Browsing by Author "Ibarra, Manuel J."

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    A Comparison of Cultivation Techniques NFT-I, FR and Soil: An IoT Monitoring Approach
    (Proceedings of International Conference on Data Science and Applications, 2026-03-13) Ibarra, Manuel J.; Alcarraz, Edgar W.; Tapia, Olivia; Ponce, Yalmar; Calderon Vilca, Hugo D.; Quispe, Carlos R.
    Hydroponics is an agricultural method where plants grow with water and mineral nutrient solutions. For a good production of vegetables, it is essential to keep within an optimal range the values of the variables that influence growth: temperature, pH, electrical conductivity and frequency of irrigation. This article compares three cultivation sub-systems NFT-I, FR and Soil. Additionally, it describes the IoT computing for monitoring the principal variables: temperature, pH, electrical conductivity and frequency of irrigation. This prototype allows notifying the farmer about the current status of each variable through Telegram social network and a Web site. The methodology was as follows: start planting the same day in the three sub-systems, controlling the values of the variables obtained by the sensors, and notifying the farmer when the values exceed the established limits, then the weight, the number of leaves, length and width were measured. The results have shown that this system can reduce electricity consumption by 97.9%, furthermore, use green computing approach with solar panel energy supply. Finally, lettuce production was good, and in terms of weight, the number of leaves, length and width, followed the relationship FR > NFT-I > Soil.
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    IoT Computing for Monitoring NFT-I Cultivation Technique in Vegetable Production
    (Intelligent Systems and Applications (IntelliSys 2021), 2026-03-12) Ibarra, Manuel J.; Alcarraz, Edgar W.; Tapia, Olivia; Kari, Aydeé; Ponce, Yalmar; Pozo, Rosmery S.
    This article compares the production and growth times of three types of lettuce and in three cultivation systems NFT-I, RF and soil with Worm Humus. Additionally, it describes the NFT-I cultivation system, which is a cultivation technique supported by the Internet of Things (IoT). NFT-I allows to measure and store the data of three parameters: ambient temperature, pH level and electrical conductivity; the advantage is that this system allows notifying the farmer about the current status of each variable and notifying through the social network Telegram (through bots). The methodology used was to start the planting process in the three systems on the same day, then the NFT-I system was saving data read by the sensors, and later measurements were made of the time and growth of each of the planted lettuces. The results show that this system can reduce electricity consumption by 91.6%; on the other hand, it helps farmers monitor plant growth. On the other hand, regarding the harvest time, it can be verified that the RF system, NFT-I and land were harvested in 61, 69 and 105 days respectively, which shows that RF is the most efficient; In terms of size, the number of leaves, length and width, RF is also of better size than the NFT-I crop and soil. Finally, in these times of confinement due to the coronavirus disease (COVID-19), in which the economy has slowed and the needs are multiple, this NFT-I system could help people create their vegetable growing system of quickly and cheaply.
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    Serious Games for Learning: A Quantitative Review of Literature
    (Serious Games (JCSG 2020), 2026-03-13) Ibarra, Manuel J.; Ibañez, Vladimiro; Frango Silveira, Ismar; Collazos, Cesar A.; Wallner, Günter; Rauterberg, Matthias
    There exists a considerable amount of digital games that are described and published in the scientific literature. Among them, there are those considered as “serious games”, whose foremost goal differs from pure entertainment, being conceived mainly for training, capacity building, and education among other ends. Serious digital games for learning represent an important part of this whole set, and it is relevant to observe the actual state-of-the-art about the research in this field. In this sense, this paper presents a quantitative literature review on previous papers published in peer-reviewed conference proceedings or journals related to digital games for learning.