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| Author | Miguel Realpe; Jonathan S. Paillacho Corredores; Joe Saverio & Allan Alarcon | ||||
| Title | Open Source system for identification of corn leaf chlorophyll contents based on multispectral images | Type | Conference Article | ||
| Year | 2019 | Publication | International Conference on Applied Technologies (ICAT 2019); Quito, Ecuador | Abbreviated Journal | |
| Volume | Issue | Pages  |
572-581 | ||
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| Abstract | It is important for farmers to know the level of chlorophyll in plants since this depends on the treatment they should give to their crops. There are two common classic methods to get chlorophyll values: from laboratory analysis and electronic devices. Both methods obtain the chlorophyll level of one sample at a time, although they can be destructive. The objective of this research is to develop a system that allows obtaining the chlorophyll level of plants using images. Python programming language and different libraries of that language were used to develop the solution. It was decided to implement an image labeling module, a simple linear regression and a prediction module. The first module was used to create a database that links the values of the images with those of chlorophyll, which was then used to obtain linear regression in order to determine the relationship between these variables. Finally, the linear regression was used in the prediction system to obtain chlorophyll values from the images. The linear regression was trained with 92 images, obtaining a root-mean-square error of 7.27 SPAD units. While the testing was perform using 10 values getting a maximum error of 15.5%. It is concluded that the system is appropriate for chlorophyll contents identification of corn leaves in field tests. However, it can also be adapted for other measurement and crops. The system can be downloaded at github.com/JoeSvr95/NDVI-Checking [1]. |
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| Notes | Approved | no | |||
| Call Number | gtsi @ user @ | Serial | 116 | ||
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| Author | Miguel A. Murillo, Julio E. Alvia, & Miguel Realpe | ||||
| Title | Beyond visual and radio line of sight UAVs monitoring system through open software in a simulated environment. | Type | Conference Article | ||
| Year | 2021 | Publication | The 2nd International Conference on Applied Technologies (ICAT 2020), diciembre 2-4. Communications in Computer and Information Science | Abbreviated Journal | |
| Volume | 1388 | Issue | Pages |
629-642 | |
| Keywords | Drone, Open Source, Internet, Web Application, Web Server, SITL, Line of sight, UAV. | ||||
| Abstract | The problem of loss of line of sight when operating drones has be-come a reality with adverse effects for professional and amateur drone opera-tors, since it brings technical problems such as loss of data collected by the de-vice in one or more instants of time during the flight and even misunderstand-ings of legal nature when the drone flies over prohibited or private places. This paper describes the implementation of a drone monitoring system using the In-ternet as a long-range communication network in order to avoid the problem of loss of communication between the ground station and the device. For this, a simulated environment is used through an appropriate open software tool. The operation of the system is based on a client that makes requests to a server, the latter in turn communicates with several servers, each of which has a drone connected to it. In the proposed system when a drone is ready to start a flight, its server informs the main server of the system, which in turn gives feedback to the client informing it that the device is ready to carry out the flight; this way customers can send a mission to the device and keep track of its progress in real time on the screen of their web application. | ||||
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| Language | English | Summary Language | Original Title | ||
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 186 | ||
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| Author | Emmanuel Moran, Boris Vintimilla & Miguel Realpe | ||||
| Title | Towards a Robust Solution for the Supermarket Shelf Audit Problem. | Type | Conference Article | ||
| Year | 2023 | Publication | Proceedings of the International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications VISIGRAPP 2023 | Abbreviated Journal | |
| Volume | Issue | Pages |
912 - 919 | ||
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| Notes | Approved | no | |||
| Call Number | cidis @ cidis @ | Serial | 204 | ||
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