Tesis y Tesistas 2020 - Postgrado - Fac. de Informática - UNLP

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Mg. Ernesto Esteban Ledesma
From the field tests carried out with the prototype, the first
data were obtained that relate the different variables of the
sensors and their impact on the level of water risk.
When the most critical variations in soil moisture, the
determining variables are reduced to room temperature
and PH. A more significant finding regarding the variables
is related to the behavior of the PH: It has been detected
that when the PH is below 230 mV and the humidity in the
soil is below 450mV, the number of risk situations increases
significantly. This finding will be validated in future tests.
Future Research Lines
Regarding the Determination of new Data Logs
It remains to verify the model inferences in different crop
seasons.
Also the evaluation of how the incorporation of additional
information affects the results (in processing times and
precision): satellite data and polygon information, etc.
Variable sampling
Since the interval between samplings classically established
in the community is very wide in relation to the speed of
change of the model, the economic impact on yield must
still be specified, when irrigation is guided by early warnings
and water stress is completely prevented.
Detection and Prediction of Low Green Index Levels
Another interesting problem to consider during rice
cultivation is the early detection of deficiencies and
shortage of chlorophyll. Likewise, it is possible to study the
proper use of nitrogen in these crops.
Pest detection and prediction
Through climatic variables that the model works, it is
possible to develop a set of stamps for the detection of
certain pests in crops.
Detection and prediction based on other crops
It is planned to incorporate in the core of the FHS model
data, variables typical of other precision cultures. In this
way it is possible to design specialized predictive models.
Of the new variables that are detected, different patterns
must be defined regarding the status of the new type of
crop, so that it reacts on the different alerts provided by the
system.
Related to the Kronos Agro prototype
This section details the pending activities, improvements
and new lines of research that arise from the prototype as
a piece of software.
Implementation of a mobile system
The proposed system encompasses web technology and
complies with “responsive interfaces” (those with the
ability to adapt to any device screen). Therefore, a native
application for mobile devices can be developed.
Reports of water risk situations
If it is extended to be able to use different monitoring zones
in parallel, users could report
risk incidents by taking the coordinates (latitude and
longitude) and send them to Firebase to indicate the risk
reports in that location.
The use of Firebase Functions (functions that fire routines
when events occur) allows you to execute a function stored
in the database every time a water risk is reported. Among
other things, the functions could be extended not only to
alarms (current use) but also to control triggers such as
irrigation valves, WEB messaging, etc.
Determine new patterns from analysis of field test results
The prototype currently works with 8 patterns (defined
by water risk), increasing this number of patterns implies
improving the efficiency of the prototype and detecting
more situations (and more diversity).
89 TESIS Y TESISTAS 2020