Global Edge Computing Market Outlook, 2029

The tech world is witnessing a surge in the edge computing market, driven by the explosion of Internet of Things (IoT) devices and the ever-growing need for real-time data processing. This exciting market is poised for significant growth in the coming years. The ever-increasing adoption of IoT devices is a major driver. These devices generate massive amounts of data that need to be processed and analysed quickly. Traditional methods of sending this data to the cloud for processing can create delays. Edge computing provides the perfect solution by handling this data at the source, closer to where it's generated, enabling real-time insights and faster decision-making. The growing demand for cloud computing and real-time data insights is fuelling the need for edge computing solutions. Businesses across industries are increasingly reliant on real-time data to optimize operations, improve efficiency, and gain a competitive edge. Edge computing plays a crucial role in facilitating this by enabling the collection, processing, and analysis of data closer to its origin. The market itself can be categorized into three main segments: hardware, software, and services. The hardware segment, driven by the rising demand for edge devices like routers and gateways, is expected to hold the dominant position. These devices are essential for collecting and processing data at the edge. According to the research report, “Global Edge Computing Market Outlook, 2029” published by Bonafide Research, the market is anticipated to reach USD 50 Billion by 2023. Edge computing has a wide range of applications across various sectors. Smart cities are expected to be the biggest user, leveraging edge computing for real-time data processing and analysis from their extensive network of IoT devices. Imagine traffic lights that adjust based on real-time traffic flow or waste management systems optimized based on bin fullness data – these are just a few examples of how edge computing is transforming smart cities. Industrial automation, healthcare, and retail are other key areas where edge computing is making its mark, enabling real-time monitoring, predictive maintenance, and personalized customer experiences. While North America is currently leading the pack in edge computing adoption, followed by Europe and Asia Pacific, the Asia Pacific region is expected to experience the fastest growth due to its rapid adoption of IoT devices and increasing demand for cloud computing solutions. Major companies like General Electric, Amazon Web Services (AWS), Intel, Microsoft, SAP, and Huawei are at the forefront of the edge computing market, offering innovative solutions to meet the growing demand. There are, however, some challenges that need to be addressed. High-speed data processing, secure data transmission, and the need for scalable and adaptable infrastructure are key hurdles that need to be overcome. The opportunities in this market are vast, driven by the increasing adoption of IoT devices, the growing demand for cloud computing, and the need for real-time data processing and analysis. As the world becomes increasingly interconnected and data-driven, edge computing will play a crucial role in enabling real-time decision-making and unlocking new possibilities across various industries.

Market Drivers • Increasing demand for real-time data processing: Edge computing enables real-time data processing, which is critical for applications such as autonomous vehicles, smart cities, and industrial automation. • Growing need for reduced latency: Edge computing reduces latency by processing data closer to the source, which is essential for applications that require fast decision-making, such as healthcare and finance. • Advancements in IoT and AI: the proliferation of IoT devices and advancements in AI are driving the need for edge computing to process and analyse data in real-time. • Cost savings: Edge computing reduces the need for data transmission and storage, resulting in cost savings for organizations. • Improved security: Edge computing reduces the risk of data breaches by processing sensitive data closer to the source, reducing the need for data transmission. Market Challenges • Data security: Edge computing increases the attack surface, making it more vulnerable to cyber threats. • Complexity: Edge computing requires complex infrastructure and management, which can be challenging for organizations to implement and maintain. • Scalability: Edge computing requires scalable infrastructure to handle increasing amounts of data and traffic. • Standards and interoperability: Edge computing requires standards and interoperability to ensure seamless communication between devices and systems. • Lack of skilled professionals: Edge computing requires specialized skills and expertise, which can be a challenge for organizations to find and retain. ? Market Trends • Edge AI: Edge AI is becoming increasingly popular, enabling real-time AI processing and analysis at the edge. • 5G and edge computing: The rollout of 5G networks is driving the adoption of edge computing, enabling faster data processing and analysis. • Edge computing for IoT: Edge computing is being increasingly used for IoT applications, such as industrial automation and smart cities. • Cloud-edge convergence: Cloud-edge convergence is becoming more prevalent, enabling seamless integration between cloud and edge computing. • Edge computing for autonomous vehicles: Edge computing is being used in autonomous vehicles to enable real-time processing and analysis of sensor data. Based on the report, the Components- based segment is distinguished into hard ware, software and services. The Hardware leads in the edge computing industry due to its foundational role in enabling physical computing infrastructure and processing capabilities at the edge.

Hardware holds a prominent position in the edge computing industry primarily because it serves as the foundational infrastructure enabling the deployment and operation of edge computing networks and applications. Edge computing relies heavily on physical hardware components such as servers, routers, switches, sensors, and edge devices, which are essential for processing data closer to where it is generated, thereby reducing latency and improving response times for critical applications. The reasons why hardware is crucial in edge computing is its ability to provide the necessary computing power and storage capabilities required to process and analyze data at the edge of the network. Unlike traditional centralized computing models where data is transmitted to a remote data center for processing, edge computing places computing resources closer to the data source. This proximity minimizes the time and bandwidth required to transmit data, making it ideal for applications that demand real-time processing, such as industrial automation, autonomous vehicles, and IoT (Internet of Things) deployments. In the context of edge computing, hardware components play a vital role in supporting diverse environments and use cases. For instance, in industrial settings, edge servers and ruggedized edge devices are deployed to monitor and control manufacturing processes in real-time, ensuring operational efficiency and reducing downtime. Similarly, in smart cities, edge hardware facilitates the deployment of intelligent infrastructure for managing traffic, energy distribution, and public safety applications at the edge of the network. The scalability and flexibility of hardware solutions are critical factors driving their dominance in the edge computing industry. Edge hardware can be customized and optimized to meet specific performance requirements and environmental conditions of different edge deployments, whether in remote locations with limited connectivity or in highly dynamic mobile environments. This adaptability allows organizations to deploy edge computing solutions tailored to their operational needs, enhancing overall system reliability and performance. Hardware innovation in the edge computing sector continues to evolve rapidly, driven by advancements in semiconductor technology, networking protocols, and edge-specific hardware designs. Manufacturers are developing specialized edge processors, accelerators, and IoT gateway devices that are capable of handling complex workloads and supporting emerging technologies such as AI (Artificial Intelligence) and machine learning at the edge. These innovations not only improve processing efficiency but also enable new applications and services that require intensive computing capabilities at the edge. Based on the report, the Application-based Segment is segmented into Industrial IOT , consumer IOT and Others Industrial IoT (IIoT) is growing in the edge computing industry due to its need for real-time data processing, low latency requirements, and the ability to support mission-critical applications in industrial environments. The growth of Industrial IoT (IIoT) in the edge computing industry is driven by several factors that highlight its unique requirements and advantages in industrial applications. IIoT encompasses the integration of sensors, devices, and machines in industrial settings to collect and analyze data, optimize operations, and enable predictive maintenance. Edge computing plays a pivotal role in IIoT by facilitating local data processing and analysis at the edge of the network, closer to where data is generated, rather than transmitting it to centralized cloud servers. One of the primary reasons IIoT is flourishing in the edge computing landscape is its demand for real-time data processing and low-latency response times. In industrial environments such as manufacturing plants, oil and gas facilities, and utilities, milliseconds can impact operational efficiency, safety, and decision-making processes significantly. Edge computing allows critical data to be processed locally, enabling immediate actions and insights without depending on round-trip data transmissions to distant data centers. This capability is essential for applications like predictive maintenance, where anomalies in machinery performance need instant detection to prevent costly downtime and optimize asset utilization. IIoT applications often involve massive amounts of data generated by sensors and devices monitoring various aspects of industrial operations. Edge computing addresses the challenge of bandwidth limitations and network congestion by filtering and processing data locally before transmitting only relevant information to the cloud or centralized servers. This approach reduces bandwidth costs and optimizes network traffic, making it feasible to scale IIoT deployments across diverse and geographically dispersed industrial facilities. The reliability and resilience offered by edge computing are critical for IIoT applications operating in harsh and remote environments. Industrial settings often require computing solutions that can withstand extreme temperatures, humidity, vibrations, and electromagnetic interference. Edge computing hardware, such as ruggedized servers and edge gateways, are designed to meet these environmental challenges while ensuring continuous operation and data integrity. This robustness enhances the overall reliability and availability of IIoT systems, which are essential for maintaining uninterrupted production processes and ensuring worker safety. The integration of edge computing with IIoT enables advanced analytics and machine learning capabilities directly at the edge. Edge devices equipped with AI accelerators and local processing power can perform complex data analytics tasks, such as pattern recognition and anomaly detection, in real-time. This capability empowers industrial enterprises to derive actionable insights from operational data swiftly, leading to improved decision-making, optimized resource allocation, and enhanced operational efficiencies. North America leads in the edge computing industry due to its advanced technological infrastructure, strong innovation ecosystem, and widespread adoption of IoT across various sectors. North America stands at the forefront of the edge computing industry owing to several key factors that contribute to its leadership in technological innovation and adoption. One of the primary reasons is the region's robust and advanced technological infrastructure, which provides a solid foundation for the deployment and scaling of edge computing solutions. The United States, in particular, boasts extensive fiber-optic networks, 5G connectivity, and a dense network of data centers, enabling efficient data transmission and low-latency communications—essential for edge computing applications that require real-time data processing and quick response times. North America's leadership in edge computing is bolstered by its strong innovation ecosystem and entrepreneurial spirit. The region is home to a vibrant startup culture, tech giants, research institutions, and academic centers that foster innovation and drive technological advancements in edge computing technologies. Startups and established companies alike are actively developing edge computing solutions tailored for diverse applications, from smart cities and autonomous vehicles to healthcare and industrial automation. This ecosystem encourages collaboration, investment in R&D, and the rapid commercialization of cutting-edge technologies, positioning North America as a hub for edge computing innovation globally. The widespread adoption of IoT (Internet of Things) across various sectors in North America has fueled the growth of edge computing. IoT devices, such as sensors, cameras, and connected machinery, generate vast amounts of data that require real-time processing and analysis. Edge computing enables this data to be processed locally, near the source of its generation, rather than sending it to centralized cloud servers. This approach reduces latency, bandwidth usage, and operational costs while enhancing data privacy and security critical considerations for industries ranging from manufacturing and logistics to healthcare and retail. North America's edge computing leadership is supported by its proactive approach to regulatory frameworks and standards. Government initiatives and policies encourage the adoption of advanced technologies, including edge computing, by providing incentives for infrastructure development, research funding, and fostering a conducive regulatory environment for technological innovation. These initiatives not only attract investments but also facilitate collaboration between public and private sectors to address challenges and opportunities in deploying edge computing solutions across different domains. The region's strong presence in key industries such as aerospace, automotive, healthcare, and telecommunications drives demand for edge computing solutions tailored to specific industry requirements. For instance, in aerospace and automotive sectors, edge computing enables real-time data processing for autonomous systems, vehicle-to-vehicle communication, and predictive maintenance. In healthcare, edge computing supports remote patient monitoring, personalized medicine, and healthcare analytics, enhancing patient care outcomes and operational efficiencies. • Microsoft and Azure Stack Edge Mini in the US (2023): Microsoft unveiled a miniaturized version of its Azure Stack Edge product in 2023. This compact device brings the power of Azure cloud computing directly to resource-constrained environments. This innovation caters to scenarios where deploying larger edge computing systems might not be feasible. • Siemens MindSphere AI at the Edge in Germany (2022): German industrial giant Siemens introduced MindSphere AI at the Edge in 2022. This solution allows for on-device artificial intelligence (AI) processing within their MindSphere industrial IoT platform. This enables real-time data analysis and faster decision-making on factory floors and other industrial settings. • Adlink and Mediatek Filogic 830 SoC in Taiwan (2023): Adlink, a Taiwanese industrial computing leader, partnered with Mediatek to develop a system-on-chip (SoC) specifically designed for edge computing applications. This chip, the Filogic 830 SoC, boasts high performance and low power consumption, making it ideal for resource-sensitive edge devices. • Etiqa and Amazon Web Services (AWS) in Singapore (2023): Singaporean insurance company Etiqa partnered with AWS in 2023 to leverage edge computing for faster insurance claim processing. This collaboration aims to analyze data from connected devices in real-time, enabling quicker claim assessments and approvals. • Verizon and AWS Private Mobile Edge Compute in the US (2021): In 2021, Verizon and AWS joined forces to offer private mobile edge compute solutions in the US. This offering combines Verizon's 5G network with AWS's cloud computing services at the edge, enabling ultra-low latency applications like autonomous vehicles and industrial automation. ? Considered in this report • Historic year: 2018 • Base year: 2023 • Estimated year: 2024 • Forecast year: 2029 Aspects covered in this report • Edge Computing market Outlook with its value and forecast along with its segments • Various drivers and challenges • On-going trends and developments • Top profiled companies • Strategic recommendation By Component • Hardware • Software • Services By Application • Industrial IoT (IoT) • Consumer IoT • Other applications By Vertical • BFSI • Manufacturing • Information Technology • Retail The approach of the report: This report consists of a combined approach of primary and secondary research. Initially, secondary research was used to get an understanding of the market and list the companies that are present in it. The secondary research consists of third-party sources such as press releases, annual reports of companies, and government-generated reports and databases. After gathering the data from secondary sources, primary research was conducted by conducting telephone interviews with the leading players about how the market is functioning and then conducting trade calls with dealers and distributors of the market. Post this; we have started making primary calls to consumers by equally segmenting them in regional aspects, tier aspects, age group, and gender. Once we have primary data with us, we can start verifying the details obtained from secondary sources. Intended audience This report can be useful to industry consultants, manufacturers, suppliers, associations, and organizations related to the Edge Computing industry, government bodies, and other stakeholders to align their market-centric strategies. In addition to marketing and presentations, it will also increase competitive knowledge about the industry.