From data analysis to optimisation and automation
Both Forrest and Gartner project technologies like Machine Learning and Mixed Reality to be among the sectors with the highest rates of growth and profitability over the next five years.
FifthIngenium takes care of the initial design, development and software setup, with several years of experience optimizing automotive and manufacturing fields, and constantly seeking to integrate with manufacturers of industrial machine and tools, robots, and other Workforce 4.0 processes.
ML balances between the need to automate workflow and enhancing people’s skills.
Self-configuration and self-optimization
This intelligent system allows to control production, improving the workflow up to complete self-organization.
Integration with Mixed Reality
ML can be integrated with Mixed Reality for Model Evaluation on Cloud, on Device or on Local Network.
Smart processes and monitoring
Service systems open new possibilities for efficient value creation in processes and in monitoring, through the real-time analysis and monitoring of data streams.
A model for image recognition and classification can be trained through ML algorithms, and implemented seamlessly both in the cloud or on premise.
Object recognition and human pose detection
Using ML for object recognition and human gesture detection offers the opportunity to choose the best combination of features and classifiers for learning.
FifthIngenium develops Machine Learning solutions using the best dedicated hardware and software.
Hardware for high performance, with ultra-low power, perfect for on-device AI and ML applications. It is specifically designed to achieve more computation at lower power for computer vision and AI at the edge.
Azure Machine Learning
Cloud-based environment useful to train, deploy, automate, manage, and track ML models. Azure Machine Learning can be used for any kind of ML, from classical ML to deep learning, from supervised to unsupervised learning.
It is an end-to-end open-source platform for ML and deep learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications.