Abstract
Smartphones show potential for controlling and monitoring variables in agriculture. Their processing capacity, instrumentation, connectivity, low cost, and accessibility allow farmers (among other users in rural areas) to operate them easily with applications adjusted to their specific needs. In this investigation, the integration of inertial sensors, a GPS, and a camera are presented for the monitoring of a coffee crop. An Android-based application was developed with two operating modes: (i) Navigation: for georeferencing trees, which can be as close as 0.5 m from each other; and (ii) Acquisition: control of video acquisition, based on the movement of the mobile device over a branch, and measurement of image quality, using clarity indexes to select the most appropriate frames for application in future processes. The integration of inertial sensors in navigation mode, shows a mean relative error of ±0.15 m, and total error ±5.15 m. In acquisition mode, the system correctly identifies the beginning and end of mobile phone movement in 99% of cases, and image quality is determined by means of a sharpness factor which measures blurriness. With the developed system, it will be possible to obtain georeferenced information about coffee trees, such as their production, nutritional state, and presence of plagues or diseases.
Highlights
Precision agriculture (PA) emerged from the need to correctly program activities on a farm, to make efficient use of economic, human, and technological resources, to reduce environmental impact, and to make crops traceable
The movement of a mobile device was accurately identified as it recorded videos and moved over the branches of a coffee tree
This technological characteristic caused the resulting videos of a sampling to have smaller sizes, and causes less space to be required on servers or the device itself
Summary
Precision agriculture (PA) emerged from the need to correctly program activities on a farm, to make efficient use of economic, human, and technological resources, to reduce environmental impact, and to make crops traceable. The need to make decisions on a plantation, based on real crop measurements (which are referenced terms of in space and time) has resulted in the development of different technologies to estimate, evaluate, and understand variables on plantations that affect production. PA works, along with the measurement of multiple variables in field, which require computational systems for their storage and processing. Some devices have been developed for the measurement of nutritional stage [1], leaf area index [2], and soil analysis [3], which, due to their high cost, are not accessible to small agriculturalists. Mobile devices are computers with multiple sensors, control and variable-monitoring capacities, and can be used under field conditions using applications adjusted to the needs of agriculturalists, who already have this type of technology at hand.
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