Abstract
Water management has become a global priority in recent decades. The demand for water resources is increasing in cities due to the increase in population and the intensive use of water in economic activities and ornamentation. The problem is exacerbated when cities are built on desert regions, this is the case of Lima which is the second largest city built on a desert after Cairo. In this type of cities, it is necessary to minimize water consumption in activities that do not cover the priority needs of the population. For this reason, one of the most important tasks in the management of water resources in Lima is the optimization of water use in irrigation of parks, malls and other public green areas, necessary to offer a good quality of life to citizens. This research develops a smart decision support system to optimize irrigation in city parks. The proposed methodology takes 4 variables: land area, temperature, park humidity and weather forecast. First, strategic segmentation of the total area of the park is carried out, followed by the use of low-cost sensors to construct real-time humidity and temperature maps of the land area. Afterwards, a fuzzy inference system (FIS) that incorporates the knowledge of agronomists to process vague information in terms of computer interpretable language, together with the data collected from the variables and humidity and temperature maps is built, to assess the need for irrigation of each segment of the park. A dashboard is made to facilitate the visualization of results, including humidity and temperature maps, the weather forecast for the area and the recommendation of the FIS, which supports decision-making on irrigation needs in each segment of the park. The methodology was applied in a case study that corresponds to a San Isidro park in the city of Lima. Significant expected savings were obtained in terms of water resources and monetary units, which demonstrates the viability of the application of this smart system oriented at supporting decision-making on smart irrigation in the city’s parks.
Highlights
Water resources management has become a global priority in the last decades [1]
In summary a methodological framework is proposed, this includes data collection, data storage, data pre-processing, interpolation of the land humidity and temperature values to minimize the amount of sensors needed for a good representation of the variables, a fuzzy inference system whose output is a score based on the variables, and a visual decision-making tool with recommendations to help those in charge of the irrigation to make better and more informed decisions
A methodological framework is proposed, this includes data collection, data storage, data pre-processing, interpolation of the land humidity and temperature values to minimize the amount of sensors needed for a good representation of the variables, a Fuzzy Inference System, and a visual decision-making tool
Summary
Water resources management has become a global priority in the last decades [1]. The Rio + 20Declaration emphasizes the need to establish a green economy to achieve sustainable development and at the same time protect and improve the management of the world’s natural resources [2].water resources are increasingly recognized as a central pillar of the green economy. Water resources management has become a global priority in the last decades [1]. Declaration emphasizes the need to establish a green economy to achieve sustainable development and at the same time protect and improve the management of the world’s natural resources [2]. Water resources are increasingly recognized as a central pillar of the green economy. The preservation of water resources is an engine of economic growth and a prerequisite for commercial investment. In some localities, good water management comes as a result of growth [1]. The significance of water resources is justified by different factors.
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