It’s presented the prototype of a monitoring system to measure the increase in the level of course of rivers for the timely prevention before a contingency of flooding. Are used hardware and software open platforms, which allow the integration and exchange of sensor modules to increase the functionality and scope, they also employ standard communication protocols that facilitate the scalability and reconfigurability of the nodes. It’s considered a solar system cells to supply energy ensuring continuous operation, also includes a real-time data transmission using wireless technology. As an Early warning System its main function is to reduce or prevent the damage caused by threats of floods. The Huasteca area has a large amount of rivers, which tend to be near populated areas or settlements, in times of rain, the majority are likely to grow suddenly and exponentially. The functional tests of the prototype were conducted in a controlled environment, identifying the appropriate process for the collection, reading and transfer of data, as well as their interpretation. The technology presented is feasible for their deployment, it allows the integration of more sensors that could form a monitoring network of larger scope.
The raw cane sugar industry in Huasteca Potosina, Mexico represents a growing market nationwide and globally. Mexico exports to the US, Europe and Japan with below rate such as a country like India, Colombia or Brazil. The little technification of this sector in the region is considered as a factor of the delays in the agro industry development. The Technological Institute of Ciudad Valles currently conducts researches for the evaluation of two of the quality characteristics of the raw cane sugar: color and texture; exploiting the computer sciences through image processing. This project defines the development of an information system through the iWeb methodology and data mining techniques to provide the information that characterizes the raw cane sugar as a quality product. With the systematization of processes for quality control, it is possible to provide direct information that supports decision-making and favors the growth of the industry towards global markets. Incorporating characteristics of information portability, ability to have reliable data on product evaluation and statistical representation of defects; becoming a support tool for the improvement of the raw cane sugar industry.
This research work shows that with the use of remote sensing technology it is possible to more effectively fulfill two of the purposes pursued by farmers in the field; manage crops more efficiently and include environmental care in decision-making. Specifically, remote sensing is applied in the context of precision agriculture through geographic information systems (GIS), unmanned aerial vehicles (UAV), multispectral sensors that capture the reflectance of the infrared band of the light spectrum (for interpretation of the biochemical state of the crop), global geopositioning systems (GPS), among others. This study limits the use of this technology to the processing of multispectral images obtained by aerial photogrammetry, and its subsequent treatment for the generation of orthoimages, the calculation of the NDVI vegetation index and the classification of land cover by clustering. Finally, the effect of classification with RGB and multispectral images is analyzed.
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