Report Ocean has released a research study titled “Edge AI Software Market” This study offers precise economic forecasts, global assessments, and country-level insights. It provides a comprehensive view of the competitive market and includes an in-depth supply chain analysis to identify significant industry changes. The study explores the current market status, anticipated future growth, technological advancements, investment opportunities, market economics, and financial data. It thoroughly examines the market and offers insights based on a SWOT analysis of the industry.
The global edge AI software market held a market value of USD 1,459.8 Million in 2021 and is projected to reach USD 8,049.8 Million by the year 2027. The market is anticipated to register a CAGR of 35.9% during the forecast period.Edge AI is the disposition of artificial intelligence applications in devices all over the physical world. The AI computation has to be done near the user at the edge of the network, near to the location of the data, rather than centrally in a cloud computing facility or even a private data center.The market is set to boom at a double-digit growth rate owing to the increased advancements in AI-powered IoT in smart applications. The increased use of edge AI software in the 5G network industry also fuels the growth rate of the market.
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On the other hand, the data privacy compliance standards are not proper in all regions which hamper the market growth to a limited extent. Moreover, AI and machine learning continue to develop, yet many AI disruptors lack the capacity to process complex AI, machine learning algorithms. Thus, such elements hinder the market growth.Growth Influencers:Advancements in AI-powered IoT (Internet of Things) for Intelligent Systems and Smart ApplicationsThe extensive implementation of the Internet of Things has powered the detonation of big data. With the swift ability to amass data in every aspect of a business, the edge AI software are playing a prominent role. The AI-powered IoT software are used from industrial sensors, robots, to smart cameras. Thus, the increasing advancements fuel the market growth.Use of Edge AI computing in 5G network
key player
Anagog Ltd., Alef Edge, Inc., AWS, Bragi.Com, Azion Technologies, Chaos Prime, Inc., Foghorn Systems, Inc., Clearblade, Inc., Google, IBM, Gorilla Technology Group, Inc., Imagimob, TACT.AI, Nutanix, Microsoft, Sixsq Sarl, Synaptics, Octonion, TIBCO Software, and Veea Inc, among others.
MARKET OVERVIEW
The Edge AI Software market represents a segment within the artificial intelligence (AI) industry that focuses on deploying AI algorithms and models directly on edge devices, such as smartphones, IoT devices, edge servers, and other edge computing infrastructure. This approach enables data processing, analysis, and AI-driven decision-making closer to the source of data generation. Here’s a deep analysis of the Edge AI Software market within the industry:
Market Overview:
Growth Trajectory: The Edge AI Software market has witnessed substantial growth due to the increasing demand for real-time data processing, reduced latency, and improved privacy and security offered by edge computing.
Market Size: The market has expanded significantly as industries adopt edge AI solutions to enable on-device intelligence and decision-making capabilities.
Market Players: Various software companies, AI startups, cloud service providers, and chip manufacturers contribute to the development and deployment of Edge AI Software.
Key Features and Functionalities:
On-Device AI Processing: Software solutions enabling the deployment of machine learning models, inference engines, and AI algorithms directly on edge devices without relying solely on cloud-based processing.
Low Latency and Real-time Insights: Edge AI software allows for faster data analysis, immediate decision-making, and reduced dependence on constant internet connectivity or cloud resources.
Edge Device Optimization: Tools optimizing AI models for resource-constrained edge devices, ensuring efficient use of processing power, memory, and energy consumption.
Industry Applications:
Internet of Things (IoT): Edge AI software used in IoT devices for real-time monitoring, predictive maintenance, anomaly detection, and smart automation in various industries like manufacturing, healthcare, and smart cities.
Autonomous Vehicles: Deployment of edge AI solutions for object detection, image recognition, decision-making, and real-time analysis in autonomous vehicles and driver assistance systems.
Retail and Consumer Electronics: AI-enabled edge devices for personalized recommendations, smart assistants, facial recognition, and inventory management.
Market Drivers:
Real-time Decision Making: Demand for instant decision-making capabilities and reduced latency in applications requiring quick responses, such as critical infrastructure, healthcare, and autonomous systems.
Privacy and Security: Concerns over data privacy, security, and compliance driving the need for processing sensitive data directly on edge devices without transmitting it to centralized cloud servers.
Bandwidth and Connectivity: Optimization of network bandwidth and reduced reliance on continuous connectivity, especially in remote or bandwidth-constrained environments.
Challenges and Opportunities:
Resource Constraints: Challenges in optimizing and deploying complex AI models on resource-limited edge devices while maintaining accuracy and performance.
Standardization and Compatibility: Opportunities for standardizing edge AI software frameworks, interoperability, and compatibility across different hardware platforms and vendors.
Edge AI Ecosystem Development: Opportunities for collaborations among software developers, hardware manufacturers, and AI solution providers to develop comprehensive edge AI ecosystems.
Industry Trends:
Federated Learning: Adoption of federated learning techniques enabling model training across distributed edge devices while preserving data privacy and security.
Continuous Model Optimization: Development of AI software allowing for continuous model updates, optimization, and learning from real-time data at the edge.
AI at the Network Edge: Integration of AI capabilities within edge networking equipment to enable intelligent edge routing, traffic optimization, and network analytics.
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Market Dynamics:
Competitive Landscape: Presence of various software companies and cloud service providers offering edge AI solutions, driving competition and innovation in the market.
Integration with Edge Infrastructure: Collaboration between AI software developers and hardware manufacturers to create integrated solutions optimized for edge computing environments.
Regulatory Compliance and Standards: Adherence to regulatory requirements and industry standards for data privacy, security, and ethical AI practices in edge computing.
Future Outlook:
Continued Growth: The Edge AI Software market is poised for continuous growth as industries increasingly leverage edge computing for real-time data analysis and decision-making.
AI Customization for Edge Devices: Expectations of advancements in AI software allowing for customization and optimization of models specifically tailored for diverse edge devices and applications.
Edge-to-Cloud Synergy: Integration and orchestration of AI workloads between edge devices and cloud infrastructure for seamless data processing and insights across the entire network
Segments Overview:The global edge AI software market is segmented into component, data source, application, and end users.By Component,? Softwareo Software Toolso Platform? Serviceso Training and Consulting Serviceso System Integration and Testingo Support and Maintenance
The software segment held the largest market share of more than 80% in 2021. On the basis of the software segment, the platform sub-segment is expected to hold an opportunity of more than USD 3,500 Million during 2021 to 2027.
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By Data Source,? Biometric Data? Mobile Data? Sensor Data? Speech Recognition? Video and Image RecognitionThe biometric data segment is anticipated to hold the highest growth rate of 36.6%. on the other hand, the sensor data held the largest market share of more than 25% in 2021.
By Application,? Access Control? Autonomous Vehicles? Energy Management? Predictive Maintenance? Remote Monitoring? Telemetry? Video Surveillance? OthersThe energy management segment held the largest market share of more than 20% in 2021. On the other hand, the remote monitoring segment is projected to hold an opportunity of more than USD 900 Million during 2021 to 2027.
By End Users,? Advanced Industries? Banking and Insurance? Chemicals and Agriculture? Consumer? Cross-Vertical? Energy and Materials? Healthcare? Infrastructure? Media and Entertainment? Public Sector and Utilities? Retail? Travel, Transport and LogisticsThe healthcare segment held the highest growth rate of 37.2%. Moreover, the travel, transport and logistics segment held the largest market share of more than 20% in 2021.
Regional Overview
By region, the global edge AI software market is divided into North America, Europe, Asia Pacific, Middle East & Africa, and South America.
Executive Summary
Introduction
Methodology
Market Overview
Market Analysis
Market Size and Forecast
Market Trends
Market Dynamics
Market Segmentation
Competitive Landscape
Competitive Scenario
Key Players
Regional Analysis
Regional Market Overview
Market Size and Forecast by Region
Product/Service Analysis
Product/Service Overview
Market Size and Forecast by Product/Service
End-User Analysis
End-User Overview
Market Size and Forecast by End-User
Industry Structure
Key Findings and Recommendations
Conclusion
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