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AI (Artificial Intelligence) Image Recognition Market – Growth, Trends, and Forecast (2019 – 2024)
| Information & Communications Technology | Published by: Mordor Intelligence | Market: |
| 100 pages | Published: 11-06-2019 |
- Information & Communications Technology
- Mordor Intelligence
- 100 pages
- Published: 11-06-2019
Market Overview
The AI image recognition market was valued at USD 1.41 billion in 2018 and is projected to reach a market value of USD 5.32 billion by 2024 at a CAGR of 24.7% over the forecast period (2019 – 2024). Image recognition technologies comprise voice, iris, palm, hand vein pattern, fingerprints, retina, hand geometry, facial pattern recognition, object identification etc. Image recognition based on these indications can be applied across various fields, such as vehicular safety, advertising, security and surveillance, biometric scanning machines, pedestrian recognition, and E-commerce.
The adoption of artificial intelligence (AI) technology is rising, owing to its ability to enhance and automate operations and enrich the user experience. Governments are also focusing on increasing their AI capabilities to revolutionize various sectors, from healthcare to transport. EU has committed to invest EUR 1.5 billion in AI to catch up with the United States and Asia.
From the technical side, skills are needed to implement and develop road map infrastructure, manage security, and capture and analyze data.
According to Eirik Thorsnes at UNI Research in Bergen, Norway, “There has been a tremendous development in recent years, and we are now surpassing the human level in terms of image recognition and analysis. Computers never get tired of looking at near-identical images and may be capable of noticing even the tiniest nuances that we humans cannot see. In addition, as it gets easier to analyze large volumes of images and video, many processes in society can be improved and optimized.
Scope of the Report
Image recognition, in the context of machine vision, is the ability of software to identify objects, places, people, writing and actions in images. Computers can use machine vision technologies in combination with a camera and artificial intelligence software to achieve image recognition. Image recognition is used to perform a large number of machine-based visual tasks, such as labeling the content of images with meta tags, performing image content search, guiding autonomous robots and self-driving cars, and in accident avoidance systems.
Key Market Trends
Banking Sector Expected to Witness Prominent Growth
Images are real and omnipresent, and unlike other forms of data, they cannot be forged easily. These traits make images repositories of big data, and hence, exploiting such data can be a great source of information for financial institutions.
The banking industry has been a major benefactor of AI, with firms in the BFSI industry relying on the technology for a diverse range of applications, like personalizing communication with customers, staying competitive in a continuously evolving market, and improving the productivity drastically through the automation of redundant tasks (which is a major task due to the conventional infrastructure in a number of old school financial institutions).
Banks have tons of unstructured data on interactions with customers, customer photographs, and old documents, to name a few. The data, if deciphered well, can provide valuable inputs for the future of the financial institutions.
Facebook can now identify and map 98% of its images correctly to the right person. Imaging technology is being used for identifying and removing fake social accounts. Such image-based fake identification has immense potential in enriching credit-scoring and risk-modeling of banks. Images could also be used by underwriters in risk assessment and fraud identification.
Asia-Pacific Expected to Witness Rapid Growth
Image recognition solutions have been gaining prominence incessantly in Asia-Pacific, particularly to cater to the growing need for security solutions due to the advent of the smart homes and smart city initiatives in the developing economies in the region.
Due to the growth of the e-commerce segment of the retail industry in the recent past, vendors in the Asia-Pacific market are investing majorly in image recognition technologies to offer an enhanced digital experience to consumers.
Government initiatives and investments have been supportive of the market growth, which has further been complemented by the presence of major players, such as IBM, Microsoft, and Google, among others, in Asia-Pacific. Singapore’s National Research Foundation has invested about USD 107.64 million in the AI. SG initiative, to uplift the artificial intelligence technology.
Artificial intelligence offers the region massive opportunities for growth, innovation, and productivity, with the potential to address key issues in the social environment within the fast developing economies.
Competitive Landscape
The market is fragmented. The key players operating in this market are innovating their products on a regular basis and this is leading them to gain sustainable competitive advantage.
Due to this, there is always a high competition between players to innovate and introduce new products. The intense competition will drive down prices and can decrease the overall profitability of the industry.
Two of the key players in the industry are AWS and Alphabet. Some of the key developments in this market include:
A new capability being introduced to visual recognition by IBM, namely, color tagging. The new capability allows users to quickly assess the dominant color schemes within an image and turn these into actionable insights.
Google launched a camera based on artificial intelligence, which helps in deep integration between hardware and software. This can play a vital role in military or defense mechanism to record.
Reasons to Purchase this report:
– The market estimate (ME) sheet in Excel format
– Report customization as per the client’s requirements
– 3 months of analyst support
1 INTRODUCTION
1.1 Study Deliverables
1.2 Study Assumptions
1.3 Scope of the Study
2 RESEARCH METHODOLOGY
3 EXECUTIVE SUMMARY
4 MARKET DYNAMICS
4.1 Market Overview
4.2 Introduction to Market Drivers and Restraints
4.3 Market Drivers
4.3.1 Growing AI Adoption
4.3.2 Increasing Use of Big Data Analytics
4.3.3 Declining Costs of Hardware
4.4 Market Restraints
4.4.1 Lack of Technical Expertize
4.5 Value Chain Analysis
4.6 Industry Attractiveness Porter’s Five Forces Analysis
4.6.1 Threat of New Entrants
4.6.2 Bargaining Power of Buyers/Consumers
4.6.3 Bargaining Power of Suppliers
4.6.4 Threat of Substitute Products
4.6.5 Intensity of Competitive Rivalry
5 MARKET SEGMENTATION
5.1 By Type
5.1.1 Hardware
5.1.2 Software
5.1.3 Services
5.2 By End User
5.2.1 Automotive
5.2.2 BFSI
5.2.3 Healthcare
5.2.4 Retail
5.2.5 Security
5.2.6 Other End Users
5.3 Geography
5.3.1 North America
5.3.2 Europe
5.3.3 Asia-Pacific
5.3.4 Latin America
5.3.5 Middle East & Africa
6 COMPETITIVE LANDSCAPE
6.1 Company Profiles
6.1.1 IBM Corporation
6.1.2 Alphabet Inc.
6.1.3 Amazon Inc.
6.1.4 Intel Corp.
6.1.5 MICRON TECHNOLOGY INC.
6.1.6 Clarifai Inc.
6.1.7 Microsoft Corporation
6.1.8 Nvidia Corporation
6.1.9 Qualcomm Corp.
6.1.10 Samsung Electronics
6.1.11 Xilinx Inc.
7 MARKET INVESTMENT ANALYSIS
8 MARKET OPPORTUNITIES AND FUTURE TRENDS
MARKET SEGMENTATION
By Type
Hardware
Software
Services
By End User
Automotive
BFSI
Healthcare
Retail
Security
Other End Users
Geography
North America
Europe
Asia-Pacific
Latin America
Middle East & Africa
Artificial Intelligence (AI) in Food & Beverages Market – Growth, Trends, and Forecast (2019 – 2024)
| Information & Communications Technology | Published by: Mordor Intelligence | Market: |
| 100 pages | Published: 11-06-2019 |
- Information & Communications Technology
- Mordor Intelligence
- 100 pages
- Published: 11-06-2019
Market Overview
The Artificial Intelligence in Food and Beverages Market is expected to register a CAGR of over 65.3% during the forecast period 2019 – 2024. Changes in consumer demands towards preferring fast, affordable, and easily accessible food options has led to a transformation in the food and beverages industry, with market leaders leveraging advanced technologies, such as artificial intelligence and machine learning to scale operations and help companies stay relevant in a dynamic market environment.
The AI has been actively gaining prominence over the last five years, with many of the companies actively investing in exploring the potential of technology in the industry. This emerging technology of AI is helping F&B companies with supply chain management through the logistics, predictive analytics and also the transparency.
Organisations are increasingly digitizing their supply chain to differentiate and also to drive revenue growth which is improving the efficiency across the supply chain. Supply chains are generating a massive amount of data, where AI is helping the organization to analyze this data and gain a better understanding of variables in the supply chain by anticipating future scenarios.
AI in supply chains is helping businesses to innovate rapidly by reducing the time to market and establishing an agile supply chain which is capable of foreseeing and also dealing with the uncertainties. This is driving the growth of AI in the food and beverages sector.
AI provides many benefit to the F&B industry, but the high cost of large-scale deployment in the sector is restricting the market to grow. There are thin margins in the industry already, and many food and beverage companies have limited resources and cannot make significant investments, like Google or Amazon.
F&B brands usually build tightly integrated and customized in-house technology that would reflect the unique needs of the company. In today’s world, the battle for AI so competitively that leading technology companies are spending over USD 650 million annually for desirable candidates.
Companies who have the fortune of established data analytics capabilities and also the team of competent developers can safely build their own AI platform. F&B players are without such resources are seeking out solutions and providers by clearly defined goals needs, goals and also budgets.
Scope of the Report
Changes in consumer demands towards preferring fast, affordable, and easily accessible food options has led to a transformation in the food and beverages industry, with market leaders leveraging advanced technologies, such as artificial intelligence and machine learning to scale operations and help companies stay relevant in a dynamic market environment.
Key Market Trends
Consumer Engagement is expected to register a Significant Growth
Investment made by the former chairman of Tata Sons, in Techbin Solutions Pvt Ltd’s Niki.ai (which is an AI fueled chatbot that conducts conversations with consumers to assist them to order a wide range of services with the help of a chat interface), is depicting the investments and growth of the usage of chabots.
AI is being applied to understand the consumer behavior, which is expected to lead to more accurate predictions. It can further enable marketers and organizations to reach out to the customers at a personal level, engage in deeper interactions, and enhance their overall experience with the brand.
Furthermore, many consumers are adopting chabots, as they can effectively work on the offline mode. An American express report stated that more than 50% of the customers are willing to spend more in the companies that provide superior customer service. This opens up a tremendous opportunity for AI, which, in turn, is likely to fuel the growth of AI in the food and beverage sector.
AI can also help to analyze, monitor, and deduce the customer behavior and sentiments across the various social media channels. Therefore, when AI builds an in-depth customer profile, it matches it to their social experiences about the product. With the help of such powerful insights, firms can now aim to improve the customer experience and make it more productive, thereby leading to the growth of the market.
North America is Expected to Hold Major Share in the United States
The market for AI in food and beverage sector is growing in North America, with the United States leading the way. North America held a market share of 29.1% in 2017, which is second-largest region for AI in the food and beverage market.
In North America, the readiness for adoption and high fractional increase in replacement AI are the leading drivers of their economic impact, which reflects the regions leading stance on AI and its implementation, and also the high automation potential that is expected to occur at the regional level, between now and 2030.Besides, food processing is one of the major manufacturing sectors in the United States. According to the United States Department of Agriculture, 16% of value of shipments from all the US manufacturing plants comes from the food processing plants.
For most part, this sector is a very high-volume and low-margin industry. Finding new ways to gain modest increase in efficiency can make the difference between a facility turning a profit or a loss. Due to such functional constraints, many of largest food processing companies are shifting to AI technology, in order to improve the various aspects of the process. This is supporting to growth of the AI in food and beverage sector in the region.
Competitive Landscape
The Artificial Intelligence in Food and Beverages Market is highly competitive and consists of several major players. In terms of market share, few of the major players currently dominate the market. These major players with a prominent share in the market are focusing on expanding their customer base across foreign countries. These companies are leveraging on strategic collaborative initiatives to increase their market share and increase their profitability. The companies operating in the market are also acquiring start-ups working on Artificial Intelligence in Food and Beverages Market to strengthen their product capabilities. In August 2018, Key Technology introduced VERYX digital sorters for fresh-cut leafy greens. VERYX is the world’s only belt-fed sorter that can inspect product entirely in-air with top and bottom sensors, in order to detect and eliminate all foreign materials (FM) and product defects. By combining Key’s expertise in sorting and conveying, these integrated VERYX systems are specifically designed to handle the challenges of sorting leafy greens.
Reasons to Purchase this report:
– The market estimate (ME) sheet in Excel format
– Report customization as per the client’s requirements
– 3 months of analyst support
1 INTRODUCTION
1.1 Study Deliverables
1.2 Study Assumptions
1.3 Scope of the Study
2 RESEARCH METHODOLOGY
3 EXECUTIVE SUMMARY
4 MARKET DYNAMICS
4.1 Market Overview
4.2 Introduction to Market Drivers and Restraints
4.3 Market Drivers
4.3.1 Drastic Improvements in Efficiency Across the Supply Chain
4.3.2 Reduced Chance of Human Error and Associated Inaccuracies
4.3.3 Attractive, with the Ability to Generate Consumer Interest
4.4 Market Restraints
4.4.1 High Cost Associated with Large-scale Deployment of the Technology
4.5 Value Chain / Supply Chain Analysis
4.6 Industry Attractiveness Porters Five Force Analysis
4.6.1 Threat of New Entrants
4.6.2 Bargaining Power of Buyers/Consumers
4.6.3 Bargaining Power of Suppliers
4.6.4 Threat of Substitute Products
4.6.5 Intensity of Competitive Rivalry
5 MARKET SEGMENTATION
5.1 By Application
5.1.1 Food Sorting
5.1.2 Quality Control and Safety Compliance
5.1.3 Consumer Engagement
5.1.4 Production and Packaging
5.1.5 Maintenance
5.1.6 Other Applications
5.2 By End Users
5.2.1 Food Processing Industry
5.2.2 Hotel and Restaurant
5.2.3 Beverage Industry
5.3 Geography
5.3.1 North America
5.3.2 Europe
5.3.3 Asia Pacific
5.3.4 Rest of the World
6 COMPETITIVE LANDSCAPE
6.1 Company Profiles
6.1.1 Raytec Vision SpA
6.1.2 Rockwell Automation Inc.
6.1.3 ABB Ltd
6.1.4 Honeywell International Inc.
6.1.5 Key Technology Inc.
6.1.6 TOMRA Sorting Solutions AS
6.1.7 GREEFA
6.1.8 Sesotec GmbH
6.1.9 Martec of Whitell Ltd
6.1.10 NotCo
7 INVESTMENT ANALYSIS
8 MARKET OPPORTUNITIES AND FUTURE TRENDS
MARKET SEGMENTATION
By Application
Food Sorting
Quality Control and Safety Compliance
Consumer Engagement
Production and Packaging
Maintenance
Other Applications
By End Users
Food Processing Industry
Hotel and Restaurant
Beverage Industry
Geography
North America
Europe
Asia Pacific
Rest of the World
Artificial Intelligence in Life Sciences Market – Growth, Trends, and Forecast (2019 – 2024)
| Information & Communications Technology | Published by: Mordor Intelligence | Market: |
| 100 pages | Published: 12-06-2019 |
- Information & Communications Technology
- Mordor Intelligence
- 100 pages
- Published: 12-06-2019
Market Overview
Artificial Intelligence in Life Sciences Market was valued at USD 902.1 million is expected to grow at a CAGR of over 21.1% during the forecast period (2019-2024). Although artificial intelligence has been in the market in the late 1950s, the technology has become commercially accessible in the past few years. The primary reason for this accelerated growth in recent years is the massive availability of data in the life sciences sector.
As AI operates on large sets of data, the availability of such data becomes a key factor for establishing a suitable environment for the growth of AI-based solutions. With innovations in mobile technology and sensors, even the present day’s wearables like smartwatches and fitness trackers, have enough computing power to generate and process vast amounts of data.
In fact, according to the recent estimates of Consumer Technology Association, a prominent standard and trade organization for the consumer electronics industry based in the United States, health and fitness trackers accounted for more than 47% of the wearables devices sold in 2017. This scenario coupled with several medical devices used in healthcare sector generates huge sets of data that could make use of AI to derive useful results.
AI is increasingly becoming popular in drug discovery, personalized medicine, biotechnology, and clinical trials. With increasing healthcare spending in almost all parts of the world, the pharmaceutical industry has been involved in extreme R&D activities in the past few years.
Scope of the Report
Artificial Intelligence (AI) is a highly data-driven technology. In the life sciences sector, it is generally employed to make meaningful relations from loosely coupled data. With the advent of the third wave of AI, it is estimated that advanced AI solutions in the current market scenario can learn and evolve as they are being used.
Key Market Trends
Clinical Trails to Hold Significant Share
Clinical trials are one of the most data-intensive tasks in the life sciences industry. They generate vast sets of data every day monitoring several variables of a patient under observation. Subjecting these data sets to intelligent AI algorithms can help the researchers to screen meaningful correlation even between loosely coupled data.
This is encouraging many pharmaceutical companies and clinical research organizations to invest in technologies, like artificial intelligence. In the current market scenario, rapid adoption of AI is widely seen in the pharmaceutical sector, who are responsible for almost 50% of the clinical trials conducted globally every year.
Novartis claims that the deployment of QuantamBlack’s solutions has reduced patient enrolment times by 10-15%. Additionally, as of March 2018, the company has entered a partnership with IBM to make use of IBMs AI platform, IBM-Watson, to improve clinical trial recruitment, and make use of intelligent AI algorithms to predict medication efficacy.
Such initiatives are encouraging many companies to invest in AI solutions tailor-made for clinical trials. Many prominent companies, such as GlaxoSmithKline, Sanofi, Pfizer Mitsubishi Tanabe Pharma, and Genentech among others, are investing in AI-based clinical trails startups and solutions to make clinical trials more affordable.
India to Exhibit Highest Growth
India, the third-largest pharmaceutical market in Asia, is increasingly gaining much-needed government focus on expanding affordable health care. As part of the Union Budget FY19, the government announced the world’s largest National Health Protection Scheme, for which the government set aside an investment worth USD 307.6 million, to provide coverage of up to USD 7,690 per year, to 500 million people belonging to financially vulnerable households, for the treatment of serious ailments. Simultaneously, AI and machine learning have already started penetrating various industries across India, with healthcare being one of the biggest beneficiaries of the AI revolution. According to a report by CIS India published in 2018, AI could help add USD 957 billion to the Indian economy by 2035. In the July-September 2017 quarter, around 16 Indian healthcare IT companies received funding. The adoption of AI in life sciences in India is being driven by the likes of Microsoft, and a slew of health-tech startups.
Competitive Landscape
The artificial intelligence in the life sciences market has been gaining a competitive edge in recent years. In terms of market share, few of the major players currently dominate the market. These major players with a prominent share in the market are focusing on expanding their customer base across foreign countries. These companies are leveraging on strategic collaborative initiatives to increase their market share and increase their profitability. In Oct 2018, Lifegraph launched their new app on the Google Play Store. It uses AI in the core to forecast the state of patient health. The app named Lifegraph – AI technology for migraine management, was launched to help track changes in the behavior and weather throughout the day and, using machine learning, predicts an imminent attack for actionable self-care.
Reasons to Purchase this report:
– The market estimate (ME) sheet in Excel format
– Report customization as per the client’s requirements
– 3 months of analyst support
1 INTRODUCTION
1.1 Study Deliverables
1.2 Study Assumptions
1.3 Scope of the Study
2 RESEARCH METHODOLOGY
3 EXECUTIVE SUMMARY
4 MARKET DYNAMICS
4.1 Market Overview
4.2 Introduction to Market Drivers and Restraints
4.3 Market Drivers
4.3.1 Rising Adoption Of Ai In The Field Of R&D
4.3.2 High Emphasis On The Development Of Precision Medicine And Personalized Drugs
4.3.3 Increasing Demand For AI In Drug Discovery
4.4 Market Restraints
4.4.1 High Initial Costs And Concerns Over The Replacement Of Human Workforce
4.5 Technology Snapshot
4.6 Industry Attractiveness Porters Five Force Analysis
4.6.1 Threat of New Entrants
4.6.2 Bargaining Power of Buyers/Consumers
4.6.3 Bargaining Power of Suppliers
4.6.4 Threat of Substitute Products
4.6.5 Intensity of Competitive Rivalry
5 MARKET SEGMENTATION
5.1 By Application
5.1.1 Drug Discovery
5.1.2 Medical Diagnosis
5.1.3 Biotechnology
5.1.4 Clinical Trails
5.1.5 Precision and Personalized Medicine
5.1.6 Patient Monitoring
5.2 Geography
5.2.1 North America
5.2.1.1 US
5.2.1.2 Canada
5.2.2 Europe
5.2.2.1 Germany
5.2.2.2 UK
5.2.2.3 France
5.2.2.4 Rest of Europe
5.2.3 Asia Pacific
5.2.3.1 China
5.2.3.2 Japan
5.2.3.3 India
5.2.3.4 South Korea
5.2.3.5 Rest of Asia-Pacific
5.2.4 Rest of the World
6 COMPETITIVE LANDSCAPE
6.1 Company Profiles
6.1.1 IBM Corporation
6.1.2 NuMedii Inc.
6.1.3 Atomwise Inc
6.1.4 Lifegraph
6.1.5 Cyrcadia Health Inc.
6.1.6 Numerate Inc.
6.1.7 Sensely Inc.
6.1.8 Sophia Genetics SA
6.1.9 Insilico Medicine Inc.
6.1.10 Enlitic Inc.
6.1.11 APIXIO Inc.
6.1.12 Zebra Medical Vision
6.1.13 Lifegraph Limited
6.1.14 twoXAR Inc.
6.1.15 AiCure LLC
7 MARKET OPPORTUNITIES AND FUTURE TRENDS
7.1 Investment Scenario
MARKET SEGMENTATION
By Application
Drug Discovery
Medical Diagnosis
Biotechnology
Clinical Trails
Precision and Personalized Medicine
Patient Monitoring
Geography
North America
US
Canada
Europe
Germany
UK
France
Rest of Europe
Asia Pacific
China
Japan
India
South Korea
Rest of Asia-Pacific
Rest of the World
Big Data Analytics in Manufacturing Industry Market – Growth, Trends, and Forecast (2019 – 2024)
| Information & Communications Technology | Published by: Mordor Intelligence | Market: |
| 100 pages | Published: 12-06-2019 |
- Information & Communications Technology
- Mordor Intelligence
- 100 pages
- Published: 12-06-2019
Market Overview
The Big Data Analytics In Manufacturing Industry Market is expected to register a CAGR of over 30.9% during the forecast period 2019 – 2024. With the high rate of adoption of sensors and connected devices and the enabling of M2M communication, there has been a massive increase in the data points that are generated in the manufacturing industry. These data points could be of various types, ranging from a metric detailing the time taken for a material to pass through one process cycle or a more complex one, such as the calculation of the material stress capability in the automotive industry.
Manufacturing is a crucial component of a company’s end-to-end supply chain. The value chain participants, like Raw material suppliers, Inventory managers, and Manufacturers have moved from manual product, tracking to the use of barcode scanners and investing in technologies, like RFID and sensors to monitor the stock, production processes, and ascertain when maintenance is required and to take action before the production quality is affected. Such technology adoption was made to monitor aging manufacturing equipment, in order to avoid production downtime, which could be as high as EUR 180 billion (for Britain’s manufacturers, according to Oneserve, the field service management company).
In addition to monitoring the asserts, these technologies are being used to gain information about the location of raw materials and finished products within the production facility, to know the status of the availability status (both volume and location data). In addition, advancement in UHF technology has made creating RFID systems more efficient and evolved in such a way that they are able to identify raw material/product specifications like SKU, color, and type thus improving the traceability throughout the supply chain.
Manufacturing is one of the most targeted industries by cyber attackers owing to the presence of vital data related to company and government. According to EEF (formerly the Engineering Employers’ Federation), over 45% of the manufacturers have been subjected to a cybersecurity incident.
With the increasing integration of technological advancements in the manufacturing industry, the security concerns are also ascending at a significant pace.
Scope of the Report
The manufacturing industry has evolved since the last industrial revolution. Technology has played a critical role in shaping the modern manufacturing industry. With the introduction of Industry 4.0, the production establishments took a step forward and implemented many IoT and IIoT solutions to get live feedback from factories and working environments. With the implementation of Machine to Machine services and telematics solutions in production establishments, the industry has moved from the traditional value chain to technology, asset, and engineering-oriented value chain
Key Market Trends
Condition Monitoring is expected to register a Significant Growth
Condition monitoring or the act of monitoring the condition of an asset, especially through real-time data points, forms the foundation of what has become known as Industry 4.0, in its basic form. An integral part of condition monitoring, within the IIoT ecosystem, is providing data that can then be used for Predictive Maintenance (PdM) and many more smart factory applications, such as Digital Twin.
Big data analytics, especially with predictive analytics, is a growing trend and often prompts discussions around centralizing data across multiple sites, so that the consistency of data is achieved. However, a significant roadblock remains the inability of many customers to convert the flood of new data into actionable information. Big Data systems need to monitor machine failures repeatedly before they can analyze adequately and predict effectively for the future.
For instance, overhead conveyor systems are used in assembly production lines in the automotive and other manufacturing industries. The failure of single support frames can lead to the disruption of entire production lines. A condition monitoring system based on big data analytics detects the problem at an early stage and, thus, prevents unplanned downtime.
North America is Expected to Hold Major Share
North America is among the lead innovators and pioneers, in terms of adoption, for big data analytics in the manufacturing industry, and is expected to hold a significant share over the forecast period. Manufacturing sector adds a lot of value to the US economy. According to Trading Economics, GDP from manufacturing in the United States increased to USD 2125.80 billion in the second quarter of 2018, from USD 2113.80 billion in the first quarter of 2018.
The manufacturing sector is also forecast to increase faster than the general economy. According to the MAPI (Manufacturers Alliance for Productivity and Innovation) foundation, production will grow by 2.8% from 2018 to 2021. According to the Digital Change Survey done by IFS in 2017, to assess the maturity of digital transformation in a range of sectors, such as manufacturing, oil and gas, aviation, construction and contracting, 46% of the companies in all industries are looking to invest in the big data and analytics.
American multinational corporation, Intel is finding significant value in big data. The company uses big data to develop chips faster, identify manufacturing glitches, and warn about security threats.
Competitive Landscape
The Big Data Analytics In Manufacturing Industry Market is highly competitive and consists of several major players. In terms of market share, few of the major players currently dominate the market. These major players with a prominent share in the market are focusing on expanding their customer base across foreign countries. These companies are leveraging on strategic collaborative initiatives to increase their market share and increase their profitability. The companies operating in the market are also acquiring start-ups working on big data analytics in manufacturing technologies to strengthen their product capabilities. In January 2018, Datawatch has completed the acquisition of Angoss Software. This acquisition is expected to help the company to expand data science capabilities, which will enable the data scientists to perform predictive and prescriptive analytics in a wide variety of enterprise applications.
Reasons to Purchase this report:
– The market estimate (ME) sheet in Excel format
– Report customization as per the client’s requirements
– 3 months of analyst support
1 INTRODUCTION
1.1 Study Deliverables
1.2 Study Assumptions
1.3 Scope of the Study
2 RESEARCH METHODOLOGY
3 EXECUTIVE SUMMARY
4 MARKET DYNAMICS
4.1 Market Overview
4.2 Introduction to Market Drivers and Restraints
4.3 Market Drivers
4.3.1 Evolving Value Chains
4.3.2 Rapid Industrial Automation Led by Industry 4.0
4.4 Market Restraints
4.4.1 Lack of Awareness and Security Concerns
4.5 Value Chain / Supply Chain Analysis
4.6 Industry Attractiveness Porters Five Force Analysis
4.6.1 Threat of New Entrants
4.6.2 Bargaining Power of Buyers/Consumers
4.6.3 Bargaining Power of Suppliers
4.6.4 Threat of Substitute Products
4.6.5 Intensity of Competitive Rivalry
5 MARKET SEGMENTATION
5.1 By End User
5.1.1 Semiconductor
5.1.2 Aerospace
5.1.3 Automotive
5.1.4 Other End Users
5.2 By Application
5.2.1 Condition Monitoring
5.2.2 Quality Management
5.2.3 Inventory Management
5.2.4 Other Applications
5.3 Geography
5.3.1 North America
5.3.2 Europe
5.3.3 Asia Pacific
5.3.4 Latin America
5.3.5 Middle East and Africa
6 COMPETITIVE LANDSCAPE
6.1 Company Profiles
6.1.1 Fair Isaac Corporation
6.1.2 Angoss Software Corporation
6.1.3 Alteryx Inc.
6.1.4 IBM Corporation
6.1.5 Microsoft Corporation
6.1.6 Tibco Software Inc. (Alpine Data)
6.1.7 SAS Institute Inc.
6.1.8 SAP SE
6.1.9 Oracle Corporation
6.1.10 RapidMiner Inc.
6.1.11 MicroStrategy Incorporated
6.1.12 Knime AG
7 INVESTMENT ANALYSIS
8 MARKET OPPORTUNITIES AND FUTURE TRENDS
MARKET SEGMENTATION
By End User
Semiconductor
Aerospace
Automotive
Other End Users
By Application
Condition Monitoring
Quality Management
Inventory Management
Other Applications
Geography
North America
Europe
Asia Pacific
Latin America
Middle East and Africa
Blockchain Market in the Energy Sector – Growth, Trends and Forecast (2019 – 2024)
| Information & Communications Technology | Published by: Mordor Intelligence | Market: |
| 95 pages | Published: 13-06-2019 |
- Information & Communications Technology
- Mordor Intelligence
- 95 pages
- Published: 13-06-2019
Market Overview
The Blockchain Market in the Energy Sector market is expected to register a CAGR of over 67.23 % during the forecast period 2019 – 2024. The blockchain technology, which has greatly benefitted the financial sector, finds applications in the energy sector predominantly for wholesale energy trading. However, the increasing number of use cases and efforts from the regional blockchain associations are promoting the adoption of the technology for various other applications like smart contracts and digital identification.
The increasing investment activity across the emerging vendors, like LO3 and Electron, among other 100+ startups, in the market enable the vendors to actively invest in more research and innovation for developing blockchain solutions for the energy sector. Considering that the innovation would be user-driven, such investments would increase the trust among the energy market participants to adopt blockchain technology.
Utilities are expressing their interest in the technology by investing in blockchain startups. For instance, Utilities like Tokyo Electric Power Company, a Japanese utility company has invested in the Energy Web Foundation, to accelerate the commercial deployment of blockchain technology in the energy industry. In 2017, the Japanese utility has also made investments in Electron, a UK-based blockchain vendors specializing in the energy sector.
Centrica, a prominent British multinational utility giant, is set to invest in LO3, in partnership with Braemar Energy. Similar investments have also been made by RWE, a German power company in 2017. LO3 Energy has also received investments from Siemens, a prominent player in the energy sector. The vendors are also closely working with Siemens to develop a blockchain enabled transactive energy platform for environmentally-friendly electricity.
The blockchain technology is currently under testing phase across the United States and the United Kingdom, among others. The technical and costs constraints of the blockchain technology might challenge the technology adoption in the energy sector. The blockchain technology for the peer-to-peer transactions may neither be particularly cost-effective nor can be easily scaled to support massive transaction levels in the long run. The presence of very few use cases that can emphasize on the scalability of the technology and the cost associated is the reason for the blockchain technology not being viewed as a cost-effective solution in the long run.
For peer-to-peer trading, blockchains would need to handle transactions of just a few kilowatts, which may take a minimum time span of 15 minutes. The costs associated with the transaction may be worth just a few cents in traditional methods, considering the amount of trading. The Bitcoin trading fee, for instance, has increased significantly from the last quarter of 2017 to 2018. Currently, a USD 16 fee is being imposed for a USD 25 bitcoin transaction. Such high trading fee of bitcoin and other 1600 cryptocurrencies used across regions for trading makes the blockchain technology expensive, in terms of handling huge transaction levels in the long run of peer-to-peer trading.
Scope of the Report
The energy sector has certain limitations, including high administration and transmission costs mainly, due to the centralized functioning of the sector. As blockchain addresses these issues and decreases the scope for single point failures and increases transparency across the supply chain, the technology is expected to be a noteworthy digital transformation for the sector.
The blockchain technology, which has greatly benefitted the financial sector, finds applications in the energy sector predominantly for wholesale energy trading. However, the increasing number of use cases and efforts from the regional blockchain associations are promoting the adoption of the technology for various other applications like smart contracts and digital identification. Blockchain enables energy transmission companies to track the movement of excess energy thereby managing the supply-demand bottlenecks.
Key Market Trends
Smart Contract is expected to register a Significant Growth
The Smart Contract is the computer-aided program, which encodes the different conditions and possible outcomes and moves the currency or information across the ledger using blockchain technology. Blockchain with the use of smart contracts is anticipated to reduce the number of different administrative processes, which involves the deal of execution.
The smart contract enables consumers to execute and dispatch various commodities automatically, once the trade is booked. By reducing the involvement of multiple intermediaries, Blockchain will decrease the time and costs involved in executing these transactions.
For instance, ING and Société Générale S.A. decided the first oil trade by using a prototype of the Blockchain platform, (Easy Trading Connect). ING also anticipated the usage of Blockchain would help to reduce its involvement in the transaction from 3 hours to 25 minutes, which results in 30% cost savings per transaction.
The rising acceptance of electric vehicles (EVs) and the lack of coordination between consumers and charging stations enabled the adoption of smart contract solution. As, smart contract aid the EV’s to charge or discharge based upon the needs of the electric grid, which enables the vehicles to act as mobile batteries and to help stabilize the grid. Furthermore, the high adoption of smart contract solutions are expected to reduce labour costs, manual and semi-automated processes, capital costs through faster settlements, and technology costs by decreasing dependency on redundant systems.
North America is Expected to Hold Major Share
With blockchain adoption in the energy sector, transactions such as energy trading can be recorded and settled almost instantly, with no need for an intermediary and with little need for reconciliation since all parties are using the same platform. North Americans as early technological adaptors are having significant adoption of blockchain in the energy sector.The region is experiencing an increasing number of investments and partnerships, since the first blockchain in energy transaction took place, in 2016, in Brooklyn, New York. Companies in the region are partnering with other countries or having high investments to develop products related to energy sector using blockchain technology.
For instance, Bovlabs, a startup working to empower clean energy, entered into a partnership with Enchanted Rock, to test blockchain’s ability to bid into wholesale markets, with the ERCOT (Electric Reliability Council of Texas), and is expected to enter as a blockchain-based retailer in energy sector.
In another instance, LO3 Energy entered into a partnership with Energy Web Foundation (EWF), to work on standardizing data for use in EWF’s blockchain, which is designed specifically for the energy industry. As said by the LO3’s CEO, creating a data standard for transacting energy across projects and users, will be vital to meeting blockchain’s potential. Omega Grid software is operating on-site at the Stone Edge Microgrid, to test the blockchain based software’s ability to calculate optimal power flow and locational price, for each asset, on 5-minute intervals, and accept the best bids from the asset to control the load.
Competitive Landscape
The Blockchain Market in the Energy Sector is highly competitive and consists of several major players. In terms of market share, few of the major players currently dominate the market. These major players with prominent share in the market are focusing on expanding their customer base across foreign countries. These companies are leveraging on strategic collaborative initiatives to increase their market share and increase their profitability. The companies operating in the market are also acquiring start-ups working on Blockchain Market in the Energy technologies to strengthen their product capabilities. In July 2018, Microsoft Corporation announced the launch of the Enterprise Blockchain partnership, in Taiwan. The company has entered the partnership with Digital China and Hot Cool, in the hope that the three companies can use blockchain technology to enhance financial, e-commerce, entertainment, and other industries.
Reasons to Purchase this report:
– The market estimate (ME) sheet in Excel format
– Report customization as per the client’s requirements
– 3 months of analyst support
1 INTRODUCTION
1.1 Study Deliverables
1.2 Study Assumptions
1.3 Scope of the Study
2 RESEARCH METHODOLOGY
3 EXECUTIVE SUMMARY
4 MARKET DYNAMICS
4.1 Market Overview
4.2 Introduction to Market Drivers and Restraints
4.3 Market Drivers
4.3.1 Emergence Of Variable Electricity Rates And Need For Peer To Peer Trading
4.3.2 Aggressive Spending By Venture Capitalists
4.4 Market Restraints
4.4.1 Scalability Constraints
4.5 Value Chain / Supply Chain Analysis
4.6 Industry Attractiveness Porters Five Force Analysis
4.6.1 Threat of New Entrants
4.6.2 Bargaining Power of Buyers/Consumers
4.6.3 Bargaining Power of Suppliers
4.6.4 Threat of Substitute Products
4.6.5 Intensity of Competitive Rivalry
5 MARKET SEGMENTATION
5.1 By Application
5.1.1 Payments
5.1.2 Smart Contracts
5.1.3 Digital Identities
5.1.4 Governance, Risk, and Compliance Management
5.1.5 Other Applications
5.2 Geography
5.2.1 North America
5.2.2 Europe
5.2.3 Asia Pacific
5.2.4 Latin America
5.2.5 Middle East and Africa
6 COMPETITIVE LANDSCAPE
6.1 Company Profiles
6.1.1 SAP SE (SAP)
6.1.2 Microsoft Corp
6.1.3 Accenture PLC
6.1.4 IBM Corporation
6.1.5 LO3 Energy Inc.
6.1.6 GREENEUM
6.1.7 Drift Marketplace Inc.
6.1.8 IOTA Foundation
6.1.9 Btl Group Ltd
6.1.10 Power Ledger Pty Ltd
6.1.11 ImpactPPA
6.1.12 Electron (Chaddenwych Services Limited)
7 INVESTMENT ANALYSIS
8 MARKET OPPORTUNITIES AND FUTURE TRENDS
MARKET SEGMENTATION
By Application
Payments
Smart Contracts
Digital Identities
Governance, Risk, and Compliance Management
Other Applications
Geography
North America
Europe
Asia Pacific
Latin America
Middle East and Africa
Cloud Collaboration Market – Growth, Trends, and Forecasts (2019 – 2024)
| Information & Communications Technology | Published by: Mordor Intelligence | Market: |
| 100 pages | Published: 13-06-2019 |
- Information & Communications Technology
- Mordor Intelligence
- 100 pages
- Published: 13-06-2019
Market Overview
The Cloud Collaboration market was valued at USD 26.11 billion in 2018 and is expected to register a CAGR of 13.43%, over the forecast period (2019-2024).
Employees across organizations use cloud-based collaboration platform to share and work together on projects at once. Cloud collaboration enables to achieve high productivity with access to real-time data. Cloud collaboration offers high agility to companies and enables easy data sharing among remote and virtual users. With changing business requirements, companies are now looking for services, which offer easy access and increased productivity thereby supporting the growing need for agile support.
With increasing automation trends along with the changing mobility, it has become increasingly important for industries to look for solutions that can offer services thereby reducing the overall infrastructure costs.
Moreover, businesses adopting mobile services and implementing new policies to increase the employee interaction and ease of use, has become important to provide accessibility to data across multiple end-point devices.
These services allow the client and employees to access files and data who are working on offsite locations, which makes operations much more accessible. It also lets users with BYOD (Bring your own device) to take full advantage of accessing the data over the cloud.
Scope of the Report
Cloud collaboration is a type of enterprise collaboration that allows employees to work together on documents and other data types, which are stored off-premises and outside of the company firewall. Employees use a cloud-based collaboration platform to share, edit and work together on projects. Cloud collaboration enables two or more people to work on a project at once.
Key Market Trends
Demand for Enterprise Social Collaboration is on the Rise
In recent years, enterprise social collaboration(ESC) solutions have been able to connect people around the world effectively. Social applications have been limited by technology and might work fine for one department but not for another. With the advent of the cloud, the integration of social collaboration solutions is easier than ever.
The demand for enterprise social collaboration is on the rise and with good reason. With the millennials becoming an increasingly larger part of the workforce, CIOs will be forced to face enterprise social collaboration (ESC) in the future. Intelligent CIOs-who are ahead of the trend have already embraced it, leading to staggering results.
When properly integrated, ESC solutions empower both employees and employer. It can instill the intimacy and fun of social media into work-related communications, and lead to accomplishing tasks in new and more efficient ways. Trusted partners and valued customers can also be integrated directly into the network to everyone’s mutual advantage.
Cloud Collaboration in North America is Driven by the Adoption of Cloud Computing
Cloud collaboration in the region is mainly driven by businesses that are adopting cloud computing to increase capacity and productivity. Companies in the region are moving beyond the public cloud and stepping into a new era of hybrid IT that combines public cloud, private cloud, and traditional IT. These organizations have implemented a hybrid cloud strategy as it is helping them to improve the way they run their business and deliver services to customers.
As per the RightScale’s State of the Cloud Report 2018, over 80% of the North American and European companies are using a complex deployment model in the cloud, i.e., 51% of the hybrid and 21% implementing a multi-cloud strategy, with an average of five cloud providers. This has further stimulated the cloud collaboration demand. With automation trends prominent in the region, it has become increasingly important for industries to look for solutions that can offer services to reduce infrastructure costs.
Also, the increased electronic device penetration has resulted in the high adoption of BYOD, which has forced companies to adopt cloud collaboration to address employee needs. Furthermore, the presence of prominent startups with an aggressive BYOD policy and freedom for employees has augmented the growth of the cloud collaboration market.
Competitive Landscape
The Cloud Collaboration Market is highly competitive and consists of several major players. In terms of market share, few of the major players currently dominate the market. These major players with a prominent share in the market are focusing on expanding their customer base across foreign countries. These companies are leveraging on strategic collaborative initiatives to increase their market share and increase their profitability. The companies operating in the market are also acquiring start-ups working on cloud collaboration technologies to strengthen their product capabilities. In Feb 2018, Cisco completed its acquisition of BroadSoft, which would accelerate Cisco’s cloud strategy and collaboration portfolio by adding the industry’s leading cloud calling and contact center solutions to Cisco’s leading calling, meetings, messaging, customer care, hardware endpoints, and services portfolio.
Reasons to Purchase this report:
– The market estimate (ME) sheet in Excel format
– Report customization as per the client’s requirements
– 3 months of analyst support
1 INTRODUCTION
1.1 Study Deliverables
1.2 Study Assumptions
1.3 Scope of the Study
2 RESEARCH METHODOLOGY
2.1 Research Phases
2.2 Analysis Methodologies
3 EXECUTIVE SUMMARY
4 MARKET INSIGHTS
4.1 Market Overview
4.2 Industry Attractiveness Porters Five Force Analysis
4.2.1 Threat of New Entrants
4.2.2 Bargaining Power of Buyers/Consumers
4.2.3 Bargaining Power of Suppliers
4.2.4 Threat of Substitute Products
4.2.5 Intensity of Competitive Rivalry
4.3 Technology Snapshot
5 MARKET DYNAMICS
5.1 Introduction to Market Drivers and Restraints
5.2 Market Drivers
5.2.1 Increased Mobility and Changing Working Trends, Such as BYOD
5.2.2 Rising Need for Workforce Productivity and Enterprise Agility across Time Zones
5.3 Market Restraints
5.3.1 Data Security Concerns And Application Integration Complexities
6 MARKET SEGMENTATION
6.1 By Solution
6.1.1 Unified Communication and Collaboration
6.1.2 Enterprise Social Collaboration
6.1.3 Project and Team Management
6.1.4 Document Management System
6.1.5 Support Services
6.2 By Deployment Type
6.2.1 Public Cloud
6.2.2 Private Cloud
6.2.3 Hybrid Cloud
6.3 By End-user Industry
6.3.1 Telecommunication and ITES
6.3.2 Media and Entertainment
6.3.3 Education
6.3.4 Healthcare and Life Sciences
6.3.5 Banking and Financial System
6.3.6 Government and Public Sectors
6.3.7 Other End-user Industries
6.4 Geography
6.4.1 North America
6.4.2 Europe
6.4.3 Asia-Pacific
6.4.4 South America
6.4.5 Middle East and Africa
7 COMPETITIVE LANDSCAPE
7.1 Company Profiles
7.1.1 Microsoft Corporation
7.1.2 Cisco Systems Inc
7.1.3 Oracle Corporation
7.1.4 HighQ Solutions
7.1.5 IBM Corporation
7.1.6 Box Inc.
7.1.7 Citrix Systems Inc.
7.1.8 Jive Software Inc
7.1.9 Mitel Networks Corp
7.1.10 Intralinks Holdings Inc.
7.1.11 Salesforce.com Inc.
7.1.12 Hyperoffice
7.1.13 Atlassian Corporation PLC
7.1.14 Adobe Systems
7.1.15 Zoho Corporation
8 INVESTMENT ANALYSIS
9 MARKET OPPORTUNITIES AND FUTURE TRENDS
MARKET SEGMENTATION
By Solution
Unified Communication and Collaboration
Enterprise Social Collaboration
Project and Team Management
Document Management System
Support Services
By Deployment Type
Public Cloud
Private Cloud
Hybrid Cloud
By End-user Industry
Telecommunication and ITES
Media and Entertainment
Education
Healthcare and Life Sciences
Banking and Financial System
Government and Public Sectors
Other End-user Industries
Geography
North America
Europe
Asia-Pacific
South America
Middle East and Africa