The Evolution of Edge Computing: Transforming Industries with Real-Time Insights

Summary

Edge computing is empowering AI embedded applications and IoT to accelerate time to value for digital transformation initiatives. By 2023, according to IDC, more than half of new enterprise IT infrastructure will be at the edge. “Currently, around 10% of enterprise-generated data is created and processed outside a traditional centralized data center or cloud,” said Santhosh Rao, senior research director at Gartner. "By 2025, Gartner predicts this figure will reach 75%." 
 
By extension, edge computing is ushering computer vision into a new era, and the combination is driving the development of intelligent systems, smart devices and immersive experiences. The advantages of edge computing, including faster processing, heightened security and real-time insights, have elevated it to a pivotal tool for various computer vision applications.

Over the past 12 months, we have witnessed a surge in interest in critical applications for computer vision on the Edge, indicating a growing demand for fault-tolerant-based solutions. This article will explore the top applications of computer vision on edge devices—applications that span across oil & gas, discrete manufacturing, public safety and smart cities and the retail industry—each offering unique opportunities for the integration of edge computing and computer vision.  
 

Oil and gas: Enhancing environmental, health and safety (EHS) 

In the oil & gas sector, edge computing and computer vision are proving to be invaluable in addressing Environmental, Health and Safety (EHS) concerns. Vision systems can now identify issues traditionally assessed by human personnel. This includes the monitoring of flares and processes to detect hazardous conditions such as gas or fluid leaks and changes in flare chemical make-up through color analysis. Moreover, real-time cameras can be employed for Personal Protection Equipment (PPE) usage monitoring, ensuring the safety of workers in hazardous environments. These AI-enhanced systems can even detect injuries and promptly alert relevant authorities, enhancing overall safety in the industry. 
 

Discrete manufacturing: Quality control and workflow efficiency 

Computer vision on the Edge is significantly impacting discrete manufacturing. Quality Control and Quality Assurance (QCQA) processes are being optimized through the integration of computer vision systems. These systems can identify defects at multiple points in a manufacturing process, improving the efficiency of quality control. Furthermore, the capabilities of cameras to see beyond the human eye, such as thermal and infrared imaging, make them indispensable for detecting weaknesses or inconsistencies in various processes. Beyond quality control, workflow improvements are also being achieved through video analytics. By monitoring employee movements, companies can enhance workflow processes by optimizing walking routes, resource storage and assembly procedures, ultimately boosting productivity. 
 

Public safety and smart cities: Multi-faceted applications 

Edge computing is playing a pivotal role in ensuring public safety and enabling the smart city revolution. These applications span a wide spectrum, from seamlessly managing large event security to enhancing biometric testing. Edge devices are crucial for monitoring traffic flow, facilitating cashier-less checkouts and identifying security threats, all of which contribute to more effective public safety responses. In the context of smart cities, edge computing and computer vision are central to various municipal activities such as paying for parking or tolls, incident response, managing peak traffic flows and implementing energy efficient practices making cities safer and more efficient. 
 

Retail: Improving customer experience and business performance 

The retail sector is another area where edge computing is making substantial inroads through computer vision applications. These applications encompass inventory management, warehouse management systems and customer-facing systems. By analyzing data from in-store point-of-sale (POS) systems, cashier-less checkouts and e-commerce platforms, retailers can gain insights into buying patterns, optimize loss prevention strategies and gauge customer sentiment. This empowers retailers to enhance the customer experience and, in turn, boost business performance. 
 

Conclusion 

Computer vision systems are driving transformative changes across multiple industries, however edge native deployments are required to capitalize on the technology. The speed, security and real-time insights offered by edge computing make it a crucial tool for applications in oil & gas, discrete manufacturing, public safety and smart cities and retail–among other industries. Vision systems alone do not bring about change, however they provide the insight necessary to drive informed action. The local integration of these insights with real time workflow processes is necessary to enact change. As technology continues to evolve, we can expect further innovations in edge computing and computer vision, bringing about a future marked by safer, more efficient and smarter systems and devices that promise to transform our daily lives now and in years to come.