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Artificial Intelligence in Big Data Analytics and IoT: Market for Data Capture, Information and Decision Support Services 2019 – 2024

Published: May 2019: Pages: 221

Pricing: Single-user License: $1,995 USD; Multi User (Up to 5 Users): $2,995 USD; Site License: $3,995 USD; Global Site License: $4,995 USD

The Internet of Things (IoT) in consumer, enterprise, industrial, and government market segments has very unique needs in terms of infrastructure, devices, systems, and processes. One thing they all have in common is that they each produce massive amounts of data, most of which is of the unstructured variety, requiring big data technologies for management.

Artificial Intelligence (AI) algorithms enhance the ability for big data analytics and IoT platforms to provide value to each of these market segments. We see three different types of IoT Data: (1) Raw (untouched and unstructured) Data, (2) Meta (data about data), and (3) Transformed (valued-added data). Artificial Intelligence (AI) will be useful in support of managing each of these data types in terms of identifying, categorizing, and decision making.

AI coupled with advanced big data analytics provides the ability to make raw data meaningful and useful as information for decision-making purposes. The use of AI for decision making in IoT and data analytics will be crucial for efficient and effective decision making, especially in the area of streaming data and real-time analytics associated with edge computing networks. Real-time data will be a key value proposition for all use cases, segments, and solutions. The ability to capture streaming data, determine valuable attributes, and make decisions in real-time will add an entirely new dimension to service logic. In many cases, the data itself, and actionable information will be the service.

This report evaluates various AI technologies and their use relative to analytics solutions within the rapidly growing enterprise and industrial data arena. The report assesses emerging business models, leading companies, and solutions. The report also analyzes how different forms of AI may be best used for problem solving. The report also evaluates the market for AI in IoT networks and systems. The report provides forecasting for unit growth and revenue for both analytics and IoT from 2019 – 2024.


Artificial Intelligence, Industrial IoT, and Smart Machines in Enterprise and Industrial Automation 2019 – 2024

Published: June 2019; Pages: 539

Pricing: Single-user License: $2,995 USD; Multi User (Up to 5 Users): $3,995 USD; Site License: $ 4,995 USD; Global Site License: $ 6,995 USD

Artificial Intelligence (AI) algorithms enhance the ability for big data analytics and IoT platforms to provide value to each of these market segments. We see three different types of IoT Data: (1) Raw (untouched and unstructured) Data, (2) Meta (data about data), and (3) Transformed (valued-added data). Artificial Intelligence (AI) will be useful in support of managing each of these data types in terms of identifying, categorizing, and decision making. AI coupled with advanced big data analytics provides the ability to make raw data meaningful and useful as information for decision-making purposes. The use of AI for decision making in IoT and data analytics will be crucial for efficient and effective decision making, especially in the area of streaming data and real-time analytics associated with edge computing networks.

Industrial Internet of Things (IIoT) solutions are poised to transform many industry verticals including healthcare, retail, automotive, and transport. For many industries, IIoT will significantly improve reliability, production, and customer satisfaction. While, IIoT will initially improve existing processes and augmented current infrastructure, the ultimate goal will be to realize entirely new, and dramatically improved products and services. Successful companies will be those that understand how and where IoT technologies and solutions will drive opportunities for operational improvements, new and enhanced products and services, as well as completely new business models. IIoT will significantly improve reliability, production, and customer satisfaction. Initially focusing on improving existing processes and augmented current infrastructure, IIoT will rely upon as well as integrate with certain key technologies, devices, software, and applications. IIoT involves a substantial breadth and depth of technologies, many of which require careful integration and orchestration.

Smart machines collectively represent intelligent devices, machinery, equipment, and embedded automation software that perform repetitive tasks and solve complex problem autonomously. Along with Artificial Intelligence, IoT connectivity, and M2M communications, smart machines are a key component of smart systems, which include many emerging technologies such as smart dust, neuro computing, and advanced robotics. The drivers for enterprise and industrial adoption of smart machines include improvements in the smart workplace, smart data discovery, cognitive automation, and more. Currently conceived smart machine products include autonomous robots (such as service robots), self-driving vehicles, expert systems (such as medical decision support systems), medical robots, intelligent assistants (such as automated online assistants), virtual private assistants (Siri, Google Assistant, Amazon Alexa, etc.), embedded software systems (such as machine monitoring and control systems), neurocomputers (such as purpose-built intelligent machines), and smart wearable devices.

This research evaluates various AI technologies and their use relative to analytics solutions within the rapidly growing enterprise and industrial data arena. The report assesses emerging business models, leading companies, and solutions. It also analyzes how different forms of AI may be best used for problem solving. The report also evaluates the market for AI in IoT networks and systems. It provides forecasting for unit growth and revenue for both analytics and IoT from 2019 – 2024.

This research also provides an in-depth assessment of the chatbots market including global, regional, and country forecasts by industry, application, and business model. The report also include market sizing by Type (Text, Voice, and Hybrid), Use Case, Deployment Type, Value Chain Component, Market Segment (Consumer, Enterprise, Industrial, Government), Industry Vertical for years 2019 through 2024. The report provides analysis of the chatbot market across industry verticals with use cases in diverse sectors. It also provides analysis of chatbot companies including their strategic initiatives, solutions, applications, and services.

This research also evaluates IIoT technologies, companies, applications, services, and solutions. Report forecasts include overall global and regional IIoT outlook as well as IIoT by industry vertical, software, hardware, and services for the period 2019 to 2024. This research is critical to identifying opportunities for R&D, technology integration, and development of new solutions and applications across industry segments. Our findings, insights, data and forecasts are also a key part of capitalizing upon the market for new and enhanced hardware, software, platforms, and services for emerging IoT networks and systems. In support of these goals, the report provides critical analysis about IIoT technologies, companies, applications, services, and solutions.

This research also evaluates the smart machine ecosystem including technology building blocks, leading company strategies, products and services. The report evaluates various smart machine solutions, products, and services including Autonomous Robots, Expert Systems, Intelligent Assistants, Neurocomputers, and Wearable Devices. This report also evaluates the hardware, embedded software, and related services for smart machines. The report also assesses the market for smart machines in many industry verticals including Aerospace and Defense, Automotive, Banking, Consumer Electronics, Healthcare, Industrial Automation, Security, Transportation and Logistics.


Smart Buildings Market by Technology (AI, IoT, Indoor Wireless), Infrastructure, Solutions (Asset Tracking, Data Analytics, IWMS), and Regions 2019 – 2024

Published: May 2019; Pages: 289

Pricing by License: Single-user License: $1,995 USD; Multi User (Up to 5 Users): $2,995 USD; Enterprise Site License: $3,995 USD; Global Enterprise License: $4,995 USD

The smart buildings market consists of warehouses, factories, office buildings and other enterprise, industrial, and government structures. Intelligent structures leverage a variety of interdependent technologies such as Artificial Intelligence (AI), broadband wireless (including WAN and indoor wireless), cloud computing (including edge computing), and Internet of Things (IoT) networks to improve operational efficiency and enable a more safe and productive environment.

The smart buildings market is related to the smart workplace market, which includes some important enterprise and industrial automation systems and solutions such as integrated workplace management systems (IWMS), decision support systems utilizing advanced data analytics, and business asset management.

Leading companies within the commercial real estate sector are realizing tangible benefits by leveraging smart buildings market solutions as owners are able to charge higher fees for technology-enabled intelligent buildings. Accordingly, over 80% of new construction involves at least one facet of IoT and/or related smart buildings market related technologies. However, it is important to note that roughly 90% of legacy buildings in developed economies have issues that will require substantial retrofitting.

What Makes a Building “Smart”? The term smart or intelligent building refers to an enterprise structure that is supported by software and systems to ensure more efficient and effective operations. Additional goals are to enhance the health and well-being and protect enterprise assets. Intelligent buildings are also closely associated with the concept of the smart workplace, which extends beyond a centralized work zone to include distributed and remote employees and corporate assets.

Commercial real estate owners are able to charge higher lease fees for intelligent buildings for a variety of reasons including lower operational costs as well as support for improved safety, comfort, security, and productivity for workers. Smart workplace benefits facilitated by intelligent buildings include work process improvement, work flow improvement, internal and external supply chain management optimization.

Smarter Building Data Analytics: Many of the solutions that make buildings smarter involve IoT capabilities. However, data and information systems to enable better decision-making are also critically important. AI may be implemented in conjunction with big data tools to enable enhanced data analytics. Almost Analytics Solutions are good at looking for patterns and unstructured data, supplementing them with AI can provide additional benefit of learning from experience.

Since enterprise verticals in many different Industries rely on buildings for operation, many market segments can benefit. For example AI algorithms in an office building can learn from the patterns of workers to determine the optimal time to adjust lighting and HVAC. In another example, AI support at healthcare facilities can help with critical care, ensuring that resources are available where they are needed the most based on historical patterns of occupancy and resource allocation.

Integrated Workplace Management Systems: The most efficient and effective smart buildings are those that include an Integrated Workplace Management System (IWMS). An IWMS solution is leveraged to both support a more integrated building control system as well as optimizing the workplace. This includes orchestrating workflow in processes relative to building resources and the environment in terms of things like optimal lighting, heating, and ventilation for workers.

IWMS solutions rely heavily upon IoT technology and data processing for optimal operation. The integration of AI can make these systems more efficient. For example, AI can assist IWMS solutions in determining optimal allocation of building resources based on environmental factors, workflow, and the availability and location of personnel and organizational assets. This is particularly useful in a corporate campus environment or university where there are multiple buildings that are often multi-purpose and shared among departments.

Smart Building Market Report: This report evaluates the smart buildings market including technologies, players, and solutions. The report analyzes smart buildings challenges and opportunities, assesses market potential, and provides accompanying smart buildings market sizing, globally as well as regionally, and by market segment for 2019 – 2024. The report includes analysis of technologies supporting smart building automation, IWMS, and smart workplace applications and services. Smart building solution areas covered include 5G, AI, data analytics, and edge computing.


Virtual Reality Market by Segment (Consumer, Enterprise, Industrial, Government), Equipment (Hardware, Software, Components) Applications and Solutions 2019 – 2024

Published: July 2019: Pages: 232

Pricing by License: Single-user License: $ 1,995 USD; Multi User (Up to 5 Users): $2,995 USD; Enterprise Site License: $3,995 USD; Global Enterprise License: $4,995 USD

This research provides an in-depth assessment of the virtual reality market including analysis of VR ecosystem and role of value chain partners, evaluation of recent VR patent filings and intellectual property, and analysis of current price metrics VR devices, apps, and content. The report also provides an assessment of key VR companies and solutions with SWOT analysis, analysis of emerging business models and evolution of VR monetization, analysis of VR component market: devices, software, hardware, platforms. The report also presents key VR growth drivers, market challenges, and emerging opportunities.

Previously encumbered by a combination of technology gaps and consumer readiness issues, virtual reality market is poised for substantive global growth, providing abundant opportunities for service providers, content developers, and ecosystem component providers. However, the high-growth phase for VR is anticipated to start within approximately two years, which is coincident with substantially lower broadband costs as a whole (wired and wireless connections) as well as greater user acceptance within both the consumer and business market segments.

It is important to note that the virtual reality market and other immersive technologies (such as the mixed reality market) will also be important to many industry for a variety of enterprise purposes including internal operations, managing supply chains, and supporting customers. Important industry verticals include commercial real estate management, automotive, public safety, education and training. The leading sector is anticipated to be instruction (education, training, and simulations).

For the consumer virtual reality market, we see entertainment and lifestyle enhancements leading the way with the former including VR enhanced gaming and the latter including a plethora of new apps such as virtual location experiences in which groups of people get together virtually in the cyber-world. Examples include everything from virtual alumni events to watching your favorite football team play in a virtual stadium with ultra-real sights, sounds, and even feelings and smells of game day. The advancement of AI embedded within the VR market will add to realism by introducing random events that happen within a given experience.

For enterprise and industrial virtual reality market segments, we see simulations and training leading the way. We see everything from situational training (such as Verizon using Striver to train its employees how to better deal with robberies) to more traditional expectations such as VR enhanced simulations for flight and vehicle training. Businesses will also seek to use VR as a means to destress employees by offering them a virtual experience of their everyday work with random events thrown into the mix, both to add interest/amusement as well as to test and train them to see how they might react given a real-world experience such as how to best deal with a senile shoplifter.

In terms of venture investment, 2016 represented an intermediate peak for the virtual reality market with VR funding exceeding $800M. By way of comparison, the other major component of the overall immersive technology market (AR and MR) received about $450M in investment. More recently, the VR market has lagged AR/MR in terms of funding with the former receiving only $280M and the latter receiving over $850M in 2018.

However, the virtual reality market has done quite well over the last few years in terms of cumulative investment. By way of example, Jaunt VR alone receiving over $100M in investment money including from strategic investors such as Disney. However, VR is struggling to achieve market traction let alone critical mass. We see the virtual reality market gaining ground once 5G is more firmly in place commercially, but not because of wireless VR. Instead, we see a massive build-out of broadband as a whole (due to competition from the 5G market) as one of the fundamental drivers for VR adoption.

This research provides an in-depth assessment of the VR market including the following:

• Analysis of VR ecosystem and role of value chain partners
• Evaluation of recent VR patent filings and intellectual property
• Analysis of current price metrics VR devices, apps, and content
• Assessment of key VR companies and solutions with SWOT analysis
• Analysis of emerging business models and evolution of VR monetization
• Analysis of VR component market: devices, software, hardware, platforms
• Analysis of key VR growth drivers, market challenges, and emerging opportunities


Connected Device Market for Consumer, Enterprise, and Industrial IoT Devices by Use Case, Device Type, Application, Region, and Country 2019 – 2024

Published: March 2019; Pages: 109;

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Global Enterprise License:  $4,995 USD

The number, type, and purpose of connected devices is rapidly expanding as the Internet of Things (IoT) evolves beyond the current state of limited applications, many of which remain isolated and purpose-built for a given use case, industry vertical, and company. Over the course of the next four to six years, many IoT applications will become increasingly interconnected.

Some of these applications will be enhanced through communication with a smart device, which is a connected device that benefits embedded intelligence. In contrast, an IoT Device need not be smart, and in fact, many are relatively unintelligent devices that are typically single-purpose and rely upon intelligence to be provided elsewhere for data processing, analytics, analysis, and dispersal of actionable information, typically via a cloud services model.

It is important to note that cloud services may be either centralized or distributed via Multi-access Edge Computing (MEC) infrastructure. MEC will also facilitate an entirely new class of low-power devices that rely upon MEC equipment for processing. Stated differently, some IoT devices will be very light-weight computationally speaking, relying upon edge computing nodes for most of their computation needs.

Another driver for the expansion of connected devices is the Mobile Edge Computing market, will facilitate an entirely new class of low-power devices that rely upon MEC equipment for processing. Stated differently, some IoT devices will be very light-weight computationally speaking, relying upon edge computing nodes for most of their computation needs. The report evaluates the connected device market segment including consumer, enterprise, and industrial devices with associated connected device market sizing from 2019 to 2024.


Blockchain Technology Market by Use Case, Solution, Industry Vertical, Region 2019 – 2024

Published: February 2019; Pages: 198

Pricing by License: Single-user License: $ 1,995 USD; Multi User (Up to 5 Users): $ 2,995 USD; Enterprise Site License: $ 3,995 USD; Global Enterprise License: $ 4,995 USD

Blockchain and related distributed authentication and accounting technologies are poised to transform ICT, and is so doing, cause substantial disintermediation across a wide variety of industry verticals. Lessons learned in FinTech and traditional banking from the deployment and operation of decentralized authentication, clearing and settlement will be applied towards many telecom and computing problems for the benefit of many industry verticals. The impact will be wide-ranging, including everything from investing/trading to the legal cannabis industry, and very deep in terms of changes to supply chains and relationships between vendors, customers, and peers.

For example, blockchain is being used in the fleet tracking market to identify custody and ownership of vehicles. This assists the entire ecosystem, including fleet managers/owners, customers, and insurance companies. This will also help support a robust fractional usage/ownership value chain in which vehicles are used by multiple clients. In a related example, blockchain is also used in the general asset tracking market for similar purposes such as tracking ownership/custody of trailers that are often used by multiple semi-tractors as part of shipping operations and other logistics related industry verticals.

Integration and operation of blockchain technology will redefine how many other industries operate, dramatically improving efficiencies, and reduce the cost of doing business. One important example is the Internet of Things (IoT), which is a very promising area as Mind Commerce anticipates that the use of blockchain in IoT networks/systems will be one of the key means for authenticating and authorizing transactions. We see Blockchain as a Service representing a key service offering for many market segments as a mean of solution introduction and scalability via a cloud services model.

This research examines the technology, leading companies, and solutions in the evolving blockchain ecosystem. The report evaluates current and anticipated use cases for blockchain and assesses the market potential globally, regionally, and segmented by deployment type and industry vertical for the period 2019 to 2024. The report evaluates key players, solutions, and use cases. The report also assesses the prospect of integrating blockchain with other technologies including IoT and artificial intelligence. The report includes detailed forecasts by use case, application, and industry verticals from 2019 to 2024.


Artificial Intelligence Solutions Market by Industry Verticals 2018 – 2023

Published: December 2018; Pages: 509

Pricing by License: Single-user License: $ 1,995 USD; Multi User (Up to 5 Users): $ 2,995 USD; Enterprise Site License: $ 3,995 USD; Global Enterprise License: $ 4,995 USD

Artificial Intelligence (AI) is very confusing to the average enterprise or industrial manager. Corporations and government entities care very little about AI technologies as compared to real-world solutions solved by AI software and platforms. As part of its AI research business practice, we  sponsored a recent project to identify twenty-five of the top AI companies for 2018 within the Artificial Intelligence Solutions Market.

In addition to innovation and solving real-world problems, one of the most important criterion is diversity of AI solutions, which the top 25 AI companies represent. Those companies are covered in this report and are the following: Active.Ai, Anodot, AppZen, CarePredict, Crediwatch, DeepScale, Directly, Gamaya, Haptik, Imagen Technologies, Kreditech, Neurala, NewtonX, OccamzRazor, Onfido, Petuum, Signal Media, Spatial, Specif.io, Textio, Umbo Computer Vision, vPhrase, Wade & Wendy, Woobo.io, and Yanu.

This Artificial Intelligence Solutions Market report also evaluates many other AI companies, technologies, and solutions. The report covers AI solutions in all major industry verticals including agriculture, automotive, commercial real estate, education, electronics, finance, government, healthcare, human resources, legal, manufacturing, oil & gas, and more. The report includes qualitative analysis of AI use cases and applications by industry as well as forecasts for 2018 through 2023.


Title: Quantum Intelligence: Quantum Computing and Artificial Intelligence 2018 – 2023

Published: December 2018; Pages: 537

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While not anticipated to replace supercomputer based classical computing technologies for certain problem solving, quantum computing is well-positioned to support certain industry verticals and solve certain problems such as cybersecurity and cryptocurrencies that rely upon prime factoring. This is because binary constrained high performance computers would take an inordinate amount of time to solve come problems such as breaking down prime factors, a procedure necessary to support cryptology and blockchain technology.

Artificial Intelligence (AI) is poised to fundamentally shift the Information and Communications Technology (ICT) industry as technologies such as Machine Learning, Natural Language Processing, Deep Learning, and others dramatically enhance the performance of communications, apps, content, and digital commerce. AI will also drive new business models and create entirely new business opportunities as interfaces and efficiencies facilitate engagement that has been heretofore incomprehensible. AI further enhances the ability for Big Data Analytics and IoT platforms to provide value to each of these market segments.

Quantum computing and AI are highly synergistic with one another as the former speeds up problem solving for the latter, and the latter provides an automated learning structure for the former. This is anticipated to catalyze many benefits including faster parameter discovery, set-up, and even potentially algorithm adjustments. It is not beyond the realm of possibility that AI may at some point overcome to current hardware-centric limitations of quantum computing, allowing platforms to become less single purpose built machines.

This research assesses the technology, companies/organizations, R&D efforts, and potential solutions facilitated by quantum computing. It also evaluates the impact of quantum computing upon other major technologies and solution areas including AI, chipsets, edge computing, blockchain, IoT, big data analytics, and smart cities. It provides global and regional forecasts as well the outlook for quantum computing impact on hardware, software, applications, and services from 2018 to 2023.

This research also assesses the AI ecosystem, technologies, solutions and market outlook.  Key industry verticals covered include use of AI in Internet related services and products, Financial Services, Medical and Bio-informatics, Manufacturing, and Telecommunications.  Some of the key application areas covered include Marketing and Business Decision Making, Workplace Automation, Predictive Analysis and Forecast, Fraud Detection and Classification.

This research also evaluates AI analytics solutions within the rapidly growing enterprise and industrial data arena. The report assesses emerging business models, leading companies, and solutions. The report also analyzes how different forms of AI may be best used for problem solving. The report also evaluates the market for AI in IoT networks and systems. The report provides forecasting for unit growth and revenue for both analytics and IoT from 2018 – 2023.


Smart Buildings, Workplace Solutions and Integrated Workplace Management Systems 2018 – 2023

Published: December 2018; Pages: 628

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Improving the operational effectiveness and efficiency, safeguarding assets, and establishing new value-added services are a few of the fundamental goals of Smart Buildings. Enterprise will benefit in general, as will certain management services companies that operate large industrial facilities and equipment such as Drives, Pumps, Cooling Towers, and Compressors, which are all large, expensive, and utilize a lot of electricity. Internet of Things (IoT) solutions will improve lifecycle cost management for facilities and equipment through more intelligence utilization, maintenance, and predictive replacement.

IoT technologies are also anticipated to facilitate substantial positive revenue improvements within the commercial Real Estate (CRE) sector, enabling CRE companies to charge higher rents to tenants of IoT-enabled intelligent buildings as well as leverage various capabilities to provide Smart Workplace solutions. This will justify CRE industry development of Smart Building capabilities for new construction as well as justify substantial retrofits for existing buildings.

Intelligent use of IoT technologies will be also be the key to continuous improvements in the areas of process automation. This will positively impact core work flows for enterprise and industrial work locations ranging from factories and other industrial facilities to office buildings. The use of Big Data and Analytics tools will be key to transforming data captured into actionable information.

This research evaluates the Smart Buildings marketplace including technologies, players, and solutions. The report analyzes Smart Buildings challenges and opportunities, assessing market potential and provides accompanying forecasts globally as well as regionally and by market segment for 2018 – 2023.  It includes analysis of technologies supporting building automation, IWMS, and smart workplace applications and services. Solution areas covered include 5G, AI, Data Analytics, and Edge Computing.

This research also provides an in-depth analysis of the Smart Workplace including market trends, growth drivers, market challenges, leading companies, solutions, applications, and services. It analyzes the market segments by categories, product and services, connectivity and communication technology, and regions, providing forecasts for the 2018 – 2023 period. The report also analyzes smart workplace solution providers and provides specific market recommendations. This includes and evaluation of IWMS technology and applications with an assessment of business opportunities and market outlook.


Robotics and Automation Market by Cloud Robotics, UAV/Drones, Robotics Equipment, Components, Solutions, Apps and Services

Published: November 2018; Pages: 598

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Robotics is increasingly used to improve enterprise, industrial, and military automation. In addition, robots are finding their way into more consumer use cases as the general public’s concerns fade and acceptance grows in terms of benefits versus risks. While many consumer applications continue to be largely lifestyle oriented, enterprise, industrial and military organizations utilize both land-based and aerial robots are used for various repetitive, tedious, and/or dangerous tasks. Adoption and usage is anticipated to rapidly increase with improvements to artificial intelligence, robotic form factors and fitness for use, cloud computing and related business models, such as robotics as a service.

This research evaluates the Cloud Robotics market including technologies, companies, strategies, use cases, and solutions. The report provides global and regional forecasts for Cloud Robotics apps, services, and components from 2018 to 2023. Forecasts include the market outlook for Cloud Services support of Cloud Robotics including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS), and Robotics as a Service (RaaS). Forecasting for Cloud Robotics by deployment model is also included covering Public Cloud, Private Cloud, Hybrid Cloud, and Community Cloud.

This research also evaluates the market for robotics equipment, components, solutions, applications, and services for industrial, enterprise, military, and consumer markets. It includes detailed forecasts for robotics by robot type, components, capabilities, solutions, and connectivity for 2018 to 2023. It also includes quantitative analysis with forecasts covering AI technology and systems by type, use case, application, and industry vertical.

Forecasts also cover each major market sector including consumer, enterprise, industrial, and government. This research also evaluates commercial and military drones market including enabling technologies, solutions, applications and services. The report assesses the market outlook and provides detailed forecasts for revenue and deployment globally, regionally, and within major countries through 2025.


Smart Cities Market: Technologies, Solutions, and Outlook for Applications and Services 2018 – 2023

Published: November 2018; Pages: 195

Pricing by License: Single-user License: $ 1,995 USD; Multi User (Up to 5 Users):  $ 2,995 USD; Enterprise Site License:  $ 3,995 USD; Global Enterprise License:   $4,995 USD

Smart cities represent a combination of solutions deployed in an urban environment to transform the administration and support of living and working environments. Accordingly, Information and Communications Technologies (ICT) are transforming at a rapid rate, driven by urbanization, industrialization of emerging economies, and the specific needs of various smart city initiatives. Smart city development is emerging as a focal point for growth drivers in several key ICT areas including: Artificial Intelligence, Internet of Things, Connected Devices, Broadband Wireless, Cloud Computing, Big Data and Analytics.

Sustainable smart city technology deployments depend upon careful planning and execution as well as monitoring and adjustments as necessary. For example, feature/functionality must be blended to work efficiently across many different industry verticals as smart city address the needs of disparate market segments with multiple overlapping and sometimes mutually exclusive requirements. This will stimulate the need for both cross-industry coordination as well as orchestration of many different capabilities across several important technologies.

This report evaluates the smart cities market including leading vendors and strategies (such as a single vendor centric approach), infrastructure, solutions, applications and services. The report analyzes market factors driving solution adoption, technology readiness and fitness for use, and other considerations. The report assesses the aforementioned factors to derive penetration and revenue to forecast market value for the period of 2018 – 2023. The report also analyses the role of technology accelerating digital transformation including AI, edge processing, 5G deployment and usage, and advanced data analytics.


Quantum Computing Market: Companies, Solutions, Market Outlook and Forecasts 2018 – 2023

Published: October 2018; Pages: 196

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Quantum computing relies upon quantum theory, which deals with physical phenomena at the nano-scale.  One of the most important aspects of quantum computing is the quantum bit (Qubit), a unit of quantum information that exists in two states (horizontal and vertical polarization) at the same time, thanks to the superposition principle of quantum physics.

While quantum computing does not utilize a faster clock-speed than classical computing, it is much faster than traditional computing infrastructure for solving certain problems as quantum computers can handle exponentially larger data sets. Accordingly, quantum computing is well-positioned to support certain industry verticals and solve certain problems such as cybersecurity and cryptocurrencies that rely upon prime factoring. Current classical computing technologies would take an inordinate amount of time to break-down prime factors to support cryptology and blockchain technology.

Currently, quantum computers are purpose-built (e.g., not general purpose as classical HPC platforms), and are built with specific problem solving in mind and computational models such as optimizing unstructured databases search via Grover’s Algorithm or identifying prime factors via Shor’s Algorithm. These two examples represent quantum computers built to support big data analytics and cryptography respectively. Unlike general-purpose computers that may be easily updated via software, quantum computers must be adapted to new algorithms to solve different types of problems such as unstructured search vs. prime factoring. In other words, a completely different quantum computer would be required to optimize big data analytics than one used to support cryptocurrency or cybersecurity.

This report assesses the technology, companies/organizations, R&D efforts, and potential solutions facilitated by quantum computing. It also evaluates the impact of quantum computing upon other major technologies and solution areas including AI, chipsets, edge computing, blockchain, IoT, big data analytics, and smart cities. The report provides global and regional forecasts as well the outlook for quantum computing impact on hardware, software, applications, and services from 2018 to 2023.


Artificial Intelligence in Big Data Analytics and IoT: Market for Data Capture, Information and Decision Support Services 2018 – 2023

Published: September 2018; Pages: 264

Pricing: Single-user License:  $ 1,995 USD; Multi User (Up to 5 Users):  $ 2,995 USD; Site License:  $ 3,995 USD; Global Site License:  $ 4,995 USD

The Internet of Things (IoT) encompasses consumer, enterprise, and industrial market segments. Each of these markets has very unique needs in terms of infrastructure, devices, systems, and processes. One thing they all have in common is that they each produce massive amounts of data, most of which is of the unstructured variety, requiring Big Data technologies for management. Advanced analytics provide the ability to make raw data meaningful and useful as information for decision-making purposes.

Artificial Intelligence (AI) further enhances the ability for Big Data Analytics and IoT platforms to provide value to each of these market segments. The use of AI for decision making in IoT and data analytics will be crucial for efficient and effective decision making, especially in the area of streaming data and real-time analytics associated with edge computing networks. Real-time data will be a key value proposition for all use cases, segments, and solutions. The ability to capture streaming data, determine valuable attributes, and make decisions in real-time will add an entirely new dimension to service logic. In many cases, the data itself, and actionable information will be the service.

This report evaluates various AI technologies and their use relative to analytics solutions within the rapidly growing enterprise and industrial data arena. The report assesses emerging business models, leading companies, and solutions. The report also analyzes how different forms of AI may be best used for problem solving. The report also evaluates the market for AI in IoT networks and systems. The report provides forecasting for unit growth and revenue for both analytics and IoT from 2018 – 2023.


Industrial Convergence: 5G and Mobile Edge Computing, Artificial Intelligence, Data Analytics, and Internet of Things

Published: August 2018; Pages: 957

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There is an ongoing convergence of five key technologies that are poised to transform the Information and Communications Technology (ICT) ecosystem. Those technologies are Fifth Generation (5G) cellular, Artificial Intelligence (AI), Cloud Computing (including Mobile Edge Computing), Data Analytics, and the Internet of Things (IoT). Each of these technologies will have a huge impact in their own right, both on ICT as well as on all major industry verticals that depend on telecom and IT services. However, the combination of these technologies is poised to create opportunities to significantly enhance user experiences for communications, applications, digital content, and commerce.

AI is increasingly integrated in many areas including Internet search, entertainment, commerce applications, content optimization, and robotics. Leveraging various technologies such as directional antennas, millimeter wave RF, and edge computing solutions, 5G network provides much higher data rates (in a range of several gigabits per second) as compared to 4G/LTE. Equally important, 5G will provide ultra-low latency (less than 1 millisecond delay) required for certain portable or mobile apps and services such as industrial automation, robotics, haptic Internet, and virtual reality. The management of unstructured data (e.g., Big Data), the leveraging of analytics tools to derive value, and the integration between Cloud, Internet of Things (IoT), and enterprise operational technology are key focus areas for large companies across virtually every industry vertical.

This IoT research assesses 5G technologies and solutions in support of IoT.  This IoT research also analyzes the impact of 5G in IoT across infrastructure components including hardware, processors, embedded devices, software, and cloud-based service platforms.  This research also assesses the prospects for 5G IoT across all major industry verticals.  The report includes detailed forecasts covering the aforementioned areas for the period 2020 to 2025. This research also evaluates IoT edge computing via Multi-access Edge Computing (MEC) technology, architecture and building blocks, ecosystem, market drivers, applications, solutions, and deployment challenges. The report also analyzes MEC industry initiatives, leading companies, and solutions. The report includes a market assessment and forecast for MEC users and MEC revenue globally, regionally, and within the enterprise market for years 2017 to 2022. Forecasts include MEC infrastructure (equipment, platforms, software, APIs, and services).

This research also provides an in-depth assessment of the global Big Data market, including business case issues/analysis, application use cases, vendor landscape, value chain analysis, and a quantitative assessment of the industry with forecasting from 2018 to 2023.  This report also evaluates the components of Big Data infrastructure and security framework. This research also represents the most comprehensive research covering core IoT hardware, software, and firmware as well as supporting technologies such as Artificial Intelligence and Mobile Edge Computing.   The report evaluates leading vendors, products, and services offerings.  The quantitative portion of the report provides detailed forecasts for the global and regional IoT technology market for 2018 to 2023.  The report also includes specific industry recommendations in key areas such as artificial intelligence hardware, software and services.