IoT Lab - TEC

*** Technology for the Planet: How are Transforming ***

We are pleased to share our latest article published in (MDPI), in which we propose an innovative approach for the sustainable management of through the development of a Digital Twin applied to the Morroa aquifer in Colombia. This work highlights the potential of digital twins as prescriptive tools for environmental decision-making, directly contributing to SDG 6: Clean Water and Sanitation.

What does our approach include?
📡 to measure water levels, pH, dissolved oxygen, and temperature in real time.
🛰️ and NDVI-based vegetation cover analysis to assess recharge capacity.
🧠 Optimized control models using (PSO) and (LSTM) to predict future aquifer behavior under different .

What did we achieve?
✅ Determining the optimal extraction rate to maintain and extend the aquifer’s lifespan.

Read the full open-access article here: https://doi.org/10.3390/w17131973



*** Tecnología para el Planeta: Como los están Transformando la del ***

Nos complace compartir nuestro más reciente artículo publicado en la revista Water (MDPI), en el que proponemos un enfoque innovador para la gestión sostenible de , mediante el desarrollo de un gemelo digital aplicado al acuífero Morroa, en Colombia. Este trabajo destaca el potencial de los gemelos digitales como herramientas prescriptivas para la toma de decisiones ambientales, con una contribución directa al ODS 6: Agua limpia y saneamiento.

¿Qué incluye nuestra propuesta?
📡 para medir en tiempo real niveles de agua, pH, oxígeno disuelto y temperatura.
🛰️ y análisis de cobertura vegetal (NDVI) para evaluar la capacidad de recarga.
🧠 Modelos de control optimizados con (PSO) y (LSTM) para prever el comportamiento futuro del acuífero bajo distintos .

¿Qué logramos?
✅ Determinar la tasa de extracción óptima para conservar el y prolongar la vida útil del acuífero.

Consulta el artículo completo en acceso abierto: https://doi.org/10.3390/w17131973

We proudly congratulate Eng. Edwin Hernández Animas for successfully defending his Master's Thesis and earning the degree of Master of Science in Engineering from the Tecnológico de Monterrey. His thesis, titled:

"Efficient Analysis and Compression of Urban Green Areas in RGB Drone Imagery Using the OSAVI Index",
was unanimously approved by a distinguished Thesis Committee comprised of research professors from the Escuela de Ingeniería y Ciencias.

Edwin’s work addresses a key challenge in : how to monitor, analyze, and store data from drone-based imagery of green areas more efficiently without compromising quality.

Highlights of his research include:
• Demonstrating that (Optimized Soil Adjusted Vegetation Index) is more robust than (Normalized Difference Vegetation Index) in urban environments for vegetation monitoring.
• Proposing an efficient masking technique that segments drone images based on OSAVI, enabling and reduced storage size while preserving spatial resolution.
• Showing that masked image sizes correlate strongly (r = 0.98) with actual , optimizing for urban monitoring systems.
• Enhancing tree inventory algorithms, achieving results 48.9% closer to the real tree count and yielding meaningful classification metrics: Precision 0.54 | Recall 0.53 | F1-score 0.53 (Friedman Test p-value = 0.046).

Environmental, social, and ecological benefits of monitoring vegetation coverage in Urban Green Spaces (UGS):
• UGS help mitigate urban heat island effects and promote biodiversity.
• Access to green spaces has been associated with lower stress levels and improved public health.
• UGS serve as crucial refuges for urban flora and fauna, enhancing ecological balance.

Congratulations, Edwin! Your contribution supports and reinforces the role of and environmental in building .

PD. Kudos to our best drone pilot so far!!!

We extend our heartfelt congratulations to Eng. Juan Francisco David de la Fuente Bustos, a valued IoT Lab member, for successfully conducting his Public Thesis Defense today, earning the degree of Master of Science from the Tecnológico de Monterrey. His thesis on "Development of algorithm and architecture design of Camera-Radar perception system for Agriculture & Construction machinery" received Unanimous Approval from a Thesis Committee comprised of researchers from both the Escuela de Ingeniería y Ciencias and the Engineering Center.