APPLESHOW: sistema de informação geográfica para mapeamento da qualidade de maçã.

A agricultura de precisão vem se destacando nos últimos anos como a maneira de proporcionar ao produtor rural uma nova forma de gerenciamento da sua atividade, proporcionando melhores opções de tomada de decisão em busca de melhores relações de custo e benefício. A fruticultura brasileira, de um modo geral, era uma atividade que estava atrasada em relação ao uso da agricultura de precisão, principalmente se comparado às culturas de grãos, uma vez que os produtores careciam de softwares de apoio à tomada de decisão, dentre outras necessidades.bitstream/item/211579/1/Doc116b.pd

Yield mapping in fruit farming.

Due to the importance of increasing the quantity and quality of world agricultural production, the use of technologies to assist in production processes is essential. Despite this, a timid adoption by precision agriculture (PA) technologies is verified by the Brazilian fruit producers, even though it is one of the segments that had been stood out in recent years in the country's economy. In the PA context, yield maps are rich sources of information, especially by species harvested through machines, where the measurement of volumes harvested at georeferenced points is easier, allowing the generation of yield maps. In orchards intended for fresh fruit market, it is more difficult to generate yield data/maps, since it is linked to the volume harvested manually and, more importantly, to the quality of the fruit. One factor that makes it difficult to measure yield is that the harvest is done at different times because to maintain their quality, the fruits of an area are only when they reach the stipulated maturity point. To construct a system that permits of contemplating the complexity of the manual fruit harvesting processes, this paper aims to present a system that allows the yield mapping of hand-harvested orchards. The system is comprised of hardware components (intended to obtain the location of the harvester as well as the unloading record of their harvesting device at the unloading site) and software that allows processing the data obtained by the hardware device and create a mapped environment from which fruits were harvested, allowing the construction of yield maps. In addition to the yield maps, the system allows identifying the yield level of each worker performing the harvest by the number of discharges performed and the time spent. The system has been developed in partnership between the Federal Technological University of Paraná and Embrapa Grape & Wine and has been tested in apple orchards in southern Brazil. The system is expected to positively impact the sector by enabling monitoring of the quality and quantity of fruit from the orchards and providing more appropriate management aiming at the stability of the field production. Although tested only in apple cultivation, the system is promising for other segments of fruit growing, such as the production of pears, orange, fig, among others

Fruit fly electronic monitoring system.

Insects are a constant threat to agriculture, especially the cultivation of various types of fruits such as apples, pears, guava, etc. In this sense, it is worth mentioning the Anastrepha genus flies (known as fruit fly), responsible for billionaire losses in the fruit growing sector around the world, due to the severity of their attack on orchards. In Brazil, this type of pests has been controlled in most product areas by spraying insecticides, which due to the need for prior knowledge regarding the level of infestation and location of outbreaks, has shown reasonable efficiency in controlling and consequently in decreased loss caused by insects. However, the efficiency of this control can be improved, as the monitoring information of traps installed in the field is no longer obtained manually, because depending on the availability of the team, they are only checked weekly or at shorter intervals (3 days), the which can cause the rapid proliferation of insects during the periods between checks. . we present an electronic fruit fly monitoring system, consisting of an electronic trap installed in the field, responsible for capturing the insect, collecting its image, and transmitting the data, and a receiving base, located at the headquarters of the farm or place with internet access, which processes the data and confirms the pest identification in real time. Therefore, the fruit grower can monitor the totality of his orchards remotely by computer and generate maps to program the use of pesticides, allowing to control the infestation point by point, in its initial stage, and no longer in a complete area, if it so wishes. The hardware devices used for trap construction and an optoelectronic sensor developed are able to identify the entry of insects in the trap by a LED device (emitters and receivers). Identified the presence of the insect, the system triggers the triggering system of a camera located at the top of the trap that provides the images of the insect being captured. For system power savings in the orchard, it was verified that image processing should be load in a off-field server that receives the images from the trap. Streaming images for the server may be sending using transmission commercially available technologies such as Wi-Fi, 3G / 4G, or Zegbee, depending on area characteristics and network availability. Through the obtained and processed images, it was possibility recognize the insect species through of its wing patterns, avoiding false positive occurrences. The system is being tested in apple orchards in southern Brazil

Yield map generation of perennial crops for fresh consumption.

Yield mapping technologies can help to increase the quantity and quality of agricultural production. Current systems only focus on the quantifcation of the harvest, but the quality has equal or greater importance in some perennial crops and impacts directly on the financial proftability. Therefore, a system was developed to quantify and relate the quality obtained in the classifcation line with the plants of the orchard and for decision-making. The system is comprised of hardware, which obtains the location of the harvester bag during harvesting and unloading at the unloading site, and software that processes the collected data. The cloud of real-time data contributed from the diferent collectors (bins) allows the construction of yield maps, considering the multi-stage harvesting system. Further, the system enables the creation of a detailed map of the plants and fruits harvested. As the harvest focuses on quality, it takes place in stages, depending on the ripening of the fruits. In addition to the yield maps, the system allows identifcation of the efciency of each worker undertaking the harvest by the number of performed discharges and by the time spent. The system was developed in partnership with the Federal Technological University of Paraná and Embrapa Uva & Vinho and was tested in apple orchards in southern Brazil. Although the system was evaluated with only data from apple cultivation, monitoring the quality and quantifying other orchard fruits can positively impact the fruit sector

Appleshow: sistema de informação geográfica (SIG) de baixo custo para geração de mapas para a cultura da macieira.

O crescimento da necessidade de alimentos, a escassez de água, a maior preocupação com o ambiente e a busca pelo aumento da lucratividade são fatores que têm estimulado a adoção de técnicas otimizadas de manejo e gestão no contexto agrícola. Neste sentido, tecnologias relacionadas à agricultura de precisão (AP) permitiram a criação de sistemas voltados ao apoio nas tomadas de decisão, e o primeiro passo é o ordenamento das informações de forma clara, visível e compreensível a todos os interessados. O sistema APPLESHOW é um software de Sistema de Informações Geográficas (SIG), que nasceu da necessidade de organização de dados agrícolas em uma forma de mapas com capacidade de interposição e inter-relação de camadas para a análise mais próxima das informações ali dispostas. Seu diferencial é ser independente de um único datum, permitindo a geração de mapas a partir de um plano cartesiano criado pelo usuário com base na propriedade rural. Isso nasceu da sua principal aplicação projetada, que é analisar mapas de qualidade de frutas para consumo ?in natura? em pomares, que na maioria das vezes, pela sua forma de implantação, já são estabelecidos na forma de um sistema de coordenadas próprias, seguindo a linha do plantio e a posição de cada planta. Caso haja necessidade de correlacionar os dados a um mapa com datum, como o uso dos mapas gerados pelo APPLESHOW sobre imagens de satélite ou outros mapas georreferenciados, basta a conversão das coordenadas ao datum apropriado.XVI ENFRUTE 201

From Artificial Intelligence and Databases to Cognitive Computing: Past and Future Computer Engineering Research at UNIVPM

In the last decades, Computer Engineering has shown an impressive development and has become a pervasive protagonist in daily life and scientific research. Databases and Artificial Intelligence represent two of the major players in this development. Today, they are quickly converging towards a new, much more sophisticated and inclusive, paradigm, namely Cognitive Computing. This paradigm leverages Big Data and Artificial Intelligence to design approaches and build systems capable of (at least partially) reproducing human brain behavior. In this paradigm, an important role can be also played by Mathematical Programming. Cognitive systems are able to autonomously learn, reason, understand and process a huge amount of extremely varied data. Their ultimate goal is the capability of interacting naturally with their users. In the last 50 years, UNIVPM has played a leading role in scientific research in Databases and Artificial Intelligence, and, thanks to the acquired expertise, is going to play a key role in Cognitive Computing research in the future