Machine Learning, process
prediction and optimisation
Description
A chatbot is a conversational assistant that enables interaction with users, automatically and coherently responding to written or spoken queries.
It is primarily based on technologies such as Artificial Intelligence (AI) and Natural Language Processing (NLP) to recognize specific words or expressions and respond using predefined phrases. This allows the chatbot to follow a conversation naturally, answer users appropriately, and even execute tasks within existing systems.
Competitive Advantages
The growing sensorization of industrial, agricultural, and other activities provides companies with an enormous volume of data. Similarly, service companies of all types have large amounts of information on customers, suppliers, sales, etc. However, this information is often underutilized.
To fully exploit this vast amount of information, it's essential to go further—developing classification, forecasting, or optimization models that directly address the specific problems of each company and identify areas where substantial improvements can be achieved.
Applications
Some potential applications include:
- Design and development of algorithms to solve minimization problems (costs, travel, materials, processing time...) or maximization problems (sales, revenue, profit...)
- Customer knowledge: segmentation, classification, behavior prediction
- Sales and pricing forecasts
- Zero-defect manufacturing
- Failure prediction in industrial production processes
- Analysis of existing problems and design of optimal solutions
- Study and optimization of non-local problems, where the optimization of one element affects the rest of the system
- Evaluation of existing algorithms: benchmarking and efficiency analysis
- Integration and deployment of algorithms into existing systems
Classification
Technology Areas:
- Artificial Intelligence and cognitive systems
- Data mining, Big Data, database management
- Simulation and modelling
Categories:
- Concept validation and prototyping
- Testing and validation
- Market intelligence
Keywords
Machine Learning, Forecasting, Prediction, Optimization, Segmentation, Complex Algorithms, Big Data, Zero Defects, Customer Knowledge
Contact
Success Stories
Development of a forecasting model for urban solid waste management
Based on data provided by automated sensors installed in each container, a forecasting model was developed to predict fill levels for different types of waste containers (glass, packaging, paper, general waste).
The results of this prediction are used to improve service quality and optimize waste collection routes. This enables cost reduction by aligning travel frequency and routes with actual needs, thus also lowering the environmental impact of transportation itself.
