Industry 5.0, or 5IR for short, is the next stage of the manufacturing sector's continuous development. Instead of starting a revolution, 5IR aims to build on the framework laid down by Industry 4.0, its predecessor—which brought into the fold innovations such as big data, automation, cloud computing, artificial intelligence, machine-to-machine communication (M2M), and the Internet of Things (IoT)—that that have forever changed the industrial environment.
Businesses and entire sectors are still adjusting their operations to Industry 4.0. Some are adopting the 5IR goals as they go. The main objective is to promote increased human-machine cooperation using Industry 4.0 technologies, particularly in creative, intricate decision-making, and jobs requiring emotional intelligence. Businesses that implement 5IR thus benefit from the best of both worlds: automated efficiency combined with human creativity to gain a competitive edge.
Due to its human-centric goals, 5IR will have significant effects on workers. 5R puts people back on the factory floor, where their active participation in decision-making gives automated but often times rigid industrial processes more agility and flexibility.
Related: Industry 5.0 Ushers in a New Era of Human-Centric Contributions to Production Processes
Applications of Industry 5.0
Despite being in its infancy, a few potential applications for 5IR have been noted, such as:
Manufacturing
5IR will see a greater role for AI-enabled collaborative robots (Cobots) and smart devices than Industry 4.0. The new breed of cobots can visually study complex human operations and learn how to execute them, much like an apprentice, freeing workers from tedious and repetitive tasks. Cobots, as opposed to typical robots, are not restricted for safety and can safely collaborate with humans, which creates new opportunities for industry. When humans and machines work together, employees can concentrate on adding value for customers through innovation and customization. Thanks to specialized algorithms that automate visual understanding and pattern matching, smart devices are able to watch, analyze, and interpret visual input in order to detect and identify differences.
Agriculture
There is enormous potential for 5IR methods in this field. Applications include using AI to detect diseases and increase crop yields, drones for surveillance, and completely self-sufficient tractors, weed eaters, and harvesters to improve productivity.
Related: Machine Vision System Tracks Vineyard's Crop Yields
Security
By examining video footage, AI can identify patterns in human behavior. By doing this, surveillance systems will be able to identify early indicators of potential security incidents or access breaches. When paired with data analytics, footage from store security cameras may also be a useful tool for learning about the requirements, preferences, and habits of customers.
Healthcare
By combining human abilities with cutting-edge technologies, 5IR techniques can improve diagnosis, treatment, and pharmaceutical development. AI medical imaging, for instance, supports physicians with personalized treatment plans, care assistance, and decision-making.
Transportation
By reducing traffic and optimizing routes for logistics, the integration of visual systems inside cars and beside roads promotes corporate distribution while also improving environmental sustainability and driver safety.
Related: NoTraffic Solution Eases Urban Congestion
These illustrations demonstrate how imaging technology is essential to fulfilling many of the aspirational objectives of 5IR. Robots, cobots, and other machines in the 5IR era can have both AI "insight" and human-like "sight" thanks to machine vision.
To push machine vision to this new level, it will be necessary to leverage the capabilities of lightning-fast networks, AI-powered software, multimodal GPT, and high-resolution digital cameras. A subset of artificial intelligence called deep learning can teach a machine to contextualize the visual data it has collected, simulating human cognition and enabling it to make predictions. In addition, natural language processing enables these same systems to read and understand information found in visual data, such as reading labels on pharmaceutical packaging, without the need for complex programming or high levels of technical expertise found in traditional rule-based machine vision techniques.
From Camera to PC
Despite being two different stages in the development of industrial processes, Industry 4.0 and Industry 5.0 are similar in that they rely on the transmission of real-time, bandwidth-intensive visual data. Given this, a frame grabber placed in the gap between the camera and the PC could be the key component of 5IR. This computer accessory's function is to take pictures from a camera and send them to the PC's host memory so that it may process them.
Frame grabbers can use a variety of transmission standards, the most often used of which are CoaXPress (CXP) over coaxial cables, Camera Link (CL) over Ethernet connections, and Camera Link over LVDS cabling.
When compared to non-frame grabber-based transmission methods like GigE Vision or USB3, CoaXPress frame grabbers allow faster, more dependable data transmission for an image system. The CoaXPress interface, which was first launched in 2009 at the Vision show in Stuttgart, Germany, has shown itself to be the best option for balancing system costs with the increasing demands for longer cables, quicker speeds, heat dissipation, and Power over CXP power delivery.
The latest version of CoaXPress, the CXP 2.1 interface, is particularly well-suited for 5IR imaging applications. With transfer data speeds of up to 12.5 Gbps (Gigabits per Second) per link over a single coaxial cable or 50 Gbps over four cables when all four links are used for a single camera, CXP 2.1 satisfies the need for speed. Not only does CoaXPress carry image data over a single coax cable, but camera communication, control and power, reducing connectivity down to a single cable.
The latest add-on to CXP 2.1 is CoaXPress Over Fiber (CoF). Industry insiders predict that CoF will be a feasible route to 100, 200, and even 400 Gbps—velocities that are significantly faster than the capabilities of coaxial cables and therefore need the usage of optical fiber. In addition to speed, CoF will operate without the need for error-prone extenders at distances of up to 80 km (about 49.71 mi) in single mode and 300 m (about 984.25 ft) in multimode.
Related: Extending the Benefits of CoaXPress with CoaXPress over Fiber
CXP Meets AI
With AI-enabled technologies, graphics processing units (GPUs) are a crucial lever for boosting competitiveness and productivity. GPUs, with their thousands of processor cores and highly parallelable architecture, are powering deep learning, inference, and high-performance computing tasks.
CoaXPress frame grabbers are becoming more optimized to work with the newest GPU generation, allowing vision systems, robotics, and advanced edge AI applications to be deployed more quickly and with prototype systems. This development merges the lightning-fast data rate speeds of CoaXPress 2.1 with the unprecedented computational capabilities and large shared memory for CPU and embedded GPU devices. Building complex machine vision and autonomous inspection applications is made possible by CXP/GPU solutions, which combine AI-accelerated image processing with interface support for numerous CoaXPress (CXP) cameras at up to 50 Gbps. It is also an ideal platform for prototyping end-to-end AI applications.
AI-enabled technologies and machine vision advancements are driving Industry 4.0 and will form the basis of 5IR as well. Securing the appropriate hardware is essential for achieving success on this journey. Machine vision, and specifically the ever-evolving CoaXPress interface, creates a more seamless interplay between humans and machines. Furthermore, CXP can support 5IR in achieving a wide range of important goals such as lowering production waste while boosting sustainability and efficiency.
