Abstract
This article details the development and deployment of an Internet of Things (IoT) platform aimed at optimizing water usage in community kitchens in Cali, Colombia. Conducted at the Fundación Aprender, Crear y Crecer, which serves as both a dining hall for 120 people and a residence for the project leader’s family, this initiative employs an IoT architecture enhanced by Edge Computing technologies. This system integrates continuous data collection through IoT sensors, edge processing for predictive analysis, and a cloud platform for advanced data analytics and visualization, optimizing decision-making in real-time. The research findings indicate a strong positive correlation (Pearson coefficient approx. 0.926) between rising average temperatures and increased water consumption, especially during summer months. Data gathered over two years enabled the identification of consumption patterns and hypothesis formulation. Based on these insights, a scalable platform is proposed for implementation across 762 other community dining facilities in the city, offering a robust solution for large-scale water management. This strategy not only aims to enhance environmental and economic sustainability but also seeks to improve the quality of life for vulnerable communities through efficient water resource management.
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Acknowledgments
This research stems from the Cybersecurity for IoT Networks (SCRIN) project (C068/23), the result of a collaboration agreement signed between the National Cybersecurity Institute (INCIBE) and the University of Salamanca. This initiative is being carried out within the framework of the funds of the Recovery, Transformation and Resilience Plan, financed by the European Union (Next Generation).
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Giraldo, D.M., Sarria, N.V., Núñez V., J.M., Flórez, S.L., De la Prieta, F. (2025). Architecture of an IoT Platform for the Optimization of Water Resources in Community Kitchens in Cali, Colombia. In: Novais, P., et al. Ambient Intelligence – Software and Applications – 15th International Symposium on Ambient Intelligence. ISAmI 2024. Lecture Notes in Networks and Systems, vol 1279. Springer, Cham. https://doi.org/10.1007/978-3-031-83117-1_16
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