AEWIN, which provide smartly designed networking platforms, announces partnership with UNISEM to accelerate the move into the AI-assisted future. UNISEM has taken its video analytics expertise and implemented it into useful real-world applications.
UNISEM developed a solution that is based on AI’s Deep Learning method to help in solving traffic problems caused by complex and diverse traffic environment, and drivers’ traffic law disobedience. UniTraffic is a traffic management technology that utilises deep learning-based image processing technology and multi-object detection that counts and classifies on-road objects such as pedestrians, automobiles, motorcycles, and trucks. It can also detect the licence plate number of vehicles that violated traffic regulations.
According to the company, it has 99% accuracy for multiple object recognition in real-time. UniTraffic solution provides statistics and traffic flow patterns to plan future infrastructural development and upgrades. Likewise, for city administration and police departments, UniTraffic can minimise the time used for administering tickets and reduce personnel costs.
“UNISEM’s vision aligned closely with AEWIN’s hardware development roadmap. The continued relationship allowed us the integrate designs optimal for UNISEM’s specific hardware requirements,” said Charles Lin, CEO at AEWIN. “Today’s announcement is the result of the past few years of cooperation. Through repeated testing and benchmarking, AEWIN has thoroughly investigated the performance characteristics of the UNISEM software suite that allows us to provide a workload-optimised total solution.”
UniSafety can help prevent incidents during manufacturing
To prevent various accidents during the manufacturing process, AEWIN cooperates with UNISEM’s IoT Division to provide UniSafety, an AI-based computer vision solution. This is a Smart Factory solution that uses Deep Learning-based computer vision technology to provide a safe work environment, prevent potential accident, and reduce serious injuries.
UniSafety is based on video analytics technology enhanced with deep learning that allows detection of various dangerous situations, such as fire, falling materials, non-wearing of safety equipment, intrusion, etc., that can occur during the production process. In the case of an accident or unusual situation, the system informs the safety supervisors via web-dashboard notification, text message, and loudspeaker. It also offers motion detection for detecting unauthorised access or intrusions.
“AEWIN has been exceedingly helpful in our quest to find the right hardware to host our solutions. AEWIN has not only provided insights in hardware design and selection, as well as taking our software in-house to provide customised firmware specific for our workloads,” said Jung Boo Eun, the Managing Director from UNISEM.