Session 3 - Decision Support Systems I

Abstract: This paper presents a Wireless Sensor Network (WSN) solution applied to Precision Agriculture (PA) capable of collecting real time data on different parameters related to agriculture. The technological advances related to this activity are of great importance since agriculture is considered an economic and social pillar essential for the wellbeing of society. In addition, the growing demand for real-time information in the agriculture field has driven the development of efficient wireless communications via sensor networks. WSN provides low cost, low energy consumption, easy to implement solution in places of difficult access for the implementation of wired networks. Precision agriculture is a way to optimize resources and improve cultivation through the collection of relevant information through the deployment of sensor networks, providing government authorities with statistical information to make appropriate decisions based on reliable data. The present research describes the design, implementation and validation process of a WSN technological solution which can collect information related to humidity, environment and soil temperature, atmospheric pressure, level of luminosity and UV radiation; this information is relevant to determine optimal parameters for cultivation and farming methods using IoT technologies for Big Data analysis at the government level.

Authors: Jorge Granda, Carlos Molina-Colcha, Sergio-Enrique Hidalgo-Lupera and Christian-David Valarezo-Varela

Abstract: The study compares among traditional heuristic methodologies such as the Mora – Vahrson method with a statistical method named Logical Fuzzy in order to determine an improvement in the determination of the susceptibility of landslides. The validation of the Fuzzy Logic methodology, diminishes the subjectivity of the heuristic methods obtaining results that are close to the reality, independently that the researcher is familiar with the geodynamic phenomena that intervene in the occurrence of uncertainties of the land. The Metropolitan District of Quito has been characterized to have prone sectors landslides in the rainy season and being seismically active. The result of these methodologies is different models that are defined by means of an adjustment, which agrees with the reality of the land. Therefore, the validation of the susceptibility to landslides in this sector of Quito, with new methodologies like the proposal, will be a vital instrument for the elaboration of risk cartography in other sectors of the city as well as in other cities in the Inter-Andean area.

Authors: Carolina Alexandra Jaramillo Castelo, Oswaldo Padilla Almeida, Mario Cruz D ́howitt and Theofilos Toulkeridis

Abstract: A problematic gap between existing online privacy controls and actual user disclosure behavior motivates researchers to focus on a design and development of intelligent privacy controls. These intelligent controls intend to decrease the burden of privacy decision-making and generate user-tailored privacy suggestions. To do so, at first it is necessary to analyze user privacy preferences. Previous studies have shown that user privacy profiles tend to have a multidimensional structure, which in turn might bring issues of an inexact user classification. This paper proposes to apply a fuzzy clustering approach, where fuzzy membership degree values can be used for the calculation of more precise personalized privacy suggestions. Based on the real-world dataset collected from a political platform, the fuzzy c-means algorithm was applied to demonstrate the multidimensionality and the existence of imprecise user privacy profiles, where a user simultaneously possesses features inherent in several clusters.

Authors: Aigul Kaskina


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11 - 13 June 2025
Bern, Switzerland

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