Big Data and Agro: 7Puentes joins the Palenque Project

7Puentes, together with FluxIT company, won an open tender to carry out the Palenque Project, a platform to store data and an applications ecosystem that will provide technological solutions for the agricultural sector.

The initiative, financed by Sadosky Foundation and the National Ministry of Agriculture Livestock and Fisheries, will provide producers of the agribusiness a platform to store large amounts of data (generated by sensors, performance monitors, etc.) and be able to cross them with other public data systems, such as weather, topography, etc.

“The platform that we have developed enables the exchange of information between the different actors based on the definition of protocols and models of consensual and unified data, and the generation of public knowledge based on the crossing, modelling and analysis of producers’ data and public data,” explains Ernesto Mislej, 7Puentes partner and project leader.

The technological development of the agricultural activity is a process that has been underway over the last few years and involves small, medium and big producers. Initiatives like Palenque Project respond to the sector demands and are part of the phenomenon known as precision agriculture: the availability of information summarized and organized in dashboards and control panels describing the health condition of crops provides agricultural engineers the necessary support to make the right decisions. Having this information online and in real time expedites the decision processes and reduces costs significantly.

“This project is based on the Hadoop technology and it is a GIS system (geographical information system), something absolutely innovative since there are few GIS systems of Big Data,” states Mislej.

7Puentes, through Palenque Project, is seeking to add value to one of the strategic economic activities for most of the countries: the agribusiness. With a greater level of accuracy in the information, the productive performance of fields can be optimized and, consequently, increase the agricultural production.