This record consists of several scripts and files designed to calculate and visualize the efficiency of a burner, as well as predict the burner power using a neural network model. This model consists of a sequential neural network with multiple layers. Bo...
The purpose of the Data Exploration Service is to allow the users of VesselAI to explore the available datasets, combine them and express complex queries on them. The service offers an environment through which the user can discover the available datasets...
Using a unique dataset, comprising historical maritime data for different vessel voyages, including vessel type, voyage information and environmental factors, we employ decision trees, a number of regression, and artificial neural network algorithms for p...
The Kaspar AI Natural Language Media Indexing Engine (NLMIE) is an application for MacOS machines with M1/M2/M3 chips, which allows for fast and natural video search within Adobe Premiere Pro.
LexaTexer provides an Enterprise AI platform to support the energy value chain with prebuilt, configurable AI applications addressing CAPEX intense hydro assets like Pelton and Francis turbines and pumps. In this project we combine our Enterprise AI platf...
The Load Forecast Model is distinguished by its precision in predicting energy load demands, owing to its integration of advanced machine learning algorithms. Its cloud-hosted nature ensures scalability and adaptability, catering to both centralized and e...
The project SuperPower 2.0 developed thanks to I-NERGY second open call has developed super-resolution algorithms to increment the pixels in a thermal image using Convolutional Neural Networks. The datasets included consists of two subserts of original t...
The project SuperPower 2.0 developed thanks to I-NERGY second open call has developed super-resolution algorithms to increment the pixels in a thermal image using Convolutional Neural Networks. The datasets included consists of two subserts of original ...
The main objective of the project is the creation of a module with the help of Web Scraping, Machine Learning and Artificial Intelligence techniques capable of recommending the recommended light intensity for the next day of the public lights of a city in...
UrbAlytics aims to bridge Artificial Intelligence with Earth Observations, producing information layers that can support city planners and decision-makers in the context of climate resilience and related challenges in urban areas. This research investigat...
The main goal is to achieve excellence in the HELIOS public lighting remote management system, implemented in more than 40 cities in Spain. We will use AI to predict future breakdowns for both luminaire and eboxes. The necessary data is included.
A flexible and extensible synthetic data generation engine based on mainstream statistics distributions and on timeseries generative AI techniques.
With the growth and improvement of production automation in manufacturing, Artificial Intelligence (AI) systems must be safe, trusted, and secure, even when operating in dynamic, unstructured and unpredictable environments. In this regard, one of the STAR...
The Assessment List for Trustworthy Artificial Intelligence (ALTAI), is a practical tool that helps business and organisations to self-assess the trustworthiness of their AI systems under development.