Artificial Intelligence
ZIRAK IoT & Machine Learning has developed several IoT (Internet of Things) and Machine Learning projects, from architectural analysis to the implementation of the End to End solution, using Big Data and Artificial Intelligence techniques to offer innovative Earth Observation and Predictive Maintenance solutions.
Main application sectors
We have produced integrated platforms, models and algorithms for:
Environment
- Earth Observation with AI, multispectral drones, Lidar and satellite images
- Rare and invasive plants identification & prediction
- Monitoring of forests, city greenery
- Computer Vision and Taxonomy-based Machine Learning platform
- Object tracking, drone with RGB, multi and hyper-spectral cameras
Mobility
- Virtual Sensors
- Electric motor rotor temperature predictions
- Electric motor rotor torsion failure prediction
Industry 4.0
- Predictive maintenance on objects subjected to vibrational stress and on roller-bearing machines
- Dynamic integrated shopfloor operation management
- Production statistics and alerts management
- Production and assembly line control
- Mobile to Machine
Logistics
- Tracking of the production chain via Blockchain and integration with existing software systems
- Predictive logistics platform (REDtag) and log analysis system for parcel traceability
Our solid experience and knowledge is applicable to other sectors, such as:
- Avionics
- Biomedics
- Infrastructures monitoring
Innovation
The synergy established with largest Italian and international research institutes has allowed us to contribute as part of large European projects in cutting-edge technologies.
We have deepened our study of the cutting-edge technologies and platforms that we use on a daily basis:
Our added value:
- Architectural analysis and development of turnkey projects
- Neural network techniques applied to Big Data
- Close collaboration with international research centres
- Experience in European projects
- Innovative solutions for the automotive, logistics and industrial sectors
- Big Data management, prediction and estimation of residual useful life.
