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Edge AI Software Market by Component (Solutions and Services), Data Source (Video and Image Recognition, Speech Recognition, Biometric Data, Sensor Data, and Mobile Data), Application (Autonomous Vehicles, Access Management, Video Surveillance, Remote Monitoring & Predictive Maintenance, Energy Management, and Others), and Industry Vertical (Manufacturing, Automotive, Telecom, Healthcare, Government & Public, and Others): Global Opportunity Analysis and Industry Forecast, 2019–2026

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Sep 2019 | 29 Views
 
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Edge AI Software Market Outlook: 2026

Edge AI software consists of AI algorithms that process data and analyze at the edge, end-devices, or locally on a hardware device. In simple terms, AI algorithms are implemented directly on a device that collects data i.e. sensor data or signals. For example, augmented reality glasses, drones, or cameras. The need for data processing in terminal equipment or end-device proves to be particularly important when the speed of data processing is crucial. Edge AI software is widely used where even milliseconds of data transmission delay is not affordable, sensitive data should not leave the device, and low power consumption is a necessity; as edge AI does not send data to the cloud regularly, which, in turn, automatically minimizes the use of batteries. A detailed example of edge AI software is an elderly person wearing a watch that can detect falls. The Edge AI system use accelerometer data in real time as input to the AI algorithm that detects the fall. These factors are expected to boost adoption of the edge AI software, this, supports the global edge AI software market growth during the forecast period.

Rise in need for scalability, high connectivity, low power consumption, and reduced latency among diverse industries is among many driving factors that increase demand for edge infrastructure in the form of micro data centers or distributed computing architecture. Rapid growth in the number of intelligent applications and smart devices and the rise in demand for device-side computation are also anticipated to boost the growth of the edge AI software market. However, security and privacy concerns associated to edge AI solutions restrains the growth of the edge AI software market. Interoperability issues result into slow adoption of edge AI software, which, in turn, hinders the growth of the edge AI software market. Furthermore, key opportunity in the global edge AI software market is emergence of the 5G networks, which is proliferating the adoption of edge AI software among IT and telecommunications industries.

The market is segmented into component, data source, application, industry vertical, and region. By component, it is bifurcated into solutions and services. By solutions, the market is further sub segmented into platform and software tools. By services, the market is further sub segmented into training & consulting services, system integration & testing, and support & maintenance. In terms of data source, it is classified into video and image recognition, speech recognition, biometric data, sensor data, and mobile data. By application, it is categorized into autonomous vehicles, access management, video surveillance, remote monitoring & predictive maintenance, energy management, and others. By industry vertical, it is divided into manufacturing, automotive, telecom, healthcare, government & public, and others. Region-wise, it is analyzed across North America, Europe, Asia-Pacific, and LAMEA.

The global edge AI software market analysis includes key players such as Xnor.AI, Anagog Ltd, Veea, Inc., Invision AI, Octonion SA., Swim.AI, Inc., Imagimob AB, Nutanix, Inc., IBM Corporation, TIBCO Software, Inc., Foghorn Systems, Microsoft Corporation, and Amazon Web Services, Inc. These players have adopted various strategies to increase their market penetration and strengthen their position in the industry. Current and future edge AI software market trends are outlined to determine the overall attractiveness of the market.

KEY BENEFITS FOR STAKEHOLDERS

  • The study provides an in-depth analysis of the global edge AI software market share with current trends and future estimations to elucidate the imminent investment pockets.
  • Information about key drivers, restraints, and opportunities and their impact analysis on the global edge AI software market size is provided.
  • Porter’s five forces analysis illustrates the potency of buyers and suppliers operating in the global edge AI software industry.
  • The quantitative analysis of the global edge AI software market from 2018–2026 provided to determine the market potential. 

KEY MARKET SEGMENTS

By Component

  • Solutions
  • Services

By Data Source

  • Video and Image Recognition
  • Speech Recognition
  • Biometric Data
  • Sensor Data
  • Mobile Data

By Application

  • Autonomous Vehicles 
  • Access Management 
  • Video Surveillance 
  • Remote Monitoring and Predictive Maintenance 
  • Energy Management 
  • Others

By Industry Vertical

  • Manufacturing 
  • Automotive
  • Telecom
  • Healthcare
  • Government and Public
  • Others

By Region

  • North America
    • U.S.
    • Canada
  • Europe 
    • UK
    • Germany 
    • France
    • Rest of Europe
  • Asia-Pacific 
    • China
    • India
    • Japan
    • Singapore
    • Rest of Asia-Pacific
  • LAMEA
    • Latin America 
    • Middle East
    • Africa

KEY MARKET PLAYERS 

  • Xnor.AI 
  • Anagog Ltd
  • Veea, Inc.
  • Invision AI
  • Octonion SA.
  • Swim.AI, Inc.
  • Imagimob AB
  • Nutanix, Inc.
  • IBM Corporation
  • TIBCO Software Inc
  • Foghorn Systems 
  • Microsoft Corporation
  • Amazon Web Services, Inc.
 

    

 
 
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