Mediaboss Marketing

DUBLIN--(BUSINESS WIRE)--The "Geospatial Analytics Artificial Intelligence Market - Forecast (2020 - 2025)" report has been added to ResearchAndMarkets.com's offering.

The global geospatial analytics AI market is estimated to grow at a CAGR of 24.00% during the forecast period 2020-2025.

APAC is projected to be the fastest-growing market with a CAGR of 32.6%, which can be mainly attributed to the growing usage of geospatial analytics across various booming industrial sectors as well as the growing infrastructural developments in the region.

Geospatial Analytics AI Market Outlook

Geospatial Analytics Artificial Intelligence employs Artificial Intelligence technologies such as deep learning and machine learning to combine geographic information system (GIS) with business intelligence information. Geospatial Analytics AI finds a wide range of applications in logistics, transportation, surveying, agriculture, sales and marketing, medical and others. The multidisciplinary applications of Geospatial Analytics AI is primarily due to the assistance of the technology in decision making, resource planning and allocation that are essential in many industries. According to Industry ARC findings, the hazard assessment application segment will hold the largest market share during the forecast period.

Geospatial Analytics AI Market Growth Drivers

The growth of the transportation industry is expected to drive the geospatial analytics AI market during the forecast period. The aviation industry is a major segment where technology can be helpful in streamlining operations by controlling air traffic and increasing safety and security in airports. The growing fraudulent activities in the Banking, Financial Services, and Insurance (BFSI) sector are also expected to drive the market for Geospatial Analytics AI Market.

Geospatial Analytics AI Market Challenges

High costs of technology is a major challenge that is hampering the adoption of technology despite a wide number of applications across various industry verticals. Additionally, there are many national laws and regulations imposed by various countries that curtail the growth of the industry.

Geospatial Analytics AI Market Research Scope

The base year of the study is 2020, with forecast done up to 2025. The study presents a thorough analysis of the competitive landscape, taking into account the market shares of the leading companies. It also provides information on unit shipments. These provide the key market participants with the necessary business intelligence and help them understand the future of the Geospatial Analytics AI Market. The assessment includes the forecast, an overview of the competitive structure, the market shares of the competitors, as well as the market trends, market demands, market drivers, market challenges, and product analysis. The market drivers and restraints have been assessed to fathom their impact over the forecast period. This report further identifies the key opportunities for growth while also detailing the key challenges and possible threats.

Geospatial Analytics AI Market Report: Industry Coverage

Key Topics Covered:

1. Geospatial Analytics Artificial Intelligence Market - Overview

2. Geospatial Analytics Artificial Intelligence Market - Executive summary

3. Geospatial Analytics Artificial Intelligence Market

3.1. Comparative analysis

3.1.1. Product Benchmarking - Top 10 companies

3.1.2. Top 5 Financials Analysis

3.1.3. Market Value split by Top 10 companies

3.1.4. Patent Analysis - Top 10 companies

3.1.5. Pricing Analysis

4. Geospatial Analytics Artificial Intelligence Market Forces

4.1. Drivers

4.2. Constraints

4.3. Challenges

4.4. Porters five force model

5. Geospatial Analytics Artificial Intelligence Market -Strategic analysis

5.1. Value chain analysis

5.2. Opportunities analysis

5.3. Product life cycle

5.4. Suppliers and distributors Market Share

6. Geospatial Analytics Artificial Intelligence Market - By Data Source (Market Size -$Million / $Billion)

6.1. Market Size and Market Share Analysis

6.2. Application Revenue and Trend Research

6.3. Product Segment Analysis

7. Geospatial Analytics Artificial Intelligence Market - By Solution (Market Size -$Million / $Billion)

7.1. Hardware

7.1.1. Memory

7.1.2. Processor

7.1.3. Others

7.2. Software

7.2.1. By Deployment

7.2.1.1. Cloud

7.2.1.2. On-Premise

7.3. Services

8. Geospatial Analytics Artificial Intelligence Market - By Machine Learning (Market Size -$Million / $Billion)

8.1. Unsupervised Learning

8.2. Supervised Learning

8.3. Reinforced Learning

8.4. Semi-supervised Learning

8.5. Deep Learning

8.6. Others

9. Geospatial Analytics Artificial Intelligence Market - By Applications (Market Size -$Million / $Billion)

9.1. Geographic Information

9.2. Real Estate

9.3. Coastal application

9.4. Sales & Marketing

9.5. Fraud Detection

9.6. Transport & Logistics

9.7. Agriculture

9.8. Surveying

9.9. Hazard assessment

9.10. Natural Resource Management

9.9. Others

10. Geospatial Analytics Artificial Intelligence - By Geography (Market Size -$Million / $Billion)

10.1. Geospatial Analytics Artificial Intelligence Market - North America Segment Research

10.2. North America Market Research (Million / $Billion)

10.3. Geospatial Analytics Artificial Intelligence - South America Segment Research

10.4. South America Market Research (Market Size -$Million / $Billion)

10.5. Geospatial Analytics Artificial Intelligence - Europe Segment Research

10.6. Europe Market Research (Market Size -$Million / $Billion)

10.7. Geospatial Analytics Artificial Intelligence - APAC Segment Research

10.8. APAC Market Research (Market Size -$Million / $Billion)

11. Geospatial Analytics Artificial Intelligence Market - Entropy

11.1. New product launches

11.2. M&A's, collaborations, JVs and partnerships

12. Geospatial Analytics Artificial Intelligence Market - Industry / Segment Competition landscape Premium

12.1. Market Share Analysis

12.1.1. Market Share by Country- Top companies

12.1.2. Market Share by Region- Top 10 companies

12.1.3. Market Share by type of Application - Top 10 companies

12.1.4. Market Share by type of Product / Product category- Top 10 companies

12.1.5. Market Share at global level- Top 10 companies

12.1.6. Best Practises for companies

13. Geospatial Analytics Artificial Intelligence Market Company Analysis

13.1. Market Share, Company Revenue, Products, M&A, Developments

13.2. Google

13.3. Microsoft

13.4. Geoblink

13.5. ESRI

13.6. Trimble Inc.

13.7. HEXAGON

13.8. Harris Corporation

13.9. Digital Globe

13.10. Bentley Systems

13.11. Incorporated

13.12. General Electric

14. Geospatial Analytics Artificial Intelligence Market - Appendix

For more information about this report visit https://www.researchandmarkets.com/r/isah13

See more here:
Geospatial Analytics Artificial Intelligence Market (2020 to 2025) - Drivers, Constraints and Challenges - ResearchAndMarkets.com - Business Wire

Were halfway through 2020 and its safe to say that the year will be forever associated with the COVID-19 pandemic. For most of the last six months travel restrictions, lockdowns, social distancing and mask wearing have been put in place in an attempt to curtail the spread. Now, as the world attempts to reopen, governments and businesses must deal with the dual problems of restarting after the shutdowns and, in the absence of a vaccine, trying to contain further outbreaks. Technology is playing a key role in the research trying to understand the virus and eventually developing that vaccine. Can it also play a part in containing the spread until it is deployed? Can it help life return to normal?

Addfor, an Italian company with almost two decades of experience in Artificial Intelligence Solutions development for engineering, has created an AI-enabled system called citySAFE that can help to monitor so-called hot spots as well as mitigation efforts in an attempt to limit the spread. citySAFE interfaces with already installed camera systems or mobile cams, to provide aggregate information for either outdoor or indoor public and private spaces. Lenovo is collaborating with Addfor by defining and providing the right system hardware configuration to support the immense raw processing power required by a high camera-count video streaming.

The citySAFE application relies on a simplified interface that displays critical situations in real-time, leveraging available data about infection and hospitalization rates, then color-coding areas accordingly. For example, if a hot spot springs up, citySAFE can, in real time, assess the extent to which mitigation efforts in that area are being followed. All indices, such as counting populations, population density, or percentage of mask usage are calculated in real-time and grouped in space and time to be explored both geographically and temporally with an advanced graphical interface. Health officials can then issue warnings and deploy personnel to remind people and businesses about masks social distancing, and other safe practices. This same scenario could play out for a private company with a large footprint campus, manufacturing or distribution complex.

citySAFE was recently tested on a large scale in Turin, Italy with the collaboration of the public administration and other local authorities. It is the only integrated system available at the moment that allows the timely and continuous monitoring of an entire city, either from city surveillance or aerial cameras, for the issues related to the control of the spread of the COVID-19 virus. By using existing city camera infrastructure, citizens are subjected only to their existing level of CCTV observation.

This type of continuous streaming of live video data requires tremendous processing power, both at the edge, where the video is captured, and in the data center where the results are compiled, run through the algorithms for inference, distributed and retrained. In this context, Lenovo is providing the unique rugged ThinkSystem SE350 edge server. By using the computational power of the high-performance NVIDIA T4 GPU, the ThinkSystem SE350 delivers video streaming wirelessly from cameras, and real-time inference at the edge. On the back end, the Lenovo GPU dense ThinkSystem SR670, designed to support up to eight high-performance NVIDIA V100 GPUs, is built for running large AI workloads such as citySAFE and scales linearly as requirements grow. Both the ThinkSystem SE350 and SR670 are built on Intel Xeon processors for optimal performance and security.

We know that the pandemic will not go on forever: A vaccine will be found and deployed. Life will return to normal. When it does, citySAFE and its associated infrastructure can be repurposed for developing new or enhancing existing services the city administration or private companies provide citizens or employees such in areas such as safety, parking management, waiting times, and advanced digital signage systems for traffic or missing persons alerts.

In 2100s, future historians will study the COVID-19 pandemic, the same way that weve studied the Spanish Flu outbreak of 1918. They will see the mistakes from 1918, some corrected, some repeated, in 2020. And they will see a global crisis fought on a local basis. Mitigating the spread of the virus in the interim until a vaccine is developed, while restarting the economies of the world, is the tightrope we find ourselves on now. How we execute those precarious steps may end up being the yardstick by which those future historians measure us. In the face of these challenges, how did we get life to return to normal?

Go here to see the original:
Using Artificial Intelligence in the Fight Against COVID-19 - HPCwire

Artificial intelligence once relegated to academic studies and sci-fi nerds has become one of the hottest technologies, infiltrating every industry.

AI adoption was already accelerating before the COVID-19 crisis, but experts say that demand for AI tools is now is poised to grow even faster.

"The entire industry of AI is getting a huge boost from this unfortunate crisis," David Blumberg, founder and managing partner at Blumberg Capital, told Business Insider in May. "There is a silver lining to this dark cloud that we've all been living in for over two and a half, three months."

Former Cisco CEO John Chambers, who now runs his own venture firm JC2 Ventures, told Business Insider in an interview in May that he expects one to five major AI players to emerge from the current crisis.

AI has helped businesses take on big and small tasks, from making long-term sales growth projections to the automation of routine, time-consuming tasks.A 2019 Gartner survey found that major organizations planned to double their number of AI-related initiatives in the following year, from an average of 4 to 10. But as they pandemic has forced businesses to try to adapt to major changes, like the sudden pivot to remote work and tightening budgets, they're looking for ways to streamline and operate more efficiently.

"AI is best at solving all these really boring meat-and-potato problems," James Cham, a partner at Bloomberg Partners, told Business Insider. Many of the opportunities for using AI involve "straightforward process engineering," he said, where the technology can be used to shorten or streamline a process.

Industries like collaboration, shipping logistics, and manufacturing and warehousing will be particularly keen on using AI, said Sandeep Bhadra, a partner at Vertex Ventures.

Jake Saper at Emergence Capital had a similar prediction, that "vertical" specific AI software will be in more demand.

Here are 12 startups that analysts and investors say are well-positioned to grow thanks to a surge in demand for AI tools:

Originally posted here:
These 12 artificial intelligence startups are poised for success, particularly in a post-COVID world, according to experts - Business Insider

Researchers have figured out a way to transform a few dozen pixels into a high resolution image of a face using artificial intelligence.

A team from Duke University in the US created an algorithm capable of "imagining" realistic-looking faces from blurry, unrecognisable pictures of people, with eight-times more effectiveness than previous methods.

"Never have super-resolution images been created at this resolution before with this much detail," said Duke computer scientist Cynthia Rudin, who led the research.

Sharing the full story, not just the headlines

The images generated by the AI do not resemble real people, instead they are faces that look plausibly real. It therefore cannot be used to identify people from low resolution images captured by security cameras.

The PULSE (Photo Upsampling via Latent Space Exploration) system developed by Dr Rudin and her team creates images with 64-times the resolution than the original blurred picture.

The PULSE algorithm is able to achieve such high levels of resolution by reverse engineering the image from high resolution images that look similar to the low resolution image when down scaled.

The images generated by enhancing the pixels do not represent real people (Duke University)

Through this process, facial features like eyelashes, teeth and wrinkles that were impossible to see in the low resolution image become recognisable and detailed.

"Instead of starting with the low resolution image and slowly adding detail, PULSE traverses the high resolution natural image manifold, searching for images that downscale to the original low resolution image," states a paper detailing the research.

The AI algorithm is able to enhance a few dozen pixels into a high-resolution picture of a face (Duke University)

"Our method outperforms state-of-the-art methods in perceptual quality at higher resolutions and scale factors than previously possible."

The system could theoretically be used on low resolution images of almost anything, ranging from medicine and microscopy, to astronomy and satellite imagery.

This means noisy, poor-quality images of distant planets and solar systems could be imagined in high resolution.

The research will be presented at the 2020 Conference on Computer Vision and Pattern Recognition (CVPR) this week.

Continued here:
Artificial intelligence enhances blurry faces into 'super-resolution images' - The Independent

London, June 15, 2020 (GLOBE NEWSWIRE) -- The automotive artificial intelligence market is expected to grow at a CAGR of 39.8% from 2019 to reach $15.9 billion by 2027.

Several established automotive organizations across the globe are increasingly struggling with the rising cost of operations, dissatisfied customers, declining sales, and unidentified competition. Advanced capabilities of AI, coupled with rising consumer expectations, have pushed the automotive industry into adopting artificial intelligence. Several organizations are investing heavily in order to reap the profits in highly dynamic and competitive market environments. The global artificial intelligence in automotive market is expected to witness strong growth over the coming years due to the growing demand for autonomous vehicles, adoption of advanced automotive solutions, growing adoption of artificial intelligence for traffic management, and government initiatives and investments towards connected and autonomous vehicles.

DownloadFree Sample Report Now @https://www.meticulousresearch.com/download-sample-report/cp_id=4996

The increasing volume of data gathered through IoT devices, coupled with the widespread availability of high-speed broadband networks and the emergence of 5G technologies is driving the need for faster data processing. Apart from this, widening the implementation of computer vision technologies across vehicles and shifting consumer preferences for premium vehicles to improve the driving experience while enhancing the vehicle and pedestrian safety are some of the key factors anticipated to drive the growth of artificial intelligence in automotive market in the near future. However, lack of infrastructure coupled with the high procurement operating cost is expected to challenge the growth of the artificial intelligence in automotive market growth during the forecast period.

The global market for artificial intelligence in automotive industry is expected to grow at a CAGR of 39.8% from 2019 to reach $15.9 billion by 2027. The market is witnessing consistent growth owing to the increasing demand for smart IoT devices in automotive, surging demand for connected vehicles, and adoption of advanced driver assistance systems. Apart from this, surging adoption of AI-based solutions and services among the automotive industry is also contributing to the overall growth of artificial intelligence in automotive market. While developed economies offer technological growth opportunities through the proliferation of advanced technologies, the ongoing digital transformation initiatives across emerging economies such as Asia-Pacific and Latin America are likely to offer high growth opportunities for vendors operating in the market.

The global artificial intelligence in automotive market is mainly segmented by components (hardware, software, services), by technology (machine learning, computer vision, natural language processing, context-aware computing), by process (signal recognition, image recognition, voice recognition, data mining), by application (semi-autonomous driving, human-machine interface), and region.

Speak to our Analysts to Understand the Impact of COVID-19 on Your Business:https://www.meticulousresearch.com/speak-to-analyst/cp_id=4996

Based on components, the artificial intelligence in automotive market is segmented into hardware, software, and services. The software segment dominated the artificial intelligence in automotive market in 2019 in terms of market share. This is mainly attributed to the growing usage of learning analytics, growing acceptance of in-car assistants driven by machine learning techniques and an increase in demand for autonomous platforms for automotive industry. However, the services segment is slated to grow at the fastest CAGR during the forecast period and will emerge as the major segment in terms of market share by 2027. This growth is mainly driven by the surging demand for AI-based cloud services for autonomous vehicles, over-the-air (OTA) software services, traffic and mapping services, shared mobility services, remote maintenance services, technical support & training services, maintenance & support services, integration services, performance measurement services, and consulting services.

Based on technology, the artificial intelligence in automotive market is segmented into machine learning, computer vision, natural language processing, and context-aware computing. The machine learning technology segment held the largest share of the overall automotive artificial intelligence market in 2019, owing to the demand for signal diagnosing, image recognition, speech recognition, data mining, and an increase in unstructured data generated by the automotive industry. However, the computer vision technology is slated to grow at the fastest CAGR during the forecast period, due to a widening implementation of computer vision in semi-autonomous vehicles to tackle distracted/ drowsy driving and surging use of LIDAR sensors and cameras to avoid vehicle collisions.

Based on process, the overall artificial intelligence in automotive market is segmented into signal recognition, image recognition, voice recognition, and data mining. The signal recognition segment dominated the artificial intelligence in the automotive market in 2019 and is also estimated to continue its dominance over the forecast period. The growth in this market segment is attributed to the increasing growth of automotive safety systems, rising consumer preference for signal recognition in autonomous vehicles, and government regulations pertaining to the safety rating of a vehicle to reduce road collisions. However, the image recognition process is slated to grow at the fastest CAGR during the forecast period, due to growing demand for advanced driver assistance systems (ADAS) such as road signs detection and pedestrian protection systems.

Based on application, the artificial intelligence in automotive market is majorly segmented into semi-autonomous driving and human-machine interface. The human-machine interface segment dominated the artificial intelligence in automotive market in 2019. This is attributed to the increasing demand for interactive technologies in vehicles, connected systems, and smart convenient features.

Quick Buy Automotive AI MarketResearch Report: https://www.meticulousresearch.com/buy_now.php?pformat=295&vformat=877

Geographically, the global artificial intelligence in automotive market is segmented into five regions, namely, North America, Europe, Asia-Pacific, Latin America, and the Middle East & Africa with a further analysis of major countries in these regions. North America accounted for the largest share of global artificial intelligence in automotive market in 2019, followed by Europe and the Asia-Pacific region. The largest share of this region is mainly attributed to the presence of developed economies, such as the United States and Canada, focusing on enhancing the existing solutions in the automotive industry, and the existence of major players in this market along with a high willingness to adopt advanced technologies. Apart from this, the growing demand for enhanced user experience, rising living standards, growing adoption of autonomous vehicles and availability of high-end infrastructure, increasing R&D expenditure, and various government initiatives supporting AI research are contributing to the growth in this region.

On the other hand, Asia-Pacific region is projected to grow at the highest CAGR during the forecast period. This growth is attributed to an increase in demand for premium vehicles, growing investments in AI technology for improved productivity, and increasing adoption of AI-based solutions and services in the automotive industry. Apart from this, developing internet & connectivity infrastructure, growing adoption of intelligent solutions and increasing digitalization, and increasing investments by the major players in this region are contributing to the growth in the Asia Pacific AI in automotive market.

Some of the key players operating in the global artificial intelligence in automotive market are Google LLC (U.S.), IBM Corporation (U.S.), Intel Corporation (U.S.), Microsoft Corporation (U.S.), Nvidia Corporation (U.S.), Tesla, Inc. (U.S.), Xilinx, Inc. (U.S.), Micron Technology, Inc. (U.S.), Ford Motor Company (U.S.), General Motors Company (U.S.), Harman International Industries Inc. (South Korea), Honda Motor Co., Ltd. (Japan), Audi AG (Germany), and Qualcomm Technologies, Inc. (U.S.), among others.

To gain more insights into the market with a detailed table of content and figures, click here:https://www.meticulousresearch.com/product/automotive-artificial-intelligence-market-4996/

Scope of the Report:

Automotive AI Market, by Component

Automotive AI Market, by Technology

Automotive AI Market, by Process

Automotive AI Market, by Application

Automotive AI Market, by Geography

DownloadFree Sample Report Now @https://www.meticulousresearch.com/download-sample-report/cp_id=4996

Amidst this crisis, Meticulous Researchis continuously assessing the impact of COVID-19 pandemic on various sub-markets and enables global organizations to strategize for the post-COVID-19 world and sustain their growth. Let us know if you would like to assess the impact of COVID-19 on any industry here-https://www.meticulousresearch.com/custom-research.php

Related Reports:

Artificial Intelligence in Supply Chain Market by Component (Platforms, Solutions) Technology (Machine Learning, Computer Vision, Natural Language Processing), Application (Warehouse, Fleet, Inventory Management), and by End User - Global Forecast to 2027

https://www.meticulousresearch.com/product/artificial-intelligence-ai-in-supply-chain-market-5064/

Artificial Intelligence in Manufacturing Market by Component, Technology (ML, Computer Vision, NLP), Application (Cybersecurity, Robot, Planning), Industry (Electronics, Energy, Automotive, Metals and Machine, Food and Beverages) Global Forecast to 2027

https://www.meticulousresearch.com/product/artificial-intelligence-in-manufacturing-market-4983/

Artificial Intelligence in Healthcare Market by Product (Hardware, Software, Services), Technology (Machine Learning, Context-Aware Computing, NLP), Application (Drug Discovery, Precision Medicine), End User, And Geography - Global Forecast to 2025

https://www.meticulousresearch.com/product/artificial-intelligence-healthcare-market/

Artificial Intelligence in Security Market by Offering (Hardware, Software, Service), Security Type (Network Security, Application Security), Technology (Machine Learning, NLP, Context Awareness,), Solution, End-User, and Region - Global Forecast to 2027

https://www.meticulousresearch.com/product/artificial-intelligence-in-security-market-4991/

About Meticulous Research

The name of our company defines our services, strengths, and values. Since the inception, we have only thrived to research, analyze and present the critical market data with great attention to details.

Meticulous Research was founded in 2010 and incorporated as Meticulous Market Research Pvt. Ltd. in 2013 as a private limited company under the Companies Act, 1956. Since its incorporation, with the help of its unique research methodologies, the company has become the leading provider of premium market intelligence in North America, Europe, Asia-Pacific, Latin America, and Middle East & Africa regions.

With the meticulous primary and secondary research techniques, we have built strong capabilities in data collection, interpretation, and analysis of data including qualitative and quantitative research with the finest team of analysts. We design our meticulously analyzed intelligent and value-driven syndicate market research reports, custom studies, quick turnaround research, and consulting solutions to address business challenges of sustainable growth.

See original here:
Automotive Artificial Intelligence Market Worth $15.9 Billion by 2027, Growing at a CAGR of 39.8% from 2019- Global Market Opportunity Analysis and...