Environmental monitoring is critical to developing appropriate policies for environmental sustainability. The quality of drinking and agricultural water is affected by bad environmental management strategies. In addition, natural water sources have been reduced due to climate changes and the lack of police and compliance with regulations for water resources management. In the Andes region of Ecuador, these problems have increased in recent decades. The lack of water affects not only human well-being, but also causes soil degradation. Therefore, finding alternative water sources has become the underlying requirement to provide human well-being and mitigate soil degradation in these regions. This article presents a fog collection system based on water condensation towers and Internet of Things (IoT) technology with real-time monitoring. Our system allows the monitoring of environmental parameters while providing alternative sources of water from the environmental fog. Therefore, by collecting information related to the process of fog collection and climatic measurements of the environment, we seek to determine the state and trends of environmental conditions with respect to the performance of fog collection. In addition, our system allows the storage of historical ecological data, which can be used to develop environmental management policies. We have deployed our system on the slopes of the Ilalo volcano, Pichincha province, being part of the Ecuadorian Andes, where the soil deterioration has increased in recent years and has the largest soil degradation rate in Ecuador.

Water management is one of the fundamental principles for comprehensive management and water security and is affected in various ways by the degradation of watersheds, mainly the agriculture sector due to the reduction of water resources and soil erosion. The objective of this research was to implement a dynamic model for the water management of the Quebrada de Togllahuayco as a modeling and dynamic prediction tool and thus determine the quantity of water available for a sustainable quinoa crop and the adaptation to future conditions. This work involves the use of dynamic modeling applied to water supply for irrigation with a general model and the application for the ancestral population of La Toglla. A trend model with incidence of climate change and a current one under the initial variables is proposed. The Vensim 7.3.4 free software was used, determining a positive water balance to satisfy the needs of water, both to preserve the ecological flow and to use water for irrigation, since approximately 10,500 m3 is needed for cultivation, which is favorable for the use of water.

Nowadays, the veracity related with data quality such as incomplete, inconsistent, vague or noisy data creates a major challenge to data mining and data analysis. Rough set theory presents a special tool for handling the incomplete and imprecise data in information systems. In this paper, rough set based matrix-represented approximations are presented to compute lower and upper approximations. The induced approximations are conducted as inputs for data analysis method, LERS (Learning from Examples based on Rough Set) used with LEM2 (Learning from Examples Module, Version2) rule induction algorithm. Analyzes are performed on missing datasets with "do not care" conditions and missing datasets with lost values. In addition, experiments on missing datasets with different missing percent by using different thresholds are also provided. The experimental results show that the system outperforms when missing data are characterized as "do not care" conditions than represented as lost values.

The objective of the study was to determine the climatic variability of Pedro Moncayo canton, to establish methodologies for planning and adaptation of the agricultural production systems of the canton. Meteorological data in the period 1965-2016, various aspects of climate variability and the occurrence of extreme events such as the ENSO phenomenon were analyzed, and how they have influenced the air pressure, precipitation and the temperatures of the canton. The Standardized Precipitation Index and the equation created by Fournier were applied. The results show that the average thermal amplitude was 2.46 ° C, the average temperature increase of 0.5 ° C in the whole-time series analyzed. The period of drought corresponds to the months of May to September and to the rainy season of October to April; and the annual average value is 618 mm per year, with a minimum of 409 mm for 2001 and a maximum of 846 mm for 2008. The characterization of the climate variability of the canton will allow corrective measures of territorial planning and formulate a sustainable management plan of the territory.