In-field hyperspectral imaging dataset of Manzanilla and Gordal olive varieties throughout the season

Because spectral technology has exhibited benefits in food-related applications, an increasing amount of effort is being dedicated to develop new food-related spectral technologies. In recent years, the use of remote sensing or unmanned aerial vehicles for precision agriculture has increased. As spectral technology continues to improve, portable spectral devices become available in the market, offering the possibility of realising in-field monitoring. This study demonstrates hyperspectral imaging and spectral olive signatures of the Manzanilla and Gordal cultivars analysed throughout the table-olive season from May to September. The data were acquired using an in-field technique and sampled via a non-destructive approach. The olives were monitored periodically during the season using a hyperspectral camera. A white reference was used to normalise the illumination variability in the spectra. The acquired data were saved in files named raw, normalised, and processed data. The normalised data were calculated by the sensor by correcting the white and black levels using the acquired reflectance values. The olive spectral signature of the images is saved in the processed data files. The images were labelled and processed using an algorithm to retrieve the olive spectral signatures. The results were stored as a chart with 204 columns and ‘n’ rows. Each row represents the pixel of an olive in the image, and the columns contain the reflectance information at that specific band. These data provide information about two olive cultivars during the season, which can be used for various research purposes. Statistical and artificial intelligence approaches correlate spectral signatures with olive characteristics such as growth level, organoleptic properties, or even cultivar classification.Hermanos Donaire Ibáñez Agrícola, SC and the Regulatory Council of the PGI Manzanilla and Gordal Olives from Sevill

Optimización de vida útil de baterías en aplicaciones de IoT con recarga mediante fuentes renovables

La gestión energética en dispositivos IoT es un aspecto clave, por el gran número de dispositivos y su difícil acceso para labores de mantenimiento cuando están instalados en campo. Mediante la utilización de procesos de bajo consumo y técnicas de “Energy Harvesting”, se puede lograr alargar la vida útil de estos dispositivos, teniendo en cuenta que estas fuentes de energía, generalmente renovables, no están siempre disponibles, por lo que para conseguir un uso eficiente es necesario ajustar diversos parámetros del sistema de almacenamiento. A partir de estas premisas, un sistema dinámico que ajuste estos parámetros en función de la disponibilidad del recurso energético puede resultar muy relevante para la mejora de la fiabilidad de los nodos IoT. Mediante el modelado de los sistemas de adquisición de energía y de almacenamiento energético basados en litio, se han obtenido estimaciones de vida útil de la batería. Además, mediante la variación de parámetros de entrada del modelo de batería se puede lograr utilizar el recurso energético de forma óptima cuando este esté disponible, además de aumentar la duración de la batería. Por ello, una gestión dinámica de los parámetros del sistema puede otorgar una mayor vida útil para dispositivos IoT desplegados en campo

Sistema ciber-físico aplicado al mantenimiento predictivo en el sector hotelero

El sector turístico es clave para la economía española, por lo que desarrollos e innovaciones en términos de digitalización son necesarios para mejorarlo. Para ello, se plantea la utilización de sistemas ciber-físicos, los cuales parten del concepto de la virtualización de la planta mediante la adquisición de los estados de los equipos físicos. A partir de esta esta información, y mediante algoritmos específicos, se realizan acciones para cerrar los lazos de control, fomentando la digitalización del sector industrial. En este sistema ciber-físico se va a utilizar una aplicación de mantenimiento predictivo de los equipos de clima. Se ha desarrollado una red de adquisición de datos con algoritmos que se encarguen de la gestión y procesado de datos. Estos sistemas tienen conectividad a internet. Por último, cerrando el lazo de control, se actúa sobre el sistema cambiando el estado físico de los equipos. Este sistema se ha desplegado sobre una instalación hotelera específica, pudiendo ser interoperable con tecnologías de terceros

Identification of Olives Using In-Field Hyperspectral Imaging with Lightweight Models

During the growing season, olives progress through nine different phenological stages, starting with bud development and ending with senescence. During their lifespan, olives undergo changes in their external color and chemical properties. To tackle these properties, we used hyperspectral imaging during the growing season of the olives. The objective of this study was to develop a lightweight model capable of identifying olives in the hyperspectral images using their spectral information. To achieve this goal, we utilized the hyperspectral imaging of olives while they were still on the tree and conducted this process throughout the entire growing season directly in the field without artificial light sources. The images were taken on-site every week from 9:00 to 11:00 a.m. UTC to avoid light saturation and glitters. The data were analyzed using training and testing classifiers, including Decision Tree, Logistic Regression, Random Forest, and Support Vector Machine on labeled datasets. The Logistic Regression model showed the best balance between classification success rate, size, and inference time, achieving a 98% F1-score with less than 1 KB in parameters. A reduction in size was achieved by analyzing the wavelengths that were critical in the decision making, reducing the dimensionality of the hypercube. So, with this novel model, olives in a hyperspectral image can be identified during the season, providing data to enhance a farmer’s decision-making process through further automatic applications

Design and Evaluation of a Heterogeneous Lightweight Blockchain-Based Marketplace

The proposal of this paper is to introduce a low-level blockchain marketplace, which is a blockchain where participants could share its power generation and demand. To achieve this implementation in a secure way for each actor in the network, we proposed to deploy it over efficient and generic low-performance devices. Thus, they are installed as IoT devices, registering measurements each fifteen minutes, and also acting as blockchain nodes for the marketplace. Nevertheless, it is necessary that blockchain is lightweight, so it is implemented as a specific consensus protocol that allows each node to have enough time and computer requirements to act both as an IoT device and a blockchain node. This marketplace will be ruled by Smart Contracts deployed inside the blockchain. With them, it is possible to make registers for power generation and demand. This low-level marketplace could be connected to other services to execute matching algorithms from the data stored in the blockchain. Finally, a real test-bed implementation of the marketplace was tested, to confirm that it is technically feasible

Algoritmos evolutivos implementados en robótica

En este trabajo se presenta la programación de un algoritmo evolutivo realizado en el lenguaje C++ para la resolución de distintos problemas en los que se busca escoger los mejores valores para un conjunto de variables definidas de un problema. La idea principal consiste en que estas variables estarán contenidas en un vector para cada individuo que tengamos, llamado cromosoma. El programa comenzará inicializando estos vectores de forma que comience una simulación y se mida cómo de bueno es ese individuo a partir de una métrica definida que variará en función del tipo de problema que tengamos. Estos mejores individuos serán seleccionados para la generación de la siguiente población, generados por cruce y mutación de los padres, los mejores de la anterior generación. Este proceso se repetirá hasta llegar a un resultado que consideremos óptimo o en su defecto hasta que el programa finalice después de simular un cierto número de generaciones. Como prueba de concepto, esta metodología se ha implementado en el aprendizaje de un robot cuadrúpedo para caminar en el entorno Webots

Análisis de consumo energético de redes Blockchain en dispositivos embebidos de bajo consumo

Se presenta un estudio para la integración de dispositivos embebidos IoT (Internet of Things), que son capaces de gestionar la información proveniente de sensores de forma eficiente con un mínimo coste computacional, con la tecnología Blockchain, que permite garantizar la veracidad de los datos, generalmente a cambio de un alto coste computacional. Se analiza una red Blockchain ejecutada sobre IoT, así como las variables que definen la capacidad que tiene dicha red para almacenar la información, y su consumo energético

Virtual Laboratory for Digital Signal Processing

Digital Signal Processor is a useful tool for learning and practice about filters for digital signals. The practices of the subject “Procesado Digital de Señales” made the students learn how to use it, and how to run some algorithms. But the hardware and laboratory restrictions and the complexity of subject provoked some availability problems of digital signal processor platforms. An effective solution is the creation of a virtual laboratory which connects to the real hardware, as explained in this document

A Coffee Berry Borer (Coleoptera: Curculionidae: Scolytinae) Bibliography

Native to Africa, the coffee berry borer, Hypothenemus hampei (Ferrari) (Coleoptera: Curculionidae: Scolytinae), has gradually invaded most coffee-growing areas worldwide. Adult females colonize the coffee berry and oviposit within galleries in the coffee seeds. Larvae and adults consume the seeds, resulting in drastic reductions in yields and quality, negatively affecting the income of approximately 20 million coffee-growing families (~100 million people) in ~80 countries, with losses surpassing more than $500 million annually (Vega et al. 2015). It has become evident that the coffee berry borer scientific community could greatly benefit from having access to a bibliography of the literature related to the insect. Such an information source would allow scientists to find out what research areas have been explored throughout the many coffee berry borer-infested countries after more than 100 years of research on the topic. It could also help to direct lead future research efforts into novel areas, and away from topics and ideas that have been thoroughly investigated in the past