Alex Morgan, to support their mission to help girls and women find confident paths forward in sports and life.Athlete IntelligenceToday, Strava announced the start of an accelerated product roadmap, outlining how Strava will implement the latest technological enhancements in AI and machine learning, to transform the athlete experience.
One key advancement to the platform includes the company’s latest development, Athlete Intelligence. Strava is introducing its beta AI-powered feature which turns each subscriber’s training data into an easily digestible summary that contextualizes their accomplishments and fitness goals. Unlike other AI-powered training services, Strava connects with thousands of devices, wearables, and fitness apps, so an athlete’s insights can consider their entire fitness story across multiple sports and modalities.
The features shared at Camp Strava will be released on a rolling basis through the end of the year. To view the full list of product releases and further details, visit www.press.strava.com.
For more information on Strava, to create a free account, or to start a free subscription trial visit www.strava.com.
About Strava Strava is the leading digital community for active people with more than 125 million athletes, in more than 190 countries. The platform offers a holistic view of your active lifestyle, no matter where you live, which sport you love and/or what device you use. Everyone belongs on Strava when they are pursuing an active life. Join the community, find motivation and discover new experiences with a Strava subscription.
Visit www.strava.com for more information and connect with Strava on Instagram, Twitter, Facebook, YouTube and LinkedIn.
Media Contact: [email protected]
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Artificial Intelligence
Japan Data Center Market Investment to Reach $14.48 Billion by 2028 – Watch Out Exclusive Insight on Japan & Hong Kong Data Center Market – Arizton
CHICAGO, May 16, 2024 /PRNewswire/ — Arizton publishes the latest research report on the Japan data center market and Hong Kong data center market.
The Japan Data Center Market to Witness Investments of $14.48 Billion by 2029.
Get Insights on 107 Existing Data Centers and 41 Upcoming Facilities across Japan.
The data center market in Japan is experiencing the emergence of self-built hyperscale data center facilities by major operators such as Google, Microsoft, and Amazon Web Services (AWS). This development is expected to impact the colocation market in Japan. Since these hyperscale operators store workloads in their own data center facilities, it may reduce the source of revenue generation for colocation operators.
Japan is a well-established data center market in the APAC region. The country supports investments with its macroeconomic policies and other incentives for investors. The market is witnessing several investments from local and global data center operators, further expanding its presence. Tokyo and Osaka are Japan’s major destinations for data center development, accounting for over 90% of the existing data center facilities. The government announced the offer of subsidies in Hokkaido and Kyushu for data center development and decentralize data centers from Tokyo and Osaka.
Investment Opportunities
In October 2023, SoftBank and its subsidiary, IDC Frontier, announced the plan to develop a new data center facility in Tomakomai City, Hokkaido. The company invested around $420 million toward the project, for which it received subsidies worth $190 million from the Ministry of Economy, Trade, and Industry. In July 2023, Internet Initiative Japan (IIJ) launched its second data center building at the Shiroi data center campus in Chiba Prefecture, Greater Tokyo. Once fully built, the campus will house four data center buildings. Furthermore, the company is involved in a third expansion initiative in its Matsue City campus (which will likely go live in 2025).In June 2023, Digital Edge, in partnership with Hulic, a real estate developer, announced the start of the construction of a new data center facility, TY07, in Tokyo. The facility is expected to go online by 2025.In April 2024, GDS Services partnered with Gaw Capital to develop a new data center campus in Fuchu City, Tokyo. Both companies will jointly invest toward developing a new data center facility, with the first phase slated to go online by 2026.To Buy this Research Now, Click: https://www.arizton.com/market-reports/japan-data-center-market-investment-analysis
Existing Vs. Upcoming Data Centers
Existing Facilities in the Region (Area and Power Capacity)TokyoOsakaOther CitiesList of Upcoming Facilities in the Region (Area and Power Capacity)TokyoOsakaOther CitiesVendor Analysis
IT Infrastructure Providers: Arista Networks, Atos, Broadcom, Cisco Systems, Dell Technologies, Fujitsu, Hewlett Packard Enterprise (HPE), Hitachi Vantara, Huawei Technologies, IBM, Inspur, Lenovo, NEC, NetApp, and Oracle.
Data Center Construction Contractors & Sub-Contractors: Arup, AECOM, Daiwa House Industry, Fuji Furukawa Engineering & Construction, Hibiya Engineering, ISG, Kajima Corporation, Keihanshin Building, Linesight, MARCAI DESIGN, Meiho Facility Works, Nikken Sekkei, NTT FACILITIES, Obayashi Corporation, SHINRYO Corporation, TAISEI Corporation.
Support Infrastructure Providers: 3M, ABB, Alfa Laval, Caterpillar, Cummins, Delta Electronics, Eaton, Fuji Electric, HITEC Power Protection, Johnson Controls, Kawasaki Heavy Industries, KOHLSER-SDMO, Legrand, Mitsubishi Electric, Rittal, Rolls-Royce, Schneider Electric, STULZ, Siemens, Vertiv.
Data Center Investors: AirTrunk, Alibaba Cloud, Amazon Web Services, AT TOKYO, Colt Data Centre Services, Digital Edge, Equinix, Fujitsu, Goodman, Google, IDC Frontier, Internet Initiative Japan (IIJ), MC Digital Realty, Microsoft, NTT Communications, SCSK Corporation (NETXDC), Telehouse, Tencent Cloud, TIS INTEC Group.
New Entrants: Ada Infrastructure, Edge Centres, CyrusOne, ESR, GDS Services, Keppel Data Centres, NEXTDC, Princeton Digital Group (PDG), SC Zeus Data Center, STACK Infrastructure, ST Telemedia Global Data Centres, Vantage Data Centers, Yondr.
The Hong Kong Data Center Market will Witness Investments of $4.80 Billion by 2029.
Get Insights on 54 Existing Data Centers and 12 Upcoming Facilities across Hong Kong.
The Hong Kong data center market is booming, driven by the increasing demand for digital services. The data center investments in Hong Kong over the next two to three years are expected to remain high due to the surge in demand and the significant boost due to the advancements in AI technologies. Investors are actively investing in this market.
Hong Kong is a mature and thriving market for data center development in the APAC region. Investors find it an attractive market owing to the high internet and social media usage levels, a robust business ecosystem, and excellent connectivity through both inland and submarine cables. Additionally, the deployment of 5G technology further enhances its appeal.
Hong Kong stands out globally for the incredibly high rates of cell phone and home broadband service usage. With around 300 licensed internet service providers, there is robust competition, providing data center operators with a wide range of choices.
Hong Kong is considered an attractive destination for businesses due to various reasons. Its proximity to mainland China and its import-export relations with major markets, such as China and the US, make it easier for businesses to operate. Additionally, the market has experienced significant growth in Foreign Direct Investment (FDI), ranking after countries like the UK, the US, and China.
Investment Opportunities
In December 2023, the company completed the core and shell construction of phase-1 of the MEGA IDC data center campus. The facility has already signed lease agreements with cloud service providers and international banks for its available space. The company plans to expand the campus through phase-2 during the forecast period.In March 2023, the company launched its seventh data center facility, MEGA Gateway, in Tsuen Wan. The facility is part of its connected MEGA campus.Goodman is among the major investors in the Hong Kong market, and it is continuously expanding its data center presence. In March 2024, the company announced the construction of the new Texaco data center facility in Tsuen Wan. The facility is a brownfield construction that involved the conversion of an industrial building into a data center facility. The facility is likely to go online by 2026.Over 60% Of Future Demand to Come from Cloud Service Providers
The Hong Kong data center market has the presence of on-premises data centers operated by educational institutions, the government, and financial services such as HSBC Bank. A significant decline in on-premises data centers will occur in the next three to five years owing to the increase in digitalizing initiatives across sectors and the strong growth in demand for colocation and cloud services. In addition, most existing service providers offer managed solutions to enterprise customers, which will likely grow in the market from 2024-2029.
The market has the presence of all global cloud operators, such as Amazon Web Services (AWS), Google, Microsoft, Alibaba Cloud, Huawei Cloud, and Tencent Cloud. This will propel the demand for wholesale colocation services through these service providers’ continuous expansion initiatives. The cloud segments will likely dominate capacity take-up over the next five years. In addition, the market will witness the entry of multiple global organizations to service customers through a local presence.
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Existing VS. Upcoming Data Centers
Existing Facilities in the Region (Area and Power Capacity)Tseung Kwan OKwai ChungTsuen WanFanlingFo TanChai WanTai PoOther LocationList of Upcoming Facilities in the Region (Area and Power Capacity)Tseung Kwan OKwai ChungTsuen WanFanlingFo TanChai WanTai PoOther LocationVendor Analysis
IT Infrastructure Providers: Arista Network, Atos, Cisco Systems, Dell Technologies, Fujitsu, Hewlett Packard Enterprise (HPE), Huawei Technologies, IBM, Inspur, Lenovo, NetApp.
Data Center Construction Contractors & Sub-Contractors: Arup, AtkinsRéalis, Aurecon, BYME Engineering, Chung Hing Engineers Group, Cundall, DSCO Group, Gammon Construction, ISG, Studio One Design.
Support Infrastructure Providers: ABB, Airedale, Caterpillar, Cummins, Delta Electronics, Eaton, Fuji Electric, KOHLER, Legrand, Mitsubishi Electric, Piller Power Systems, Rittal, Schneider Electric, Siemens, STULZ, Sumber, Vertiv.
Data Center Investors: AirTrunk, BDx, CITIC Telcom International, China Mobile International (CMI), China Unicom, Digital Realty, Equinix, ESR, GDS Services, Global Switch, Goodman, iTech Towers Data Centre Services, NTT DATA, SUNeVision Holdings (iAdvantage), Telehouse, Towngas Telecom (TGT), Vantage Data Centers.
New Entrants: Angelo Gordon and Mapletree Investments
Japan & Hong Kong Data Center Market Segmentation
IT Infrastructure
Servers
Storage Systems
Network Infrastructure
Electrical Infrastructure
UPS Systems
Generators
Transfer Switches & Switchgears
PDUs
Other Electrical Infrastructure
Mechanical Infrastructure
Cooling Systems
Rack Cabinets
Other Mechanical Infrastructure
Cooling Systems
CRAC & CRAH Units
Chiller Units
Cooling Towers, Condensers & Dry Coolers
Economizers & Evaporative Coolers
Other Cooling Units
General Construction
Core & Shell Development
Installation & Commissioning Services
Engineering & Building Design
Fire Detection & Suppression Systems
Physical Security
DCIM
Tier Standard
Tier I & Tier II
Tier III
Tier IV
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