Monitoring system for agronomic variables based in WSN technology on cassava crops

Agriculture, and natural resources associated to its development like water, soils and forests, have a relevant role in the future of countries and environmental conservation. The optimization of these resources is made with the implementation of technological strategies and tools that make it possible. In this sense, we developed a monitoring prototype for agronomic variables in cassava crops (Manihot Esculenta Crantz) in the Atlántico department (Colombia) based in WSN using Z1 motes as hardware platform and the temperature and soil moisture sensor SHT11. The operating system used was Contiki, and the routing protocol was RPL. The Network Performance Metrics evaluated were packet loss, RSSI (Received Signal Strength Indicator), LQI (Link Quality Indicator) and network convergence time. Then, a deployment model using Schläfli notation to determine the location and number of nodes, also we calculated the coverage range of the nodes to keep network uniformity. With these calculations, we obtained the linkage budgets between specks, and results were validated with RadioMobile software. Then, test fields were made in a cassava crop located in the city of Manati, Atlántico. Finally, with the help of server client architecture XAMPP, all data was stored and visualized through SIMCA (Agricultural Crop Information and Monitoring System), a web application developed by authors

Received strength signal intensity performance analysis in wireless sensor network using Arduino platform and XBee wireless modules

Today, through the monitoring of agronomic variables, the wireless sensor networks are playing an increasingly important role in precision agriculture. Among the emerging technologies used to develop prototypes related to wireless sensor network, we find the Arduino platform and XBee radio modules from the DIGI Company. In this article, based on field tests, we conducted a comparative analysis of received strength signal intensity levels, calculation of path loss with “log-normal shadowing” and free-space path loss models. In addition, we measure packet loss for different transmission, distances and environments with respect to an “Arduino Mega” board, and radio modules XBee PRO S1 and XBee Pro S2. The tests for the packet loss and received strength signal intensity level show the best performance for the XBee Pro S2 in the indoor, outdoor, and rural scenarios

Utilization of Internet of Things and wireless sensor networks for sustainable smallholder agriculture

Agriculture is the economy’s backbone for most developing countries. Most of these countries suffer from insufficient agricultural production. The availability of real-time, reliable and farm-specific information may significantly contribute to more sufficient and sustained production. Typically, such information is usually fragmented and often does fit one-on-one with the farm or farm plot. Automated, precise and affordable data collection and dissemination tools are vital to bring such information to these levels. The tools must address details of spatial and temporal variability. The Internet of Things (IoT) and wireless sensor networks (WSNs) are useful technology in this respect. This paper investigates the usability of IoT and WSN for smallholder agriculture applications. An in-depth qualitative and quantitative analysis of relevant work over the past decade was conducted. We explore the type and purpose of agricultural parameters, study and describe available resources, needed skills and technological requirements that allow sustained deployment of IoT and WSN technology. Our findings reveal significant gaps in utilization of the technology in the context of smallholder farm practices caused by social, economic, infrastructural and technological barriers. We also identify a significant future opportunity to design and implement affordable and reliable data acquisition tools and frameworks, with a possible integration of citizen science

Radio wave attenuation measurement system based on RSSI for precision agriculture: application to tomato greenhouses

Precision agriculture and smart farming are concepts that are acquiring an important boom due to their relationship with the Internet of Things (IoT), especially in the search for new mechanisms and procedures that allow for sustainable and efficient agriculture to meet future demand from an increasing population. Both concepts require the deployment of sensor networks that monitor agricultural variables for the integration of spatial and temporal agricultural data. This paper presents a system that has been developed to measure the attenuation of radio waves in the 2.4 GHz free band (ISM- Industrial, Scientific and Medical) when propagating inside a tomato greenhouse based on the received signal strength indicator (RSSI), and a procedure for using the system to measure RSSI at different distances and heights. The system is based on Zolertia Re-Mote nodes with the Contiki operating system and a Raspberry Pi to record the data obtained. The receiver node records the RSSI at different locations in the greenhouse with the transmitter node and at different heights. In addition, a study of the radio wave attenuation was measured in a tomato greenhouse, and we publish the corresponding obtained dataset in order to share with the research community

Ensuring Agricultural Sustainability through Remote Sensing in the Era of Agriculture 5.0

This work was supported by the projects: "VIRTUOUS" funded by the European Union's Horizon 2020 Project H2020-MSCA-RISE-2019. Ref. 872181, "SUSTAINABLE" funded by the European Union's Horizon 2020 Project H2020-MSCA-RISE-2020. Ref. 101007702 and the "Project of Excellence" from Junta de Andalucia 2020. Ref. P18-H0-4700. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Timely and reliable information about crop management, production, and yield is considered of great utility by stakeholders (e.g., national and international authorities, farmers, commercial units, etc.) to ensure food safety and security. By 2050, according to Food and Agriculture Organization (FAO) estimates, around 70% more production of agricultural products will be needed to fulfil the demands of the world population. Likewise, to meet the Sustainable Development Goals (SDGs), especially the second goal of “zero hunger”, potential technologies like remote sensing (RS) need to be efficiently integrated into agriculture. The application of RS is indispensable today for a highly productive and sustainable agriculture. Therefore, the present study draws a general overview of RS technology with a special focus on the principal platforms of this technology, i.e., satellites and remotely piloted aircrafts (RPAs), and the sensors used, in relation to the 5th industrial revolution. Nevertheless, since 1957, RS technology has found applications, through the use of satellite imagery, in agriculture, which was later enriched by the incorporation of remotely piloted aircrafts (RPAs), which is further pushing the boundaries of proficiency through the upgrading of sensors capable of higher spectral, spatial, and temporal resolutions. More prominently, wireless sensor technologies (WST) have streamlined real time information acquisition and programming for respective measures. Improved algorithms and sensors can, not only add significant value to crop data acquisition, but can also devise simulations on yield, harvesting and irrigation periods, metrological data, etc., by making use of cloud computing. The RS technology generates huge sets of data that necessitate the incorporation of artificial intelligence (AI) and big data to extract useful products, thereby augmenting the adeptness and efficiency of agriculture to ensure its sustainability. These technologies have made the orientation of current research towards the estimation of plant physiological traits rather than the structural parameters possible. Futuristic approaches for benefiting from these cutting-edge technologies are discussed in this study. This study can be helpful for researchers, academics, and young students aspiring to play a role in the achievement of sustainable agriculture.European Commission 101007702 872181Junta de Andalucia P18-H0-470

Integration of ICT and Artificial Intelligence Techniques to Enhance Tomato Production

2020東京農業大

Cultivo de yuca de alta calidad con monitoreo a través de sensores inalámbricos

Se puede decir que la yuca es una lotería: así como puede salir harinosa, perfecta para acompañarla con suero, chicharrón o un buen pescado frito, puede salir mala, imposible de comer. Esto estaría relacionado, entre otros motivos, con que el suelo no es el mejor para su cultivo, a lo que se suma que en ocasiones los riegos no son los adecuados, o que los agricultores no saben si la humedad es óptima para su siembra.Vicerretoria de investigació

CBT system (Computer Based Training) of the Aircraft a-37b, used in the earth course of the combat air command No. 3 (CAMCOM-3) of the Colombian Air Force (FAC)

This article shows the implementation of an integrated and updated education system in the Combat Air Command No.3 as a school of the A-37B team, to give theoretical and virtual practice instruction optimizing strategic processes, increasing productivity, reducing operational and administrative costs in order to promote the commitment and development of human capital to crewmembers of the A-37B team; At the same time, promote technological development and innovation in the personnel that make up the Unit. In this work, the importance of the use of ICT in the educational field and the great contribution it presents in the Colombian Armed Forces is made known

RDF query and protocols language using for description and representation of web ontologies

The purpose of this article is to expose the metadata structure based on RDF (Resource Description Framework) and the way in which queries can be made using SPARQL (Protocol and RDF Query Language), as a principle for searching the Semantic Web. It also describes what must be considered to build a Web Ontology and the tools that can help the Software developer to make querys using SPARQL

Boosting precision crop protection towards agriculture 5.0 via machine learning and emerging technologies: A contextual review

Crop protection is a key activity for the sustainability and feasibility of agriculture in a current context of climate change, which is causing the destabilization of agricultural practices and an increase in the incidence of current or invasive pests, and a growing world population that requires guaranteeing the food supply chain and ensuring food security. In view of these events, this article provides a contextual review in six sections on the role of artificial intelligence (AI), machine learning (ML) and other emerging technologies to solve current and future challenges of crop protection. Over time, crop protection has progressed from a primitive agriculture 1.0 (Ag1.0) through various technological developments to reach a level of maturity closelyin line with Ag5.0 (section 1), which is characterized by successfully leveraging ML capacity and modern agricultural devices and machines that perceive, analyze and actuate following the main stages of precision crop protection (section 2). Section 3 presents a taxonomy of ML algorithms that support the development and implementation of precision crop protection, while section 4 analyses the scientific impact of ML on the basis of an extensive bibliometric study of >120 algorithms, outlining the most widely used ML and deep learning (DL) techniques currently applied in relevant case studies on the detection and control of crop diseases, weeds and plagues. Section 5 describes 39 emerging technologies in the fields of smart sensors and other advanced hardware devices, telecommunications, proximal and remote sensing, and AI-based robotics that will foreseeably lead the next generation of perception-based, decision-making and actuation systems for digitized, smart and real-time crop protection in a realistic Ag5.0. Finally, section 6 highlights the main conclusions and final remarks