Business Intelligence in the Vineyard

The evolution that is nowadays taking place in the information and communication fields, namely in mobile computing and remote monitoring, constitutes a very interesting challenge to the agricultural sector. This reality places agronomic knowledge in centre stage as these technologies are dramatically improving data collection and storage capacities, challenging the farmers and the agricultural field experts to develop processes that efficiently transform data into information and knowledge and are able to support the everyday decision making at farm level. In this work we will present a demonstration project under way in a vineyard in Portugal where we are exploring the potential of the most recent technological innovations available in the market to build the i-Farm, the information and knowledge society intelligent farm. i-Farm (intelligent farm) applies at farm level the potential offered by using in an integrated way mobile solutions, sensor networks, wireless communication and digital imagery materialized in a information system that supports farmer real time decision making in the field and in the office. The i-Farm project creates a unique knowledge repository containing information from multiple sources (crop, environment, soil, operations, market, etc.) enabling accurate and timely decisions. For the project development a Business Intelligence approach is used. In the context of this paper this broad term is used to refer to the process of aggregating, processing and building rich and relevant information which is made available dynamically in real time to managers in an interactive way to support decisions and planning activitiesinfo:eu-repo/semantics/publishedVersio

Decision making models embedded into a web-based tool for assessing pest infestation risk

Current practices in agricultural management involve the application of rules and techniques to ensure high quality and environmentally friendly production. Based on their experience, agricultural technicians and farmers make critical decisions affecting crop growth while considering several interwoven agricultural, technological, environmental, legal and economic factors. In this context, decision support systems and the knowledge models that support them, enable the incorporation of valuable experience into software systems providing support to agricultural technicians to make rapid and effective decisions for efficient crop growth. Pest control is an important issue in agricultural management due to crop yield reductions caused by pests and it involves expert knowledge. This paper presents a formalisation of the pest control problem and the workflow followed by agricultural technicians and farmers in integrated pest management, the crop production strategy that combines different practices for growing healthy crops whilst minimising pesticide use. A generic decision schema for estimating infestation risk of a given pest on a given crop is defined and it acts as a metamodel for the maintenance and extension of the knowledge embedded in a pest management decision support system which is also presented. This software tool has been implemented by integrating a rule-based tool into web-based architecture. Evaluation from validity and usability perspectives concluded that both agricultural technicians and farmers considered it a useful tool in pest control, particularly for training new technicians and inexperienced farmers

A Smart Decision System for Digital Farming

[EN] New technologies have the potential to transform agriculture and to reduce environmental impact through a green revolution. Internet of Things (IoT)-based application development platforms have the potential to run farm management tools capable of monitoring real-time events when integrated into interactive innovation models for fertirrigation. Their capabilities must extend to flexible reconfiguration of programmed actions. IoT platforms require complex smart decision-making systems based on data-analysis and data mining of big data sets. In this paper, the advantages are demonstrated of a powerful tool that applies real-time decisions from data such as variable rate irrigation, and selected parameters from field and weather conditions. The field parameters, the index vegetation (estimated using aerial images), and the irrigation events, such as flow level, pressure level, and wind speed, are periodically sampled. Data is processed in a decision-making system based on learning prediction rules in conjunction with the Drools rule engine. The multimedia platform can be remotely controlled, and offers a smart farming open data network with shared restriction levels for information exchange oriented to farmers, the fertilizer provider, and agricultural technicians that should provide the farmer with added value in the form of better decision making or more efficient exploitation operations and management.This paper has been partially supported by the European Union through the ERANETMED (Euromediterranean Cooperation through ERANET joint activities and beyond) project ERANETMED3-227 SMARTWATIR and by the "Ministerio de Ciencia, Innovacion y Universidades" through the "Ayudas para la adquisicion de equipamiento cientifico-tecnico, Subprograma estatal de infraestructuras de investigacion y equipamiento cientifico-tecnico (plan Estatal i+d+i 2017-2020)" (project EQC2018-004988-P).Cambra-Baseca, C.; Sendra, S.; Lloret, J.; Tomás Gironés, J. (2019). A Smart Decision System for Digital Farming. Agronomy. 9(5):1-19. https://doi.org/10.3390/agronomy9050216S11995Atzori, L., Iera, A., & Morabito, G. (2010). The Internet of Things: A survey. Computer Networks, 54(15), 2787-2805. doi:10.1016/j.comnet.2010.05.010Chen, M., Mao, S., & Liu, Y. (2014). Big Data: A Survey. Mobile Networks and Applications, 19(2), 171-209. doi:10.1007/s11036-013-0489-0De Mauro, A., Greco, M., & Grimaldi, M. (2016). A formal definition of Big Data based on its essential features. Library Review, 65(3), 122-135. doi:10.1108/lr-06-2015-0061Haghverdi, A., Leib, B. G., Washington-Allen, R. A., Ayers, P. D., & Buschermohle, M. J. (2015). Perspectives on delineating management zones for variable rate irrigation. Computers and Electronics in Agriculture, 117, 154-167. doi:10.1016/j.compag.2015.06.019Vazquez, J. I., Ruiz-de-Garibay, J., Eguiluz, X., Doamo, I., Renteria, S., & Ayerbe, A. (2010). Communication architectures and experiences for web-connected physical Smart objects. 2010 8th IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops). doi:10.1109/percomw.2010.5470521Misra, S., Barthwal, R., & Obaidat, M. S. (2012). Community detection in an integrated Internet of Things and social network architecture. 2012 IEEE Global Communications Conference (GLOBECOM). doi:10.1109/glocom.2012.6503350Atzori, L., Iera, A., & Morabito, G. (2014). From «smart objects» to «social objects»: The next evolutionary step of the internet of things. IEEE Communications Magazine, 52(1), 97-105. doi:10.1109/mcom.2014.6710070Agrivi App http://www.agrivi.com/en/reApollo Project http://apollo-h2020.eu/Cambra, C., Sendra, S., Lloret, J., & Lacuesta, R. (2018). Smart System for Bicarbonate Control in Irrigation for Hydroponic Precision Farming. Sensors, 18(5), 1333. doi:10.3390/s18051333Ortiz, A. M., Hussein, D., Park, S., Han, S. N., & Crespi, N. (2014). The Cluster Between Internet of Things and Social Networks: Review and Research Challenges. IEEE Internet of Things Journal, 1(3), 206-215. doi:10.1109/jiot.2014.2318835Ji, Z., Ganchev, I., O’Droma, M., Zhao, L., & Zhang, X. (2014). A Cloud-Based Car Parking Middleware for IoT-Based Smart Cities: Design and Implementation. Sensors, 14(12), 22372-22393. doi:10.3390/s141222372Ning, H., & Wang, Z. (2011). Future Internet of Things Architecture: Like Mankind Neural System or Social Organization Framework? IEEE Communications Letters, 15(4), 461-463. doi:10.1109/lcomm.2011.022411.11012

Internal outset:Exploring empirical and philosophical implications of the free-energy principle

The present dissertation took the free-energy principle (FEP) as its starting point, from which we tried to draw both philosophical and empirical consequences. Both chapter 2 and 3 departed from the idea that conscious perception depends on global amplification of sensory input, and that the basal ganglia (BG) and its irrigation by dopamine play a crucial role in gating information, conscious access, and the selection of a relevant internal model given available sensory data. The BG are thought to play this role due to their modulatory influence on thalamocortical connectivity. Because much of the evidence implicating the BG in these processes in humans is correlational, we explored two ways of manipulating BG activity experimentally. Chapter 4 investigates the philosophical heritage implicitly touched on by the FEP, which provides an alternative philosophical and historical background for present-day research in cognitive neuroscience. Friston’s FEP has been received with great enthusiasm. With good reason: it not only makes the bold claim to a unifying theory of the brain, but it is presented as an a priori principle applicable to living systems in general. In this paper, we set out to show how the breadth of scope of Friston’s framework converges with the dialectics of Georg Hegel. Through an appeal to the work of Catherine Malabou, we aimed to demonstrate how Friston not only reinvigorates Hegelian dialectics from the perspective of neuroscience, but that the implicit alignment with Hegel necessitates a reading of the FEP from the perspective of Hegel’s speculative philosophy. It is this reading that moves beyond the discussion between cognitivism and enactivism surrounding Friston’s framework; beyond the question whether the organism is a secluded entity separated from its surroundings, or whether it is a dynamical system characterized by perpetual openness and mutual exchange. From a Hegelian perspective, it is the tension between both positions itself that is operative at the level of the organism; as a contradiction the organism sustains over the course of its life. Not only does the organism’s secluded existence depend on a perpetual relation with its surroundings, but the condition for there to be such a relation is the existence of a secluded entity. We intended to show how this contradiction – tension internalized – is at the center of Friston’s anticipatory organism; how it is this contradiction that grounds the perpetual process of free energy minimization. Chapter 5 is the report of a study attempting to contrast the FEP’s perspective with that of traditional cognitive neuroscience. While the FEP casts the brain as an organism’s predictive model of how its world works and will continue to work in the future in which action is afforded a central place, research on the brain’s predictive capacities remains beholden to traditional research practices in which participants are passively shown stimuli without their active involvement (as we also did in Chapters 2 and 3). The current study is an investigation into ways in which self-generated predictions may differ from externally induced predictions. Participants completed a volatile spatial attention task under both conditions (externally/cue-induced, internally/action-induced) on different days. We used the Hierarchical Gaussian Filter, an approximate Bayesian inference model, to determine subject-specific parameters of belief-updating and inferred volatility. We found preliminary evidence in support of self-generated predictions incurring a larger reaction time cost when violated compared to predictions induced by sensory cue, which translated to participants’ increased sensitivity to changes in environmental volatility. Our results suggest that internally generated predictions may be afforded more weight, but these results are complicated by session order and duration effects, as well as a lack of statistical power

Effort Estimation for Service-Oriented Computing Environments

The concept of service in Service-Oriented Architecture (SOA) makes possible to introduce other ideas like service composition, governance and virtualization. Each of these ideas, when exercised to an enterprise level, provides benefits in terms of cost and performance. These ideas bring many new opportunities for the project managers in making the estimates of effort required to produce SOA systems. This is because the SOA systems are different from traditional software projects and there is a lack of efficient metrics and models for providing a high level of confidence in effort estimation. Thus, in this paper, an efficient estimation methodology has been presented based on analyzing the development phases of past SOA based software systems. The objective of this paper is twofold: first, to study and analyze the development phases of some past SOA based systems; second, to propose estimation metrics based on these analyzed parameters. The proposed methodology is facilitated from the use of four regression(s) based estimation models. The validation of the proposed methodology is cross checked by comparing the predictive accuracy, using some commonly used performance measurement indicators and box-plots evaluation. The evaluation results of the study (using industrial data collected from 10 SOA based software systems) show that the effort estimates obtained using the multiple linear regression model are more accurate and indicate an improvement in performance than the other used regression models

A Service Discovery Solution for Edge Choreography-Based Distributed Embedded Systems

[EN] This paper presents a solution to support service discovery for edge choreography based distributed embedded systems. The Internet of Things (IoT) edge architectural layer is composed of Raspberry Pi machines. Each machine hosts different services organized based on the choreography collaborative paradigm. The solution adds to the choreography middleware three messages passing models to be coherent and compatible with current IoT messaging protocols. It is aimed to support blind hot plugging of new machines and help with service load balance. The discovery mechanism is implemented as a broker service and supports regular expressions (Regex) in message scope to discern both publishing patterns offered by data providers and client services necessities. Results compare Control Process Unit (CPU) usage in a request¿response and datacentric configuration and analyze both regex interpreter latency times compared with a traditional message structure as well as its impact on CPU and memory consumption.The choreography engine was developed and supported by the SABIEN research group of the Universitat Politecnica de Valencia (http://www.sabien.upv.es/en/).Blanc Clavero, S.; Bayo-Monton, JL.; Palanca-Barrio, S.; Arreaga-Alvarado, NX. (2021). A Service Discovery Solution for Edge Choreography-Based Distributed Embedded Systems. Sensors. 21(2):1-19. https://doi.org/10.3390/s21020672S11921

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio