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Jul 2, 2025 in Machine Learning
Discover the top 10 sales forecasting techniques for 2025. This guide covers everything from time series to machine learning for ultimate accuracy.
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NILG.AI is selected on the Re-Source open innovation program.
NILG.AI on Mar 6, 2024
NILG.AI has scored yet another impressive victory in open innovation, the Re-Source challenge, organized by Sociedade Ponto Verde and Beta-i. The program aims to build strategic partnerships with innovative startups and established industry leaders through impactful pilot projects. This time, our proposal focuses on applying AI in the waste management industry to find more sustainable solutions.
This achievement marks a milestone in our journey through open innovation challenges. We have won and successfully executed three Hands on Data challenges: Flat Finder, Combustion Optimization, and Image Insight. Additionally, we secured a win in the Open Call for Urban Mobility solutions. These successes underscore our dedication to nurturing projects that deliver state-of-the-art technologies and scalable solutions across diverse industries.
Out of more than 150 innovative company submissions, NILG.AI’s proposal stood out, earning us a spot among the 17 chosen to join Re_source’s program in partnership with Algar. Algar, a prominent waste management entity within the MOTA-ENGIL group, specializes in the selective collection, transfer, and sorting of recyclable waste.
This achievement confirms our innovative use of Open Data to improve urban mobility solutions, an idea initially inspired by VoxPop’s SafeJourney project.
Our selected project centers on using AI to optimize waste management routes by supporting the positioning of new recycling bins in the areas where they are most needed. The pilot, which aims to apply AI in the waste management industry, will reduce the time spent doing this assessment manually and support the creation of a data-driven culture in waste management.
Stay tuned for more insights as we work alongside Algar to develop a strategic AI implementation plan, promising to redefine waste packaging management through technology.
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