Development of an open sensorized platform in a smart agriculture context: A vineyard support system for monitoring mildew disease

In recent years, some official reports, to produce best products regarding quality, quantity and economic conditions, recommend that the farming sector should benefit with new tools and techniques coming from Information and Communications Technology (ICT) realm. In this way, during last decade the deployment of sensing devices has increased considerably in the field of agriculture. This fact has led to a new concept called smart agriculture, and it contemplates activities such as field monitoring, which offer support to make decisions or perform actions, such as irrigation or fertilization. Apart from sensing devices, which use the Internet protocol to transfer data (Internet of Things), there are the so-called crop models, which are able to provide added value over the data provided by the sensors, with the aim of providing recommendations to farmers in decision-making and thus, increase the quality and quantity of their production. In this scenario, the current work uses a low-cost sensorized platform, capable of monitoring meteorological phenomena following the Internet of Things paradigm, with the goal to apply an alert disease model on the cultivation of the vine. The edge computing paradigm is used to achieve this objective; also our work follows some advances from GIScience to increase interoperability. An example of this platform has been deployed in a vineyard parcel located in the municipality of Vilafamés (Castelló Spain)

Development of an open sensorized platform in a smart agriculture context: A vineyard support system for monitoring mildew disease

In recent years, some offcial reports, to produce best products regarding quality, quantity and economic conditions, recommend that the farming sector should benefit with new tools and techniques coming from Information and Communications Technology (ICT) realm. In this way, during last decade the deployment of sensing devices has increased considerably in the field of agriculture. This fact has led to a new concept called smart agriculture, and it contemplates activities such as field monitoring, which offer support to make decisions or perform actions, such as irrigation or fertilization. Apart from sensing devices, which use the Internet protocol to transfer data (Internet of Things), there are the so-called crop models, which are able to provide added value over the data provided by the sensors, with the aim of providing recommendations to farmers in decision-making and thus, increase the quality and quantity of their production. In this scenario, the current work uses a low-cost sensorized platform, capable of monitoring meteorological phenomena following the Internet of Things paradigm, with the goal to apply an alert disease model on the cultivation of the vine. The edge computing paradigm is used to achieve this objective; also our work follows some advances from GIScience to increase interoperability. An example of this platform has been deployed in a vineyard parcel located in the municipality of Vilafamés (Castelló, Spain)

Data on records of environmental phenomena using low-cost sensors in vineyard smallholdings

Inadequate weather conditions are one of the main threats to the correct development of sensitive crops, where a bad situation can lead to greater stress on plants and their weakness against various diseases. This statement is especially decisive in the cultivation of the vineyard. Meteorological monitoring of vineyard parcels is vital to detect and prevent possible fungal diseases. The development of new Information and Communication Technologies, linked to the Smart Farming movement, together with the reduced cost of electronic components, have favoured a greater availability of meteorological monitoring stations to get to know first-class hand the state of the vineyard smallholdings. This work provides a set of over 750,000 environmental raw data records collected by low-cost Internet of Things nodes, primarily located within vineyard smallholdings. The published observations were collected between 2018-04-01 and 2018-10-31 and were validated in previous research to determine the data's reliability

An IoT Platform Based on Microservices and Serverless Paradigms for Smart Farming Purposes

Nowadays, the concept of “Everything is connected to Everything” has spread to reach increasingly diverse scenarios, due to the benefits of constantly being able to know, in real-time, the status of your factory, your city, your health or your smallholding. This wide variety of scenarios creates different challenges such as the heterogeneity of IoT devices, support for large numbers of connected devices, reliable and safe systems, energy efficiency and the possibility of using this system by third-parties in other scenarios. A transversal middleware in all IoT solutions is called an IoT platform. the IoT platform is a piece of software that works like a kind of “glue” to combine platforms and orchestrate capabilities that connect devices, users and applications/services in a “cyber-physical” world. In this way, the IoT platform can help solve the challenges listed above. This paper proposes an IoT agnostic architecture, highlighting the role of the IoT platform, within a broader ecosystem of interconnected tools, aiming at increasing scalability, stability, interoperability and reusability. For that purpose, different paradigms of computing will be used, such as microservices architecture and serverless computing. Additionally, a technological proposal of the architecture, called SEnviro Connect, is presented. This proposal is validated in the IoT scenario of smart farming, where five IoT devices (SEnviro nodes) have been deployed to improve wine production. A comprehensive performance evaluation is carried out to guarantee a scalable and stable platform

Reliability evaluation of the data acquisition potential of a low-cost climatic network for applications in agriculture

Trilles, S., Juan, P., Díaz-Avalos, C., Ribeiro, S., & Painho, M. (2020). Reliability evaluation of the data acquisition potential of a low-cost climatic network for applications in agriculture. Sensors (Switzerland), 20(22), 1-27. [6597]. https://doi.org/10.3390/s20226597Temperature, humidity and precipitation have a strong influence on the generation of diseases in different crops, especially in vine. In recent years, advances in different disciplines have enabled the deployment of sensor nodes on agricultural plots. These sensors are characterised by a low cost and so the reliability of the data obtained from them can be compromised, as they are built from low-confidence components. In this research, two studies were carried out to determine the reliability of the data obtained by different SEnviro nodes installed in vineyards. Two networks of meteorological stations were used to carry out these studies, one official and the other professional. The first study was based on calculating the homogenisation of the data, which was performed using the Climatol tool. The second study proposed a similarity analysis using cross-correlation. The results showed that the low-cost node can be used to monitor climatic conditions in an agricultural area in the central zone of the province of Castelló (Spain) and to obtain reliable observations for use in previously published fungal disease models.publishersversionpublishe

A comparative study in the standardisation of IoT devices using geospatial web standards

Although billions of devices are embedded in the World Wide Web through the Internet of Things, there is still a lack of a common, interoperable way to connect them and make them interact seamlessly. IoT has also found its way into the spatial web. Environmental monitoring and sensing platforms connected over the web by wireless sensor networks are now a common way to monitor natural phenomena. This study compares two open Web Standards ( OGC’s Sensor Observation Service and SensorThings API ) from the geospatial point of view. An IoT platform, called SEnviro , is used to integrate and evaluate implementations for each standard and contrast their qualitative and quantitative traits. The results of the study show that the SensorThings API proves to be the adequate Web Standard for IoT applications in terms of interoperability. It outperforms the contesting Web Standard in terms of flexibility and scalability, which strongly impacts on developer and user experience

Ag-IoT for crop and environment monitoring: Past, present, and future

CONTEXT: Automated monitoring of the soil-plant-atmospheric continuum at a high spatiotemporal resolution is a key to transform the labor-intensive, experience-based decision making to an automatic, data-driven approach in agricultural production. Growers could make better management decisions by leveraging the real-time field data while researchers could utilize these data to answer key scientific questions. Traditionally, data collection in agricultural fields, which largely relies on human labor, can only generate limited numbers of data points with low resolution and accuracy. During the last two decades, crop monitoring has drastically evolved with the advancement of modern sensing technologies. Most importantly, the introduction of IoT (Internet of Things) into crop, soil, and microclimate sensing has transformed crop monitoring into a quantitative and data-driven work from a qualitative and experience-based task. OBJECTIVE: Ag-IoT systems enable a data pipeline for modern agriculture that includes data collection, transmission, storage, visualization, analysis, and decision-making. This review serves as a technical guide for Ag-IoT system design and development for crop, soil, and microclimate monitoring. METHODS: It highlighted Ag-IoT platforms presented in 115 academic publications between 2011 and 2021 worldwide. These publications were analyzed based on the types of sensors and actuators used, main control boards, types of farming, crops observed, communication technologies and protocols, power supplies, and energy storage used in Ag-IoT platforms

III Workshop on disruptive information and communication technologies for innovation and digital transformation

Producción CientíficaCon la aparición de tecnologías disruptivas como Internet de las Cosas (IoT), Industria 4.0 o Realidad Virtual (VR), entre otras, cada vez hay más servicios y dispositivos con diferentes características que se interconectan mediante redes de comunicaciones y necesitan capacidades de computación y almacenamiento con las que, en principio, no cuentan. Para superar este problema se propuso la solución de computación en la nube (cloud computing), que consiste básicamente en confiar las tareas más pesadas a un servidor central con alta potencia computacional. A primera vista este enfoque resuelve el problema, pero, como generalmente estos servidores centrales (data centers) se encuentran lejos de los dispositivos finales, aparecen nuevos problemas, especialmente con respecto al aumento de la latencia. La siguiente propuesta es el MEC (Multi-access Edge Computing, o computación de acceso múltiple en el borde), que es similar a la computación en la nube, pero se basa en servidores más cercanos a los usuarios, esto es, "en el borde" de la red de acceso, en lugar de servidores lejanos "en la nube". Este artículo ofrece una revisión de las principales características, de MEC, haciendo énfasis en su aplicación en escenarios como muchas regiones hispano-portuguesas, con baja densidad de población, grandes distancias entre ciudades o pueblos, y con un importante porcentaje de entornos rurales.Fondo Europeo de Desarrollo Regional FEDER a través del proyecto DISRUPTIVE del Programa Interreg V-A España-Portugal (POCTEP) 2014-2020Ministerio de Ciencia, Innovación y Universidades (grants (ONOFRE-2: TEC2017-84423-C3-1- P and Go2Edge: RED2018-102585-T)Junta de Castilla y León - Fondo Europeo de Desarrollo Regional (project VA231P20

The digitization of agricultural industry – a systematic literature review on agriculture 4.0

Agriculture is considered one of the most important sectors that play a strategic role in ensuring food security. However, with the increasing world's population, agri-food demands are growing — posing the need to switch from traditional agricultural methods to smart agriculture practices, also known as agriculture 4.0. To fully benefit from the potential of agriculture 4.0, it is significant to understand and address the problems and challenges associated with it. This study, therefore, aims to contribute to the development of agriculture 4.0 by investigating the emerging trends of digital technologies in the agricultural industry. For this purpose, a systematic literature review based on Protocol of Preferred Reporting Items for Systematic Reviews and Meta-Analyses is conducted to analyse the scientific literature related to crop farming published in the last decade. After applying the protocol, 148 papers were selected and the extent of digital technologies adoption in agriculture was examined in the context of service type, technology readiness level, and farm type. The results have shown that digital technologies such as autonomous robotic systems, internet of things, and machine learning are significantly explored and open-air farms are frequently considered in research studies (69%), contrary to indoor farms (31%). Moreover, it is observed that most use cases are still in the prototypical phase. Finally, potential roadblocks to the digitization of the agriculture sector were identified and classified at technical and socio-economic levels. This comprehensive review results in providing useful information on the current status of digital technologies in agriculture along with prospective future opportunities