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RIS（可重构智慧表面）的全球市场（2025-2035）
市场调查报告书
商品编码
1565350

RIS（可重构智慧表面）的全球市场（2025-2035）

The Global Market for Reconfigurable Intelligent Surfaces (RIS) 2025-2035
出版日期: | 出版商: Future Markets, Inc. | 英文 172 Pages, 95 Tables, 46 Figures | 订单完成后即时交付

价格

RIS，也称为IRS（智慧反射表面）或软体控制的超表面，是一种由许多小型被动元件组成的人造结构，可以透过电子控制来操纵电磁波。这些表面可以反射、折射、吸收和聚焦接收到的讯号到所需的方向，有效地塑造无线电传播环境。随着超材料的最新进展，RIS 已成为未来 6G 无线通讯的一项有前途的技术。凭藉高阵列增益、低成本和低功耗的优势，RIS可望大幅扩大讯号覆盖范围，提高系统处理能力，并提高能源效率。

RIS 技术在电磁波操控方面提供了突破性的能力，从而提高了无线网路的覆盖范围、处理能力和能源效率。随着 5G 网路的扩展和 6G 发展的加速，RIS 有望在克服当前无线通讯的限制方面发挥关键作用。典型应用包括通讯、智慧城市、工业物联网、医疗、汽车、航空航太和消费性电子产品。对高速、低延迟通讯的需求不断增长、物联网的日益普及以及对节能无线解决方案的需求推动了市场的发展。然而，课题包括初始成本高、大规模部署的技术复杂性以及标准化问题。

本报告针对全球RIS（可重构智慧表面）市场进行研究和分析，并提供市场规模和成长预测、技术细节、应用领域、竞争格局和未来前景等资讯。

目录

第 1 章执行摘要

  • RIS（可重构智慧表面）概述
  • 主要市场推动因素与课题
  • 科技与市场趋势
  • 超材料是 RIS 的关键
  • 市场规模与成长预测
  • 竞争格局概览
  • 未来的前景与机遇

第 2 章简介

  • 技术概述
  • 系统架构
  • 现代无线通讯的重要性
  • 相对于传统无线技术的优势
  • 当前的限制与课题
  • 与其他智慧电磁 (EM) 设备的比较

第3章RIS技术

  • 超表面
  • 基于 LCD 的 RIS
  • 基于 MEMS 的 RIS
  • 基于变容二极体的 RIS
  • 基于 PIN 二极体的 RIS
  • 其他材料
  • RIS技术比较

第 4 章无线通讯系统的风险

  • 5G
  • 6G 或更高版本
  • MIMO系统和RIS
  • 波束成形和 RIS
  • 无线网路的能源效率

第五章市场与应用

  • 通讯
  • 智慧城市、物联网
  • 工业物联网、工业 4.0
  • 医疗用途
  • 汽车、交通
  • 航空航太、国防
  • 智慧家庭、消费性电子产品

第6章市场分析与趋势

  • 世界市场规模与成长预测
    • 市场区隔：依技术
    • 市场区隔：依市场
    • 市场区隔：依地区
  • 主要市场推动因素
    • 对高速、低延迟通讯的需求不断成长
    • 扩大采用物联网和智慧型设备
    • 5G 和 6G 技术的进步
    • 需要节能无线解决方案
    • 其他司机
  • 市场课题与障碍
    • 初始实施成本较高
    • 大规模部署的技术复杂性
    • 标准化和互通性问题
    • 监管和合规课题
    • 其他课题与障碍
  • 新兴市场机遇
    • 与边缘运算集成
    • 用于卫星和太空通讯的 RIS
    • RIS 先进材料
    • 人工智慧与机器学习的集成
    • 量子RIS概念
    • 认知 RIS
    • 自配置、自修復 RIS
    • 区块链整合确保安全通信
  • 未来展望
    • 6G之后的RIS
    • 全息通讯
    • 天基 RIS 网络
    • RIS 控制中的人工智慧和机器学习
    • 用于太赫兹和光无线通讯的RIS
    • 大规模 RIS 部署的生物和健康影响

第 7 章标准化与监管环境

  • 与 RIS 相关的现行标准
  • 频率分配与管理

第 8 章环境与永续性考量

  • 支援 RIS 的网路的能源效率
  • RIS技术的生命週期评估
  • 电子废弃物管理与回收
  • 永续生产方法
  • RIS 在智慧电网和能源管理中的作用
  • 大规模 RIS 部署对环境的影响

第 9 章课题与限制

  • RIS 实施中的技术课题
  • 扩大生产规模、降低成本
  • 与现有基础设施集成
  • 复杂环境下的效能
  • 安全与隐私问题

第10章公司简介（20家公司简介）

第11章附录

第 12 章参考文献

RIS, also known as Intelligent Reflecting Surfaces (IRS) or software-controlled metasurfaces, are artificial structures composed of a large number of small, passive elements that can be electronically controlled to manipulate electromagnetic waves. These surfaces can reflect, refract, absorb, or focus incoming signals in desired directions, effectively shaping the wireless propagation environment. Due to recent advances in metamaterials, Reconfigurable Intelligent Surface (RIS) has emerged as a promising technology for future 6G wireless communications. Benefiting from its high array gain, low cost, and low power consumption, RISs are expected to greatly enlarge signal coverage, improve system capacity, and increase energy efficiency.

RIS technology offers revolutionary capabilities in manipulating electromagnetic waves, enabling enhanced coverage, capacity, and energy efficiency in wireless networks. As 5G networks expand and 6G development accelerates, RIS is expected to play a crucial role in overcoming current limitations in wireless communications. Key applications span telecommunications, smart cities, Industrial IoT, healthcare, automotive, aerospace, and consumer electronics. The market is driven by increasing demand for high-speed, low-latency communications, growth in IoT adoption, and the need for energy-efficient wireless solutions. However, challenges include high initial costs, technical complexities in large-scale deployment, and standardization issues.

Report contents include:

  • Market Size and Growth Projections: Detailed forecasts of the RIS market size and growth rate from 2025 to 2035, segmented by technology type, application, and geography.
  • Technology Deep Dive: Comprehensive analysis of various RIS technologies, including metasurfaces, liquid crystal-based RIS, MEMS-based RIS, and emerging approaches.
  • Application Landscape:Exploration of key application areas such as 5G/6G networks, IoT, smart cities, autonomous vehicles, and aerospace communications.
  • Competitive Landscape: Profiles of leading companies and emerging players in the RIS space, including their technologies, strategies, and market positioning. Companies profiled include Alcan Systems, Alphacore Inc., Edgehog Advanced Technologies, Evolv Technologies Inc., Fractal Antenna Systems Inc., Greenerwave, Huawei, Kymeta Corporation, Leadoptik Inc., Lumotive, META, Metaboards Limited, Metawave Corporation, Nokia, NTT DOCOMO, Pivotal Commware Inc., SK Telecom, Teraview Limited, and ZTE Corporation.
  • Future Outlook: Assessment of emerging trends, potential disruptions, and long-term prospects for RIS technology.
  • Developments in RIS technology, including:
    • Integration with AI and machine learning for adaptive control
    • Quantum RIS concepts pushing the boundaries of performance
    • Self-configuring and self-healing RIS for enhanced reliability
    • Holographic radio and terahertz communications enabled by RIS
  • Market Drivers and Opportunities
  • Challenges and Market Dynamics
  • Technology Benchmarking and Performance Analysis
  • Comprehensive comparison of different RIS technologies.
  • Integration with Wireless Communication Systems.
  • Environmental and Sustainability Considerations.
  • Standardization and Regulatory Landscape.

TABLE OF CONTENTS

1. EXECUTIVE SUMMARY

  • 1.1. Overview of Reconfigurable Intelligent Surfaces (RIS)
  • 1.2. Key Market Drivers and Challenges
  • 1.3. Technology and Market Trends
  • 1.4. Metamaterials key to RIS
  • 1.5. Market Size and Growth Projections
  • 1.6. Competitive Landscape Overview
  • 1.7. Future Outlook and Opportunities

2. INTRODUCTION

  • 2.1. Technology overview
    • 2.1.1. Key features and functionality
    • 2.1.2. Frequencies
    • 2.1.3. Physics of Electromagnetic Wave Manipulation
      • 2.1.3.1. Reflection
      • 2.1.3.2. Refraction
      • 2.1.3.3. Diffraction
      • 2.1.3.4. Absorption
    • 2.1.4. RIS Operating Principles
      • 2.1.4.1. Passive RIS
      • 2.1.4.2. Active RIS
      • 2.1.4.3. Hybrid RIS
    • 2.1.5. Key Performance Parameters
      • 2.1.5.1. Reflection Coefficient
      • 2.1.5.2. Phase Shift Range
      • 2.1.5.3. Bandwidth
      • 2.1.5.4. Power Consumption
      • 2.1.5.5. Reconfiguration Speed
    • 2.1.6. Design Considerations for RIS
      • 2.1.6.1. Surface Element Design
      • 2.1.6.2. Array Configuration
      • 2.1.6.3. Control Mechanisms
      • 2.1.6.4. Integration with Existing Infrastructure
  • 2.2. System Architecture
  • 2.3. Importance in Modern Wireless Communications
  • 2.4. Advantages Over Traditional Wireless Technologies
  • 2.5. Current Limitations and Challenges
  • 2.6. Comparison with Other Smart Electromagnetic (EM) Devices

3. RIS TECHNOLOGIES

  • 3.1. Metasurfaces
    • 3.1.1. Principles of Metasurfaces
    • 3.1.2. Types of Metasurfaces
      • 3.1.2.1. Meta-Lens
      • 3.1.2.2. Metasurface holograms
      • 3.1.2.3. Flexible metasurfaces
    • 3.1.3. Fabrication Techniques
    • 3.1.4. Characteristics
  • 3.2. Liquid Crystal-based RIS
    • 3.2.1. Operating Principles
    • 3.2.2. Advantages and Limitations
  • 3.3. MEMS-based RIS
    • 3.3.1. MEMS Technology Overview
    • 3.3.2. Design and Fabrication
    • 3.3.3. Performance Metrics
  • 3.4. Varactor Diode-based RIS
    • 3.4.1. Overview
  • 3.5. PIN Diode-based RIS
    • 3.5.1. Overview
  • 3.6. Other Materials
    • 3.6.1. Ferroelectric materials
    • 3.6.2. Phase Change Materials
    • 3.6.3. Graphene
  • 3.7. Comparison of RIS Technologies
    • 3.7.1. Performance Metrics
    • 3.7.2. Cost Analysis
    • 3.7.3. Scalability and Manufacturing Considerations

4. RIS IN WIRELESS COMMUNICATION SYSTEMS

  • 4.1. 5G
    • 4.1.1. Overview
    • 4.1.2. Market drivers
      • 4.1.2.1. Coverage Enhancement Needs
      • 4.1.2.2. Energy Efficiency Requirements
      • 4.1.2.3. Capacity Improvement Demands
      • 4.1.2.4. Cost Optimization Goals
    • 4.1.3. Applications
    • 4.1.4. RIS operation phases
    • 4.1.5. Functionalities of RIS
    • 4.1.6. RIS prototypes
    • 4.1.7. 5G Network Requirements
    • 4.1.8. RIS Role in 5G Infrastructure
    • 4.1.9. Integration with 5G Networks
      • 4.1.9.1. Network Integration Strategies
      • 4.1.9.2. Channel Modeling
      • 4.1.9.3. Signal Processing
      • 4.1.9.4. Integration Challenges and Solutions
    • 4.1.10. Performance Enhancement
      • 4.1.10.1. Coverage Optimization
      • 4.1.10.2. Capacity Enhancement
      • 4.1.10.3. Energy Efficiency
    • 4.1.11. Advanced Applications
      • 4.1.11.1. mmWave Communications
      • 4.1.11.2. Massive MIMO Systems
      • 4.1.11.3. IoT Applications
    • 4.1.12. Implementation Challenges
      • 4.1.12.1. Technical Challenges
      • 4.1.12.2. Standardization
    • 4.1.13. Future Directions
      • 4.1.13.1. Hardware Advancements
      • 4.1.13.2. Control Systems
      • 4.1.13.3. Integration Capabilities
      • 4.1.13.4. Performance Enhancement
    • 4.1.14. Market and technology roadmap
  • 4.2. 6G and Beyond
    • 4.2.1. 6G Reconfigurable intelligent surfaces and metamaterials opportunities
    • 4.2.2. RIS materials applications
    • 4.2.3. RIS costs in volume
    • 4.2.4. RIS formulations
    • 4.2.5. RIS in Terahertz Communications
    • 4.2.6. Holographic Radio
    • 4.2.7. Intelligent Reflecting Surfaces for Satellite Communications
  • 4.3. MIMO Systems and RIS
    • 4.3.1. RIS-assisted MIMO
    • 4.3.2. RIS-based Massive MIMO
    • 4.3.3. Performance Enhancements and Challenges
  • 4.4. Beamforming and RIS
    • 4.4.1. Passive Beamforming
    • 4.4.2. Hybrid Beamforming with RIS
    • 4.4.3. Adaptive Beamforming Techniques
  • 4.5. Energy Efficiency in Wireless Networks
    • 4.5.1. RIS for Green Communications
    • 4.5.2. Energy Harvesting with RIS

5. MARKET AND APPLICATIONS

  • 5.1. Telecommunications
    • 5.1.1. Coverage Enhancement
    • 5.1.2. Capacity Improvement
    • 5.1.3. Interference Mitigation
    • 5.1.4. Market forecast
  • 5.2. Smart Cities and IoT
    • 5.2.1. Urban Environment Monitoring
    • 5.2.2. Smart Transportation Systems
    • 5.2.3. Energy Management in Buildings
    • 5.2.4. Market forecast
  • 5.3. Industrial IoT and Industry 4.0
    • 5.3.1. Factory Automation
    • 5.3.2. Warehouse Management
    • 5.3.3. Process Control and Monitoring
    • 5.3.4. Market forecast
  • 5.4. Healthcare and Medical Applications
    • 5.4.1. Wireless Body Area Networks
    • 5.4.2. Remote Patient Monitoring
    • 5.4.3. Medical Imaging Enhancement
    • 5.4.4. Market forecast
  • 5.5. Automotive and Transportation
    • 5.5.1. Vehicle-to-Everything (V2X) Communications
    • 5.5.2. Autonomous Vehicles
    • 5.5.3. Intelligent Transportation Systems
    • 5.5.4. Market forecast (IoT)
  • 5.6. Aerospace and Defense
    • 5.6.1. Radar Systems Enhancement
    • 5.6.2. Secure Communications
    • 5.6.3. Stealth Technology
    • 5.6.4. UAVs
  • 5.7. Smart Home and Consumer Electronics
    • 5.7.1. In-home Wireless Coverage Optimization
    • 5.7.2. Device-to-Device Communications
    • 5.7.3. Augmented and Virtual Reality Applications

6. MARKET ANALYSIS AND TRENDS

  • 6.1. Global Market Size and Growth Projections
    • 6.1.1. Market Segmentation by Technology
    • 6.1.2. Market Segmentation by Market
    • 6.1.3. Market Segmentation by Geography
  • 6.2. Key Market Drivers
    • 6.2.1. Increasing Demand for High-Speed, Low-Latency Communications
    • 6.2.2. Growth in IoT and Smart Device Adoption
    • 6.2.3. Advancements in 5G and 6G Technologies
    • 6.2.4. Need for Energy-Efficient Wireless Solutions
    • 6.2.5. Other drivers
  • 6.3. Market Challenges and Barriers
    • 6.3.1. High Initial Implementation Costs
    • 6.3.2. Technical Complexities in Large-Scale Deployment
    • 6.3.3. Standardization and Interoperability Issues
    • 6.3.4. Regulatory and Compliance Challenges
    • 6.3.5. Other challenges and barriers
  • 6.4. Emerging Market Opportunities
    • 6.4.1. Integration with Edge Computing
    • 6.4.2. RIS for Satellite and Space Communications
    • 6.4.3. Advanced Materials for RIS
    • 6.4.4. AI and Machine Learning Integration
    • 6.4.5. Quantum RIS Concepts
    • 6.4.6. Cognitive RIS
    • 6.4.7. Self-configuring and Self-healing RIS
    • 6.4.8. Integration with Blockchain for Secure Communications
  • 6.5. Future Outlook
    • 6.5.1. RIS in 6G and Beyond
    • 6.5.2. Holographic Communications
    • 6.5.3. Space-based RIS Networks
    • 6.5.4. AI and Machine Learning in RIS Control
    • 6.5.5. RIS for Terahertz and Optical Wireless Communications
    • 6.5.6. Biological and Health Implications of Large-Scale RIS Deployment

7. STANDARDIZATION AND REGULATORY ENVIRONMENT

  • 7.1. Current Standards Related to RIS
    • 7.1.1. IEEE Standards
    • 7.1.2. 3GPP Specifications
    • 7.1.3. ETSI Standards
  • 7.2. Spectrum Allocation and Management
    • 7.2.1. Safety and Electromagnetic Compatibility Regulations
    • 7.2.2. Data Privacy and Security Considerations

8. ENVIRONMENTAL AND SUSTAINABILITY CONSIDERATIONS

  • 8.1. Energy Efficiency of RIS-enabled Networks
  • 8.2. Life Cycle Assessment of RIS Technologies
  • 8.3. E-waste Management and Recycling
  • 8.4. Sustainable Manufacturing Practices
  • 8.5. RIS Role in Smart Grid and Energy Management
  • 8.6. Environmental Impact of Large-Scale RIS Deployment

9. CHALLENGES AND LIMITATIONS

  • 9.1. Technical Challenges in RIS Implementation
  • 9.2. Scaling Up Production and Cost Reduction
  • 9.3. Integration with Existing Infrastructure
  • 9.4. Performance in Complex Environments
  • 9.5. Security and Privacy Concerns

10. COMPANY PROFILES (20 company profiles)

11. APPENDICES

  • 11.1. Glossary of Terms
  • 11.2. List of Abbreviations
  • 11.3. Research Methodology

12. REFERENCES

List of Tables

  • Table 1. Key Market Drivers and Challenges in RIS
  • Table 2. Reconfigurable Intelligent Surfaces (RIS) Technology and Market Trends
  • Table 3. Future Outlook and Opportunities in RIS
  • Table 4. Overview of different RIS types
  • Table 5. RIS operation phases
  • Table 6. RIS Hardware
  • Table 7. Comparison of different RIS techniques
  • Table 8. RIS functionalities
  • Table 9. Challenges for fully functionalized RIS environments
  • Table 10. Comparison of Reflection Coefficient Across Different RIS Technologies
  • Table 11. Benchmarking of Reconfigurable Intelligent Surfaces (RIS) types
  • Table 12. Comparison of Key Performance Metrics for Different RIS Technologies
  • Table 13.Comparison of Phase Shift Range Across Different RIS Technologies
  • Table 14. Bandwidth and Frequency Ranges for Various RIS Technologies
  • Table 15. Power Consumption Comparison of RIS Technologies
  • Table 16. Energy Efficiency Comparison: RIS-enabled vs. Traditional Wireless Networks
  • Table 17. Reconfiguration Speed Comparison Across Different RIS Types
  • Table 18. Integration Considerations
  • Table 19. Advantages Over Traditional Wireless Technologies
  • Table 20. Current Limitations and Challenges
  • Table 21. RIS vs Other Smart Electromagnetic (EM) Devices
  • Table 22.Types of Metasurfaces
  • Table 23. Metasurface fabrication techniques
  • Table 24. Distinguishing between conductive and optical metamaterials
  • Table 25. Advantages and Limitations of Liquid Crystal-based RIS
  • Table 26. MEMS-based RIS Technology Performance Metrics
  • Table 27. Comparison of RIS Performance in Different Environmental Conditions
  • Table 28. Cost Analysis
  • Table 29. Market drivers for reconfigurable intelligent surfaces in 5G
  • Table 30. Coverage Enhancement Metrics
  • Table 31. Energy Efficiency Metrics
  • Table 32. Cost Optimization Metrics
  • Table 33. Reconfigurable intelligent surface (RIS) - applications in 5G
  • Table 34. RIS operation phases
  • Table 35. Functionalities of RIS
  • Table 36. RIS 5G Prototypes
  • Table 37. 5G Network Requirements
  • Table 38. RIS applications in wireless networks
  • Table 39. Network integration strategies for RIS technology
  • Table 40. Integration with Existing Infrastructure
  • Table 41. Performance Metrics in 5G Network Integration
  • Table 42. Path Loss Models
  • Table 43. Channel Estimation Techniques
  • Table 44. Multi-user Scenarios
  • Table 45. Precoding Techniques
  • Table 46. Integration Challenges and Solutions
  • Table 47. Coverage Extension Methods
  • Table 48. Indoor Coverage Solutions
  • Table 49. Capacity Enhancement
  • Table 50. Energy Efficiency
  • Table 51. Power Consumption Analysis
  • Table 52. High-Frequency Challenges
  • Table 53. RIS Solutions for mmWave
  • Table 54. Performance Analysis
  • Table 55. Implementation Challenges
  • Table 56. Technical Challenges for RIS
  • Table 57. Hardware Limitations for RIS in 5G
  • Table 58. Standardization Challenges
  • Table 59. RIS Materials Applications
  • Table 60. RIS costs in volume
  • Table 61. RIS formulations
  • Table 62. Adaptive Beamforming Techniques
  • Table 63. Global market forecast for RIS Adoption in 5G/6G Networks (2025-2035), Millions USD
  • Table 64. Urban Environment Monitoring Applications
  • Table 65. Smart Transportation Applications
  • Table 66. Energy Management Applications
  • Table 67. Global market forecast for RIS Adoption in Smart Cities and IoT (2025-2035), Millions USD
  • Table 68.Industrial IoT Applications
  • Table 69. Process Control Applications
  • Table 70. Global market forecast for RIS Adoption in Industrial IoT and Industry 4.0 Applications (2025-2035), Millions USD
  • Table 71. Wireless Body Area Networks Applications
  • Table 72. Remote Patient Monitoring Applications
  • Table 73. Global Market Forecast for RIS Adoption in Healthcare/Medical (2025-2035), Millions USD
  • Table 74.Automotive and Transportation Applications
  • Table 75. Global market forecast for RIS Adoption in Automotive and Transportation (2025-2035), Millions USD
  • Table 76. Augmented and Virtual Reality Applications
  • Table 77. Global RIS Market Size, by Technology Type, 2025-2035 (USD Million)
  • Table 78. Global RIS Market Size, by market, 2025-2035 (USD Million)
  • Table 79. Global RIS Market Size, by Region, 2025-2035 (USD Million)
  • Table 80. Applications in Satellite and Space Communications
  • Table 81.RIS Material Types and Applications
  • Table 82. Quantum RIS Concepts
  • Table 83. Biological and Health Implications
  • Table 84. Safety and Electromagnetic Compatibility Regulations
  • Table 85. Data Privacy and Security Considerations
  • Table 86. Environmental Impact Comparison: RIS vs. Traditional Wireless Infrastructure
  • Table 87. Energy Efficiency Metrics
  • Table 88. Life Cycle Assessment of RIS Technologies
  • Table 89. E-waste Management and Recycling
  • Table 90. Sustainable Manufacturing for RIS Technology
  • Table 91. Smart Grid Integration
  • Table 92. Environmental Impact of Large-Scale RIS Deployment
  • Table 93. Technical Challenges in RIS Implementation
  • Table 94. Glossary of Terms
  • Table 95. List of Abbreviations

List of Figures

  • Figure 1. A typical use case of an RIS, where it receives a signal from the transmitter and re-radiates it focused on the receiver
  • Figure 2. Basic RIS application: coverage extension in a cellular network
  • Figure 3. Comparison of different wireless systems
  • Figure 4. Schematic Diagram of a Typical RIS Structure
  • Figure 5. Intelligent reflection and refraction
  • Figure 6. Hardware architecture of RIS
  • Figure 7. Scanning electron microscope (SEM) images of several metalens antenna forms
  • Figure 8. Transparent and flexible metamaterial film developed by Sekishi Chemical
  • Figure 9. The structure of a three-layered PIN diode based 2-bit RIS panel
  • Figure 10. NTT DOCOMO transparent RIS
  • Figure 11. Meta Nanoweb-R
  • Figure 12. RIS mmWave communication
  • Figure 13. RIS in 5G Market and technology roadmap
  • Figure 14. Comparison between 5G and 6G wireless systems in terms of key-performance indicators
  • Figure 15. RIS-assisted wireless communication
  • Figure 16. RIS-enabled, self-sufficient ultra-massive 6G UM-MIMO base station design
  • Figure 17. Active and passive beamforming in RIS-assisted cell-free massive MIMO
  • Figure 18. Lumotive advanced beam steering concept
  • Figure 19. Deployment of RIS in a building for communication
  • Figure 20. RIS-assisted indoor enhancement of outdoor macro station coverage
  • Figure 21. Global market forecast for RIS Adoption in 5G/6G Networks (2025-2035), Millions USD
  • Figure 22. Global market forecast for RIS Adoption in Smart Cities and IoT (2025-2035), Millions USD
  • Figure 23. RIS-aided IoT communication
  • Figure 24. Global market forecast for RIS Adoption in IoT Applications (2025-2035), Millions USD
  • Figure 25. Global Market Forecast for RIS Adoption in Healthcare/Medical (2025-2035), Millions USD
  • Figure 26. RIS-assisted V2V communication system
  • Figure 27. RIS vehicle network communication
  • Figure 28. Global market forecast for RIS Adoption in Automotive and Transportation (2025-2035), Millions USD
  • Figure 29. PHY-Layer security issue scheme of RIS
  • Figure 30. RIS UAV communication
  • Figure 31. RIS VLC in a smart office room
  • Figure 32. Global RIS Market Size, by Technology Type, 2025-2035 (USD Million)
  • Figure 33. Global RIS Market Size, by Application, 2025-2035 (USD Million)
  • Figure 34. Global RIS Market Size, by Region, 2025-2035 (USD Million)
  • Figure 35. RIS-enabled wireless edge computing
  • Figure 36. Edgehog Advanced Technologies Omnidirectional anti-reflective coating
  • Figure 37. FM/R technology
  • Figure 38. Metablade antenna
  • Figure 39. MTenna flat panel antenna
  • Figure 40. Kymeta u8 antenna installed on a vehicle
  • Figure 41. LIDAR system for autonomous vehicles
  • Figure 42. Light-control metasurface beam-steering chips
  • Figure 43. Metaboard wireless charger
  • Figure 44. Metalenz metasurface-based optics on a chip
  • Figure 45. NTT DOCOMO transparent RIS
  • Figure 46. ZTE dynamic reconfigurable intelligent surface 2.0 product