Challenges
Here you will find challenges presented by the sponsoring companies.
1. Tool for analysing the electricity consumption of an installation and proposing the most economical energy tariff.
➡ Sector: Electrical
📜 Descripció: A partir del Software de Schneider Electric EcoStruxure Energy Hub, supervisar els consums d’una instal·lació real i en base al seu comportament proposar la millor tarifa elèctrica possible per tal d’ajudar a reduir els costos associats al consum energètic.
🏢 Company: Schneider Electric
2. Computer vision for quality control in industrial plants
➡ Sector: Storage and logistics industry.
📜 Description: In the reception area of a storage system, quality control is carried out on the pallet and the materials it carries. This control is implemented to prevent accidents caused by damaged pallets or oversized products, ensuring that they meet quality standards. It is proposed to implement a computer vision AI system that accurately and quickly inspects products and pallets, identifying potential visible defects such as broken pallets, products exceeding the allowed volume, and damage to the packaging.
🏢 Company: Mecalux
3. Predictive maintenance of Mecalux machines
➡ Sector: Storage and logistics industry
📜 Description: Collect real-time data from the set of machines that Mecalux has deployed in the facilities of our clients across different countries. The main objective of the collected data is to analyse it in order to anticipate potential failures that could lead to the stoppage of any machine, requiring urgent intervention, which could be either remote or on-site. This would result in costs in terms of time and money, as well as the potential economic losses clients may face if the machines are not operational.
🏢 Company: Mecalux
4. Raw material procurement planning
➡ Sector: Storage and logistics industry
📜 Description: Raw materials purchasing planning in the industrial world depends on various factors such as orders, raw material prices, and storage capacity. The challenge is to create an AI model that enables the planning of raw material purchases based on these factors in order to optimise purchasing and reduce costs.
🏢 Company: Mecalux
5. Patent analysis with AI: detection of prior disclosure
➡ Sector: Intellectual property
📜 Description: In a world where thousands of new patents are registered every day, ensuring that an invention is truly new has become a key challenge for patent offices, companies, and researchers. In this challenge, participants will step into the shoes of patent analysts with the help of artificial intelligence. Using a specific patent, they will break down and identify the key features of its claims, and search for prior art documents that describe these same features. Any matches found should include references to the identified texts. The analysis concludes with a critical assessment of whether there is any indication of prior disclosure that may cast doubt on the novelty of the analysed patent.
🏢 Company: Fractus
6. Creation of an AI model for predicting trihalometan concentration
➡ Sector: Water
📜 Description: The presence of trihalomethanes in water is a major concern in the Llobregat basin, where the chlorination disinfection process can generate a significant amount of these compounds, which are harmful to public health. To ensure safety, strict controls are implemented to ensure that trihalomethane levels remain within safe limits. Thus, the creation of an AI model will optimise monitoring and anticipate potentially problematic situations. AI can efficiently analyse large volumes of data, identify patterns and trends, and provide accurate predictions, thus improving water treatment management for consumption.
🏢 Company: CETAQUA