EDAS (EGNOS Data Access Service) Differential GNSS Corrections: A Reliable Free-of-Charge Alternative for Precision Farming in Europe

EDAS for a DGPS Maritime Service: EGNOS Based VRS Performance with Pre-Broadcast Integrity Monitoring

GALILEO and GPS Performances in the Maritime Environment

Purpose: Agriculture is a vast field that necessitates the assistance of disciplines from other fields in order to properly grow. In recent days Information technology is been used in agriculture that helps in the efficiency of the growth of the productivity of agriculture such as in the development of the quality of the farming and its products Precision agriculture are used to increase the growth of the crop quantity. In this paper, a survey includes the analysis and application of precision agriculture. Precision agriculture is used to increase the growth of the crop quantity. And various Precision agriculture companies that have helped the farmer in the field growth. Objectives: To study the role of Information Technology used in Agriculture, and view on various techniques used in precision agriculture. Methodology/Design/Approach: The analysis and the application of precision agriculture are done by referring various research paper, articles. A Literature Survey is done. Findings/Result: Farmers are currently hesitant to use the new Techniques, when compared to traditional farming, Precision farming has the potential to produce higher yields. Originality/value: Based on the secondary data available, the paper focus on the application of precision agriculture. Findings/Result: To study the role of Information Technology used in Agriculture, Precision Agriculture.

Wireless Sensor Network (WSN) technology has the potential to have impact on many aspects of Precision Agriculture (PA). However, current WSN applications in Precision Agriculture all adopt the traditional client/sever model, data are sent from the source to the destination, because of hugeous data, high concurrency and strong signal interference in Precision Agriculture and the extremely limited sensor network resources, such client/sever model hampers WSN applications in Precision Agriculture.[ This paper presents a mobile-based agent of wireless sensor network model MAPA, MAPA avoids the large agricultural intermediate data transmission through migrating the computing to the resource source, and consequently it prolongs the sensor network lifetime and promotes the WSN applications in Precision Agriculture.

Advances in Structured Light Sensors Applications in Precision Agriculture and Livestock Farming

Integrating blockchain and the internet of things in precision agriculture: Analysis, opportunities, and challenges

After two decades of availability of grain yield-mapping technology, long-term trends in field-scale profitability for precision agriculture (PA) systems and conservation practices can now be assessed. Field-scale profitability of a conventional or ‘business-as-usual’ system with an annual corn (Zea mays L.)-soybean (Glycine max [L.]) rotation and annual tillage was assessed for 11 years on a 36 ha field in central Missouri during 1993 to 2003. Following this, a ‘precision agriculture system’ (PAS) with conservation practices was implemented for the next 11 years to address production, profit and environmental concerns. The PAS was multifaceted and temporally dynamic. It included no-till, cover crops, crop rotation changes, site-specific N and variable-rate or zonal P, K and lime. Following a recent evaluation of differences in yield and yield variability, this research compared profitability of the two systems. Results indicated that PAS sustained profits in the majority (97%) of the field without subsidies for cover crops or payments for enhanced environmental protection. Profit was only lower with PAS in a drainage channel where no-till sometimes hindered soybean stands and wet soils caused wheat (Triticum aestivum L.) disease. Although profit gains were not realized after 11 years of PA and conservation practices, this system sustained profits. These results should help growers gain confidence that PA and conservation practices will be successful.

In precision farming technology, the interest of the researchers has been focused on the applications of autonomous mobile robots for agricultural operations such as planting, inspection, spraying, and harvesting. However, each autonomous robot generally performs a single agricultural task. In this context, complete autonomy in precision farming can be achieved by using coordinated multi-robot systems that can easily and safely cooperate to accomplish agricultural tasks. The efficiency of the multi-robot system depends on the number of robots, the size of the robots, the distance between each robot, the instant location and heading angle of the robots, and the size of the farmland. This paper describes the development of wireless Robot to Robot (R2R) communication system architecture and the collision avoidance algorithm for multi-robot precision farming applications. The developed system uses the fusion of a digital compass and GPS receiver for wirelessly broadcasting the spatial and temporal data of the mobile robots through WiFi. In this study, WiFi broadcasting was chosen for reasons such as the advantages of long wireless signal range and strength, not being easily affected by weather and dust, low cost, and so on. The proposed system realizes the real-time wireless broadcasting of the mobile robot information for eliminating the collision of mobile robots and improving the level of safety management. The results show that the system has flexible, reliable, and adaptable solution, and thus can increase the efficiency of the multi-robot system in precision farming applications.

The time variable Earth’s gravity field provides the information about mass transport within the system Earth, i.e., the relationship of mass transport between atmosphere, oceans, and land hydrology. We recover the low-degree parameters of the time variable gravity field using microwave observations from GPS and GLONASS satellites and from SLR data to five geodetic satellites, namely LAGEOS-1/2, Starlette, Stella, and AJISAI. GPS satellites are particularly sensitive to specific coefficients of the Earth's gravity field, because of the deep 2:1 orbital resonance with Earth rotation (two revolutions of the GPS satellites per sidereal day). The resonant coefficients cause, among other, a “secular” drift (actually periodic variations of very long periods) of the semi-major axes of up to 5.3 m/day of GPS satellites. We processed 10 years of GPS and GLONASS data using the standard orbit models from the Center of Orbit Determination in Europe (CODE) with a simultaneous estimation of the Earth gravity field coefficients and other parameters, e.g., satellite orbit parameters, station coordinates, Earth rotation parameters, troposphere delays, etc. The weekly GNSS gravity solutions up to degree and order 4/4 are compared to the weekly SLR gravity field solutions. The SLR-derived geopotential coefficients are compared to monthly GRACE and CHAMP results.

Precision farming applications are often data centric and aim collecting data from a set of sensor modules to be delivered to the central computer. For this aim, the ISO 11783 protocol which uses the Controller Area Network (CAN) as a data link protocol to perform the data communication are used to standardize and provide the serial data communication as wired between the various sensor modules and the central computer a plug/play approach. Many different types of sensors may use to collect temporal and spatial variability in precision farming applications. Especially GPS receivers are the most important sensor in a precision farming application. And also, different data bus protocols can be used for collected data transmission to the central computer. In this context, wireless sensor protocols, especially ZigBee, is gaining popularity for managing precision farming through real-time monitoring of agricultural variability. Various parameters in the precision farming can be monitored and controlled using ZigBee communication integrated with the CAN bus. In this paper, integration of the wired CAN Bus and ZigBee communication was designed, developed and implemented. In this system, the data regarding the geographical coordinate is extracted from the GPS receiver with the help of the ZigBee communication and send it to a central computer with the help of wired CAN Bus. This method has been implemented in order to adapt the ZigBee messages to the CAN Bus and reduce wire using. Finally, the data flow within designed system between CAN and ZigBee data frames was described. In this study, multiple CAN frames usage and handshaking mechanism are explained for sending sensor data longer than 64 bits. This system’s advantage is not only reduce cabling cost and increase the communication speed but also provide dynamic, flexible and applicable communication in precision farming applications.

This Project is proposed on precision agriculture system over the Internet of Things (IOT). Through analysing the present development of precision agriculture in outside world and considering its advantages and shortcomings, we decide an ecology farm as an example to conduct a replacement precision agriculture management system (PAMS). Designing a non-public Internet of Things (IOT) enabled platform for the research in precision agriculture and ecological monitoring domains. As water supplies become scarce thanks to climatically change, there's an urgent must irrigate more efficiently so as to optimize water use. During this context, farmers' use of a decision-support system is unavoidable. Indeed, the real-time supervision of microclimatic conditions are the sole thanks to know the water needs of a culture. Wireless sensor networks are playing a very important role with the arrival of the web of things within the community of the farmers. It’ll be judicious to form supervision possible via Sensors.

This chapter aims to present a survey on the existing techniques and architectures of Multimedia Big Data (MMBD) computing for Internet of Things (IoT) applications in Precision Agriculture, along with the opportunities, issues, and challenges it poses in the context. As a consequence of the digital revolution and ease of availability of electronic devices, a massive amount of data is being acquired from a variety of sources. On one hand, this overwhelming quantity of multimedia data poses several challenges, from its storage to transmission, and on the other, it presents an opportunity to provide an insight into the business trends, intelligence and render rich decision support. One of the key applications of MMBD Computing is Precision Agriculture. The chapter focuses on major agricultural applications, cyber-physical systems for smart farming, multimedia data collection approaches, and various IoT sensors along with wireless communication technologies employed in the field of Precision Agriculture.

Chapter 27 Applications in Precision Agriculture

A second green revolution is needed to double global food production over the next 30 years, and requires the use of the best of the technologies such as precision agriculture, to maximize production with minimum input costs and resources. This document shows advances in the development of prototype to direct acquired and sensing information to management fertilizes and water for applications in precision agriculture. We present the numerical/computational stage of such prototype which is equipped with laser sensors to determine the content of water, fertilizer or any other nutrient in row crops. Determining this information is key in order to know if the crop needs more of the above-mentioned substance. Our application is devoted for micro-crops which need to be swept with high precision as a result of its size. This agricultural problem translates to control engineering as a tracking problem.

In precision agriculture, the estimation of soil parameters via sensors and the creation of nutrient maps are a prerequisite for farmers to take targeted measures such as spatially resolved fertilization. In this work, 68 soil samples uniformly distributed over a field near Bonn are investigated using laser-induced breakdown spectroscopy (LIBS). These investigations include the determination of the total contents of macro- and micronutrients as well as further soil parameters such as soil pH, soil organic matter (SOM) content, and soil texture. The applied LIBS instruments are a handheld and a platform spectrometer, which potentially allows for the single-point measurement and scanning of whole fields, respectively. Their results are compared with a high-resolution lab spectrometer. The prediction of soil parameters was based on multivariate methods. Different feature selection methods and regression methods like PLS, PCR, SVM, Lasso, and Gaussian processes were tested and compared. While good predictions were obtained for Ca, Mg, P, Mn, Cu, and silt content, excellent predictions were obtained for K, Fe, and clay content. The comparison of the three different spectrometers showed that although the lab spectrometer gives the best results, measurements with both field spectrometers also yield good results. This allows for a method transfer to the in-field measurements.