Global Artificial Intelligence For Edge Devices Market Size By Applications, By Verticals, By Hardware, By Geographic Scope And Forecast
Published Date: August - 2024 | Publisher: MIR | No of Pages: 320 | Industry: latest updates trending Report | Format: Report available in PDF / Excel Format
Artificial Intelligence For Edge Devices Market Size And Forecast
The global Artificial Intelligence For Edge Devices Market size is valued at USD 19.11 Billion in 2023 and is projected to reach USD 48.9 Billion by 2030, growing at a CAGR of 26.7% during the forecast period 2024-2030.
Global Artificial Intelligence For Edge Devices Market Drivers
The market drivers for the Artificial Intelligence For Edge Devices Market can be influenced by various factors. These may include
Real-time and low latency processingFor applications like autonomous vehicles and industrial automation, edge devices with AI capabilities can process data locally, decreasing latency and enabling real-time decision-making.
Data security and privacyBy minimising the need to transfer sensitive data to centralised cloud servers, processing AI at the periphery can assist maintain data privacy and security.
Broadband effectivenessEdge AI makes better use of the existing bandwidth by reducing the need to transfer big amounts of data to the cloud.
Computerised DistributionEdge devices can cooperate and share AI-related activities thanks to edge AI, which is advantageous for applications like collaborative robots.
IoT and the Spread of SensorsIoT expansion and the widespread usage of sensors provide enormous volumes of data that may be handled and analysed using AI at the edge.
Industry 4.0 and Industrial AutomationIndustrial automation is made possible by AI-powered edge devices, which also allow for process optimisation, quality assurance, and predictive maintenance in smart factories.
Vehicles with autonomyAutonomous vehicles require AI at the edge because it offers real-time perception and decision-making abilities for effective and safe self-driving.
The Smart CityTo enhance the quality of urban life, edge AI is applied in smart city applications such intelligent traffic control, public safety, and trash management.
Applications in HealthcareFor early disease identification and healthcare management, AI on edge devices support wearable health devices, medical picture analysis, and remote patient monitoring.
Precision farming and agricultureEdge AI is used in precision agriculture to monitor livestock, manage crops more effectively, and increase farm productivity as a whole.
Global Artificial Intelligence For Edge Devices Market Restraints
Several factors can act as restraints or challenges for the Artificial Intelligence For Edge Devices Market. These may include
A low level of computational powerWhen opposed to cloud-based solutions, edge devices often have less computational capacity, which can limit the sophistication of AI algorithms that can be implemented locally.
Energy limitationsEnergy restrictions frequently prevent edge devices, especially battery-powered ones, from running resource-demanding AI algorithms continually.
Scaling problemsIt can be difficult to scale cutting-edge AI solutions across a large number of devices, and keeping track of upgrades and maintenance gets more difficult as the number of devices rises.
Expenses for HardwareParticularly for low-cost or resource-constrained applications, the expense of embedding AI-capable technology in edge devices can be a substantial obstacle.
Integration ObstaclesIt can be technically challenging and time-consuming to integrate AI into current edge devices and systems.
Data security and privacyData privacy and protection become a top priority as processing data at the edge can pose new security threats.
Obstacles in Regulatory and ComplianceCompliance issues for edge AI implementations can arise since different sectors of the economy and geographical areas may have unique regulatory standards for data processing.
Data Variability and QualityEdge devices could experience inconsistent data quality, and AI models might need to adjust to various data sources, which could cause performance problems.
Updating and maintenanceIt can be logistically difficult to maintain and update AI models and software on edge devices, especially when those devices are placed in remote or difficult-to-reach areas.
InteroperabilityIt can be difficult to make sure that several edge devices from various manufacturers can cooperate and communicate efficiently.
Global Artificial Intelligence For Edge Devices Market Segmentation Analysis
The Global Artificial Intelligence For Edge Devices Market is segmented based on Applications, Verticals, Hardware, and Geography.
Artificial Intelligence For Edge Devices Market, By Applications
Image and Video AnalyticsAI at the edge is used for real-time image and video processing, including surveillance, facial recognition, and object detection.
Natural Language Processing (NLP)Edge devices can process and understand spoken or written language for applications like voice assistants and chatbots.
Predictive MaintenanceAI-driven predictive maintenance solutions are used to monitor the health of industrial equipment and machinery.
Autonomous VehiclesAI at the edge is critical for self-driving cars, enabling real-time perception and decision-making.
Industrial RoboticsEdge AI powers industrial robots for tasks like automation, quality control, and collaborative robotics.
Edge Servers and GatewaysThese devices act as intermediaries between edge devices and the cloud, optimizing data processing and transmission.
Smart CamerasEdge AI is employed in smart cameras for applications like home security, retail analytics, and industrial monitoring.
Wearable DevicesAI on wearables provides health and fitness tracking, real-time notifications, and personalized insights.
AR/VR DevicesAugmented reality (AR) and virtual reality (VR) devices use edge AI for immersive experiences and real-time interactions.
Smart AppliancesEdge AI enhances the capabilities of smart appliances, such as ovens, refrigerators, and washing machines.
Artificial Intelligence For Edge Devices Market, By Verticals
Manufacturing and IndustrialEdge AI is used for quality control, predictive maintenance, and automation in manufacturing.
HealthcareAI at the edge supports remote patient monitoring, medical imaging, and wearable health devices.
AutomotiveAutonomous vehicles and advanced driver-assistance systems (ADAS) rely on edge AI.
RetailAI-powered edge devices enable personalized shopping experiences and inventory management.
Smart CitiesEdge AI is used in traffic management, public safety, and environmental monitoring.
AgricultureEdge AI supports precision agriculture and crop management.
Energy and UtilitiesEdge AI optimizes energy consumption in buildings and industrial facilities.
Consumer ElectronicsAI-enhanced smartphones, smart speakers, and other consumer electronics are common.
TelecommunicationsEdge AI improves network efficiency and enables real-time decision-making in telecom networks.
Defense and SecurityEdge AI is used in surveillance, threat detection, and security applications.
Artificial Intelligence For Edge Devices Market, By Hardware
AI AcceleratorsHardware accelerators like GPUs, TPUs, and FPGAs are used for AI inference at the edge.
Processors and MicrocontrollersSpecialized processors and microcontrollers are used in edge devices.
Cameras and SensorsEdge devices may incorporate specialized cameras and sensors for data collection.
Memory and StorageHigh-capacity memory and storage solutions are crucial for AI processing.
Artificial Intelligence For Edge Devices Market, By Geography
North AmericaMarket conditions and demand in the United States, Canada, and Mexico.
EuropeAnalysis of the Artificial Intelligence For Edge Devices Market in European countries.
Asia-PacificFocusing on countries like China, India, Japan, South Korea, and others.
Middle East and AfricaExamining market dynamics in the Middle East and African regions.
Latin AmericaCovering market trends and developments in countries across Latin America.
Key Players
The major players in the global Artificial Intelligence For Edge Devices Market include
By Applications, By Verticals, By Hardware, and By Geography.
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