1. Reduce data center loading, transmit less data, reduce network traffic bottlenecks.
2. Real-time applications, the data is analyzed locally, no need long distant data center.
3. Lower costs, no need to implement a server-grade machine to achieve non-complex applications.
Edge Computing as “pushing the frontier of computing applications, data and services away from centralized nodes to the logical extremes of a network.”
Today, most of AI technology still rely on the data center to execute the inference which will increase the risk of real-time application for applications such as traffic monitoring, security CCTV, etc. Therefore, it’s crucial to implement a low latency, real-time edge computing platform.
Sorting by human bare-eyes, the standard cannot fix due to a different person. Low accuracy, low productivity. The leak of confidential documents can cost you a big amount. record keeping, storage is a costly process.
Training and sorting by conventional, machine vision method, need a well-trained engineer to teach and modify the inspection criteria. Low latency, but low accuracy if the product has too many variations.
Implement deep learning methods for training and sorting, reduce, human bias and machine vision training process. High CTO, high latency, power-hungry, high power consumption.
The Unizen-AI-Edge computing device can be utilized to capture data and send traffic to a control center to optimize a traffic light system. It can also perform license plate recognition (LPR) to help law enforcement if vehicles break traffic laws or help parking services. Identify available parking spaces to assist drivers in congested urban areas.
With the algorithms developed using the Unizen-AI-Edge device, trained deep neural networks, now have inference capabilities to identify suspicious persons to alert law enforcement or for security departments to early warning scenarios.
Unizen-AI-Edge solutions help enable intelligent factories to be more efficient on work order schedule arrangements. In today’s production line, sticking to manufacturing schedules are becoming more and more important for business efficiency. From raw material storage to fabrication and complete products, all information from the factory such as manufacturing equipment process time and warehouse storage status is essential to achieve production goals. Solution-based AI technology can produce more detailed, accurate, and meaningful digital models of equipment and processes for product management.
Implementing AI into machine vision makes smart-automation applications easier. Previously, factory AOI needed sophisticated engineers to fine-tune inspection parameters such as length, width, diameters and many other specifications that required many adjustments. The Unizen-AI-Edge powered using AI technologies supports workloads such as defect detection and quality control to improve production yield.
Using the Unizen-AI-Edge for computer vision solutions at the edge of retail sites can quickly recognize the gender and age of the customers and provide relevant product information through digital signage. Display to improve product sales and inventory control. Self-checkout can reduce human resource cost so that retail owners can spend more resources on promoting products and understanding business patterns. Also, it can help to analyze customer’s in-store behavior and provide customer information based on gender and age to facilitate product positioning. Quickly converting the business intelligence gained and help build better business practices and increase profitability.
With AI-based technology, healthcare and medical centers can diagnose, locate and identify suspicious areas such as tumors and other abnormalities more quickly and accurately. Using segmentation technology and accurately. Using segmentation technology and trained models on the Unizen-AI-Edge can be used to locate and identify abnormalities with a high degree of accuracy helping doctors and researchers quickly serve the patient.