Fuzzy control system for variable rate irrigation using remote sensing

Variable rate irrigation (VRI) is the capacity to spatially vary the depth of water application in a field to handle different types of soils, crops, and other conditions. Precise management zones must be developed to efficiently apply variable rate technologies. However, there is no universal method to determine management zones. Using speed control maps for the central pivot is one option. Thus, this study aims to develop an intelligent fuzzy inference system based on precision irrigation knowledge, i.e., a system that can create prescriptive maps to control the rotation speed of the central pivot. Satellite images are used in this study because remote sensing offers quick measurements and easy access to information on crops for large irrigation areas. Based on the VRI-prescribed map created using the intelligent decisionmaking system, the pivot can increase or decrease its speed, reaching the desired depth of application in a certain irrigation zone. Therefore, considering the spatial variability in the crop has made the strategy of speed control more realistic than traditional methods for crop management. The intelligent irrigation system pointed out areas with lower leaf development, indicating that the pivot must reduce its speed, thus increasing the water layer applied to that area. The existence of well-divided zones could be observed; each zone provides a specific value for the speed that the pivot must develop for decreasing or increasing the application of the water layer to the crop area. Three quarters of the total crop area had spatial variations during water application. The set point built by the developed system pointed out zones with a decreased speed in the order of 50%. From the viewpoint of a traditional control, the relay from pivot percent timer should have been adjusted from 70% to 35% whenever the central pivot passed over that specific area. The proposed system obtained values of 37% and 47% to adjust the pivot percent timer. Therefore, it is possible to affirm that traditional control models used for central-pivot irrigators do not support the necessary precision to meet the demands of speed control determined by the developed VRI systems. Results indicate that data from the edaphoclimatic variables when well-fitted to the fuzzy logic can solve uncertainties and non-linearities of an irrigation system and establish a control model for high-precision irrigation

Integrating Remote Sensing Data into Fuzzy Control System for Variable Rate Irrigation Estimates

Variable rate irrigation (VRI) is the capacity to vary the depth of water application in a field spatially. Developing precise management zones is necessary to efficient variable rate irrigation technologies. Intelligent fuzzy inference system based on precision irrigation knowledge, i.e., a system capable of creating prescriptive maps to control the rotation speed of the central pivot. Based on the VRI-prescribed map created by the intelligent system of decision-making, the pivot can increase or decrease its speed, reaching the desired depth of application in a certain irrigation zone. Therefore, this strategy of speed control is more realistic compared to traditional methods. Results indicate that data from the edaphoclimatic variables, when well fitted to the fuzzy logic, can solve uncertainties and non-linearities of an irrigation system and establish a control model for high-precision irrigation. Because remote sensing provides quick measurements and easy access to crop information for large irrigation areas, images will be used as inputs. The developed fuzzy system for pivot control is original and innovative. Furthermore, the artificial intelligent systems can be applied widely in agricultural areas, so the results were favorable to the continuity of studies on precision irrigation and application of the fuzzy logic in precision agriculture

Development of soft computing and applications in agricultural and biological engineering

Soft computing is a set of “inexact” computing techniques, which are able to model and analyze very complex problems. For these complex problems, more conventional methods have not been able to produce cost-effective, analytical, or complete solutions. Soft computing has been extensively studied and applied in the last three decades for scientific research and engineering computing. In agricultural and biological engineering, researchers and engineers have developed methods of fuzzy logic, artificial neural networks, genetic algorithms, decision trees, and support vector machines to study soil and water regimes related to crop growth, analyze the operation of food processing, and support decision-making in precision farming. This paper reviews the development of soft computing techniques. With the concepts and methods, applications of soft computing in the field of agricultural and biological engineering are presented, especially in the soil and water context for crop management and decision support in precision agriculture. The future of development and application of soft computing in agricultural and biological engineering is discussed

Site-specific irrigation: Improvement of application map and a dynamic steering of modified centre pivot irrigation system

Einleitung: Ein Management Konzept für nachhaltige und effiziente Nutzunglandwirtschaftlicher Maßnahmen ist bekannt als teilflächenspezifische Landwirtschaft (PA – Precision Agriculture). Wird das teilflächenspezifische Konzept im Bewässerungsmanagement eingesetzt, wird es teilflächenspezifische Bewässerung genannt (PI – Precision Irrigation). Bei der teilflächenspezifische Bewässerung kann die Bewässerung zwischen den Bereichen eines Feldes auf Grund der Variabilität der Bodeneigenschaften oder dem Anbau von verschiedenen Pflanzen auf dem selben Feld variieren. Die räumliche Veränderung der nutzbaren Feldkapazität als Primärfaktor bedingt die räumliche Veränderung der Bewässerungshöhe und der Bewässerungsfrequenz. Die Bewässerungssysteme verteilen das Wasser bis heute gleichmäßig, so dass die Flächen teilweise überbewässert oder unterbewässert sind. Bezogen auf dieses Problem ist die teilflächenspezifische Beregnung geeignet, das Wasser an der richtigen Stelle zum richtigen Zeitpunkt unter Benutzung des richtigen Bewässerungssystems auszubringen. Folglich sind die Schlüsselziele dieser Arbeit: a) die Abgrenzung von Beregnungsmanagementzonen (IMZs – Irrigation Management Zones) unter Nutzung von sensorbasierten Messungen der elektrischen Leitfähigkeit (ECa – depth-weighted apparent soil electrical conductivity) des Bodens mit EM38 und VERIS 3100, b) die Entwicklung und Evaluierung einer teilflächenspezifischen mobilen Tropfbewässerung und c) Auswertung von drahtlosen  Bodenfeuchtesensoren (EnviroSCAN) und der klimatischen Wasserbilanz (AMBAVModell) zur Bestimmung der Bodenfeuchte bzw. der Bewässerungshöhe.Material und Methoden: EC25-Daten (ECa bei 25° C) wurden unter Verwendung von EM38 und VERIS 3100 Geräten bei Feldkapazität auf einem 16,6 ha großen Feldstück der FAL, Braunschweig, Deutschland, gemessen. Die ECa Daten wurden im Sekundenintervall mit zwei bis drei Metern Messabstand und in Reihenabständen von etwa vier bis sechs Metern gemessen. Zur Erstellung der EC25- und Bodenfeuchte Karten wurde die Software ArcView genutzt, nachdem die Messdaten mit Hilfe des sphärischen Kriging-Verfahren interpoliert wurden. 29 Kalibrierungspunkten wurden mit Hilfe von DGPS lokalisiert, um die beste sensorbasierte Methode zur Abgrenzung der Beregnungsmanagementzonen zu bestimmen. Bodenproben wurden in 0 - 60 cm Tiefe entnommen. Der zweite Bogen der Kreisberegnungsmaschinen wurde für die teilflächenspezifische mobile Tropfbewässerung umgerüstet. Eine kontrollierte Wassermenge konnte, durch Installierung einer Pulstechnik mit Magnetventilen (SV – Solenoid Valve), einem Computer gesteuerten Programm (PLC – Programable Logic Control) und Auswechseln der Düsen durch Siplast Tropfrohre ausgebracht werden. Ein Teil des Feldversuches wurde durch EnviroSCAN Bodenfeuchtesensoren gesteuert und der andere Teil wurde durch das AMBAV-Modell gesteuert, um die Beregnungshöhe zu bestimmen. Die hydraulische Genauigkeit der Siplast Tropfrohre wurde im Labor bei unterschiedlichen Wasserdrücken von 50, 100, 150 und 200 kPa untersucht.Ergebnisse und Diskussion: Die Untersuchung zeigt, dass EC25-Daten von verschiedenen gewerblichen Sensoren auf Grund der unterschiedlichen Gewichtung der Tiefe quantitativ unterschiedlich sind. Das höchste Bestimmtheitsmaß wurde zwischen EM38_h und EM38_v (R2 = 0,55) gefunden. In dieser Arbeit wurde ein gutes Bestimmtheitsmaß zwischen nFK und den VERIS 3100 Werten gefunden. Eine Kalibrierungsgleichung zur Abschätzung der nFK von VERIS 3100-sh zeigte eine hohe Ähnlichkeit zu den nFK Daten auf und hatte das höchste Bestimmtheitsmaß (R2 = 0,77). Die Bestimmtheitsmaße zu EM38-v- und EM38-h-Daten waren niedrig und anscheinend nicht ausreichend, um die räumliche Variabilität der nFK reflektieren zu können. Ein Grund kann die größere Messtiefe von EM38 sein. Sechs Beregnungsmanagementzonen (IMZ1: 99 bis 105, IMZ2: 105 bis 116, IMZ3: 116 bis 127, IMZ4: 127 bis 138, IMZ5: 138 bis 149 und IMZ6: 149 bis 152 mm/60 cm) wurden als optimale Anzahl an Beregnungsmanagementzonen auf dem Versuchsfeld, basierend auf den fuzzy-k-Mittelwerten (Boydell and McBratney, 1999) der zufälligen Einteilung, erkannt. Es wurde gefolgert, dass unter konventioneller Beregnung IMZ1 und IMZ2 überbewässert und IMZ4, IMZ5 und IMZ6 unterbewässert wurden. Das entwickelte Konzept der Pulsbewässerung hat sich als eine zuverlässige Technik bewährt. Die Wasserapplikationsmenge war direkt proportional zur Öffnungsdauer des Ventils, und das System war in der Lage, die Wassermenge entsprechend des Bewässerungspulses zu variieren. Weiterhin war es in der Lage, 15 Reihen mit jeweils 15 Düsen zu steuern. Es gab keine offenkundigen Probleme mit dem gepulsten Wasserabgabesystem in den durchgeführten Feldversuchen. Die Kreisberegnungsmaschinengeschwindigkeit und Pulstechnik zur Bereitstellung verschiedener Wassermengen hatten einen geringen nachteiligen Einfluss auf die Gleichmäßigkeit der Beregnungshöhe. Die Gleichmäßigkeitskoeffizienten wurden durch sinkende Pulszeiten und steigende Kreisberegnungsmaschinengeschwindigkeiten gesenkt. Die Kontrolleinheit war wie erwartet in der Lage die Bodenfeuchtedaten mittels Fernmesstechnik von dem EnviroSCAN Sensor zum zentralen Modem zu senden. Obwohl der EnviroSCANBodenfeuchtigkeitssensor empfindlich und kompliziert zu benutzen und zu kalibrieren ist, wurden die Bodenfeuchtigkeitsdaten fast störungsfrei von der Kontrolleinheit empfangen, gespeichert und zum Mobiltelefon gesendet. Für die Übertragung auf den PC wurde die Software „Kurznachricht Pro 2.2“ genutzt. Anschließend wurde die differenzierte Bewässerungshöhe kalkuliert. Die Ergebnisse zeigen, dass die EnviroSCAN-Sensoren in der Lage sind, den Verlauf der Bodenfeuchte während der Wachstumsperiode erfolgreich zu verfolgen. Weniger gut arbeitet der Sensor, um die Feuchtigkeitsverhältnisse auf sandigen Böden (unter 40 cm Tiefe), trotz bodenspezifischer Kalibrierung zu bestimmen. Während dessen hat sich das AMBAV-Modell als eine Alternative zum kostenintensiven EnviroSCAN erwiesen, das in der Lage ist, die Bodenfeuchtigkeit in der Wurzelzone der Graspflanzen als eine preiswerte und verlässliche Methode zu simulieren. Das Tropfbewässerungssystem sollte auf verlässlichen Testergebnissen und nicht auf Herstellerangaben beruhen. Die Laborexperimente zeigten, dass der Einfluß des Betriebsdrucks auf den Durchfluss am Siplast Tropfer hoch signifikant war und der Tropferdurchfluß stark vom Betriebsdruck abhing. Die CV-Werte wurden auf dem ISO-Standard basierend als gut eingestuft. Aus den Laborexperimenten wurde herausgefunden, dass der in-line Siplast Tropfer eine hohe Ausbringungsgleichmäßigkeit und einen geringen Variationskoeffizienten aufweist. Das Rohrmaterial des Siplast Tropfer ist hart und unflexibel. Es sollte nach weiteren Produkten gesucht werden, die flexibler sind und somit die Kulturen schonen. Die ökonomische Analyse dieser Arbeit zeigt, dass der Kapitalbedarf pro Hektar unter teilflächenspezifische mobile Tropfbewässerung um etwa 338 € und 250 € höher liegt als bei entsprechender Tropfbewässerung in Deutschland und im Iran. Die jährlichen Fixkosten sind geringer, als bei der Tropfbewässerung (111 und 128 [€/(ha x Jahr)] in Deutschland oder im Iran). Obwohl die teilflächenspezifische mobile Tropfbewässerung teurer ist als die Beregnung mit Kreisberegnungsmaschinen, verursacht sie weniger Wasser- und Energiekosten als die Kreisberegnungsmaschinen und hat das Potenzial den Ertrag qualitativ und quantitativ, sowie den landwirtschaftlichen Gewinn zu steigern. Die Ergebnisse zeigen, als wichtige Folge des Verfahrens, dass die teilflächenspezifische mobile Tropfbewässerung nicht notwendiger Weise eine wassersparende Technologie ist, aber es kann den Wasserbedarf optimieren. Der Energiebedarf kann um 70 % und der Wasserbedarf kann um 25 % durch die teilflächenspezifische mobile Tropfbewässerung gegenüber der Kreisberegnungsmaschine gesenkt werden. Die Modellbetrachtungen zeigten, dass durch die teilflächenspezifische mobile Tropfbewässerung im Vergleich mit der konventionellen Kreisberegnungsmaschine bei Salat, Zuckerrübe,  Kartoffel und Erdbeere etwa 575, 378, 462 und 588 kWh Energie pro Hektar gespart werden können.Schlussfolgerung: Die sensorbasierte Messung der elektrischen Leitfähigkeit bei Feldkapazität von nicht salzigen Böden ist eine preiswerte, schnelle und das Bodengefüge nicht zerstörende Alternative, um die Beregnungsmanagementzone räumlich abzugrenzen und ist den Methoden der Bodenprobenahme und Luftbildauswertung vorzuziehen. Feldstudien mit größeren Bewässerungssystemen und Felder mit verschiedenen Bodentypen, Topographie oder Pflanzenbeständen sind weiterhin zu untersuchen, um die Genauigkeit des Bewässerungskonzeptes zu validieren. Vor dem Hintergrund, dass teilflächenspezifische Bewässerung in den Anfängen steckt und eine weitere Verbreitung dieser Technologie zu erwarten ist, könnten die zusätzlichen Kosten für industrielle Ausrüstungsteile gesenkt werden. Beträchtliche Forschung und Entwicklung ist noch nötig, um die möglichen Vorteile der teilflächenspezifischen Beregnung und der Flüssigdüngung besser zu realisieren, um ein positives ökonomisches Ergebnis für den Erzeuger zu sichern.Introduction: A management concept for sustainable utilization and the efficient use of agricultural inputs is known as “Precision Agriculture” (PA). The PA concept, when applied to irrigation management is known as Precision Irrigation (PI). In PI, the need for irrigation may differ between zones of a particular field due to the spatial variation of soil properties or the cropping of different plants on the same field. Spatial variation of total available water content (TAWC) as a primary factor causes spatial variation of irrigation depth and frequency within fields. While moving irrigation systems apply water at constant rates, some areas of the field may receive too much water and others not enough. In this regard, precision irrigation (PI) is capable of applying water in the right place in the right amount at the right time using the right irrigation system. Therefore the key objectives of the present study were a) Delineation of irrigation management zones (IMZs) using sensor-based soil electrical conductivity (ECa) measurement with the aid of EM38 and VERIS 3100, b) Developing and evaluating a precision mobile drip irrigation (PMDI) and c) Evaluating wireless EnviroSCAN sensors and AMBAV-models to measure the soil moisture content.Materials and methods: EC25 data (ECa in 25° C) were collected using EM38 and VERIS 3100 at field capacity on a 16.6 ha non-saline field in the FAL, Braunschweig, Germany. ECa data were obtained in 1-s intervals corresponding to a 2 to 3 m data spacing on transects spaced approximately 4 to 6 m apart. An ArcView (ESRI) software program was used to create the EC25 and TAWC maps after the readings were interpolated using a spherical kriging model. 29 calibration points taken at a depth of 0 - 60 cm depth were located using DGPS based on the ECa spatial variability pattern and with the objective of covering the whole range of ECa values present to determine the best sensor-based method to monitor TAWC. The second span of the centre pivot irrigation machine (CP) was modified to PMDI and controlled for variable-rate water application with a pulsing technique by installing solenoid valves (SV), programmable logic control (PLC) and using a Siplast drop tube instead of sprinklers. One quarter of the study field was controlled by the EnviroSCAN soil moisture sensor and another quarter was controlled by the AMBAV-model to determine irrigation depth. In addition, the hydraulic performance of the Siplast drop tube was evaluated in the laboratory by collecting discharge rates at different pressure of 50, 100, 150 and 200 kPa.Results and discussion: This study showed that, while qualitatively similar, EC25 data obtained with different commercial sensors were quantitatively different because of different depth-weighted response functions. The highest coefficients of determination (R2) were generally found between EM38_h and EM38_v (R2 = 0.55). In this study, a better value of R2 between TAWC and the VERIS 3100 readings was found. The R2 value from VERIS 3100-sh data for TAWC estimation was maximally (0.77) and matched the TAWC data quite well, whereas R2 values to EM38-h and EM38-v data were low and apparently could not adequately reflect the spatial variability of the TAWC due to the higher influence of the EM38 on deeper layers. Six IMZs (IMZ1: 99 to 105, IMZ2: 105 to 116, IMZ3: 116 to 127, IMZ4: 127 to 138, IMZ5: 138 to 149 and IMZ6: 149 to 152 mm/60 cm) were identified based on fuzzy-k-means unsupervised classification as an optimum number of IMZs within the study field. It was concluded that under conventional uniform irrigation, IMZ1 and IMZ2 were over-irrigated, whereas IMZ4, IMZ5 and IMZ6 were under-irrigated. The developed concept of pulse irrigation was a feasible and a viable technique. Water application was directly proportional to the fraction of time the valve was opened as the system was capable of controlling fifteen banks of fifteen nozzles. There were no apparent problems with the pulsing water delivery system where the field tests were conducted. CP speed and the pulsing technique used to deliver variable amounts of irrigation had little adverse effect on system uniformity and the nozzle flow rate. Uniformity coefficients were reduced by decreasing the pulsing level and increasing CP speed. The control unit was able to monitor wireless soil moisture sensors via radio telemetry and communication from the EnviroSCAN sensors to the central ISM modem, which worked as expected. Although the EnviroSCAN soil moisture sensor was found to be delicate and intricate to use and calibrate, soil moisture data were easily sent from the control unit and received by the mobile phone and then transferred to an Excel table on a computer using easy and suitable “Kurznachricht Pro 2.2” software to calculate irrigation depth. The results suggest that EnviroSCAN sensors are able to follow the general trends successfully as soil water content measured by sampling changed during the growing season, but are not a reliable sensor to repeat moisture conditions on sandy soils (at greater depths than 40 cm ) despite its soil-specific calibration. Meanwhile, an AMBAV model as a cheap and reliable alternative instead of the expensive EnviroSCAN sensor was capable of determining and simulating soil moisture in the root zone of grass crops. Drip irrigation design should be based on reliable data sets, but not on data supplied by the manufacturer. The laboratory experiments showed that the effect of operating pressure on the discharge of Siplast emitters was highly significant and the emitter discharge was strongly influenced by the operating pressure, while some deviation from the design flow rate claimed by the manufacturer occurred. CV values were classified as good, on the basis of the ISO standard. Based on the laboratory experiments, it was found that the in-line Siplast emitter has high emission uniformity and a low coefficient of variation. In spite of high emission uniformity and a low coefficient of variation of the Siplast drop tube, it must consist of hard and inflexible material. To have a shorter drip tube installed on CP, using an in-line drop tube lateral with higher emitter discharge at low operation pressure and less emitter distance is proposed. The economic analysis of this study showed that although capital requirement per hectare under PMDI is about € 338 and € 250 more than for drip irrigation in Germany and Iran, respectively, it causes perceptibly less annual fixed cost than drip irrigation (111 and 128 [€/(ha x year)] cheaper than drip irrigation in Germany and Iran, respectively). Although PMDI causes more annual fixed expenses than CP irrigation, it has less total irrigation cost per hectare and year than CP and drip irrigation and has the potential benefit to increase yield quantity, quality and farming benefit. The results showed as an important policy implication that PMDI is not necessarily a water saving technology and it does not necessarily involve a reduction in total water use, but that it can optimize water consumption. Given a reduction of energy and water consumption of 70 % and 25 %, respectively, achieved by the PMDI as compared with the CP, results showed that about 575, 378, 462 and 588 kWh energy per hectare can be saved by PMDI in comparison with the conventional CP irrigation of lettuce, sugar beet, potato and strawberry.Conclusion: Sensor-based ECa measurement at F.C. in non-saline soil can be used as a cheap, rapid and non-destructive alternative to delineate IMZ instead of using soil sampling and aerial photography methods. Field studies using larger irrigation systems and fields with different soil types, topographic or crop characteristics are recommended to validate the precision irrigation concept and to realize and ensure a positive net economic return to the producer. With due attention to the success of PI in the early stages and developments in industrial technology in the coming years, the extra costs of industrial accessories could be minimised

A fuzzy logic micro-controller enabled system for the monitoring of micro climatic parameters of a greenhouse

Motivation behind this master dissertation is to introduce a novel study called " A fuzzy logic micro-controller enabled system for the monitoring of micro-climatic parameters of a greenhouse" which is capable of intelligently monitoring and controlling the greenhouse climate conditions in a preprogrammed manner. The proposed system consists of three stations: Sensor Station, Coordinator Station, and Central Station. To allow for better monitoring of the climate condition in the greenhouse, fuzzy logic controller is embedded in the system as the system becomes more intelligent with fuzzy decision making. The sensor station is equipped with several sensor elements such as MQ-7 (Carbon monoxide sensor), DHT11 (Temperature and humidity sensor), LDR (light sensor), grove moisture sensor (soil moisture sensor). The communication between the sensor station and the coordinator station is achieved through XBee wireless modules connected to the Arduino Mega and the communication between coordinator station and the central station is also achieved via XBee wireless modules connected to the Arduino Mega. The experiments and tests of the system were carried out at one of IKHALA TVET COLLEGE’s greenhouses that is used for learning purposes by students studying agriculture at the college. The purpose of conducting the experiments at the college’s green house was to determine the functionality and reliability of the designed wireless sensor network using ZigBee wireless technology. The experiment result indicated that XBee modules could be used as one solution to lower the installation cost, increase flexibility and reliability and create a greenhouse management system that is only based on wireless nodes. The experiment result also showed that the system became more intelligent if fuzzy logic was used by the system for decision making. The overall system design showed advantages in cost, size, power, flexibility and intelligence. It is trusted that the results of the project will give the chance for further research and development of a low cost greenhouse monitoring system for commercial use.Electrical and Mining EngineeringM. Tech. (Electrical Engineering

Assessment of data fusion oriented on data mining approaches to enhance precision agriculture practices aimed at increase of Durum Wheat (Triticum turgidum L. var. durum) yield

In 2050, world population will reach a total of 9 billion inhabitants and their food demand have to be satisfied. Durum wheat (Triticum turgidum L. var. durum) is one of the most important food crop and its consumption is increasing worldwide. Productivity growth in agriculture and profitable returns are strongly influenced by investment in research and development, where Precision Agriculture (PA) represents an innovative way to manage farms by introducing the Information and Communication Technology (ICT) into the production process. It is known that farms activities produce large amounts of data. Today ICT allows, with electronic and software systems, to collect and transfer automatically these data, thus increasing yields and profits. In this direction significant data are processed from agricultural production, and retrieved to extract useful information important to increase the knowledge base. Data from multiple data sources can be processed by a Data Fusion (DF) approach able to combine multiple data sources into an unique database system. Raw data are transformed into useful information, thus DF improves pattern recognition, analysis of growth factors, and relationship between crops and environments. Data Fusion is synonym of Data Integration, Sensor Fusion, and Image Fusion. By means of Data Mining (DM) it is possible to extract useful information from data of the production processes thus providing new outputs concerning product quality and product “health status”. The following literature take into account the DF and DM techniques applied to Precision Agriculture (PA) and to cultivation inputs (water, nitrogen, etc.) management.  We report also last advances of DF and DM in modern agriculture and in precision durum wheat production

Simulation of site-specific irrigation control strategies with sparse input data

Crop and irrigation water use efficiencies may be improved by managing irrigation application timing and volumes using physical and agronomic principles. However, the crop water requirement may be spatially variable due to different soil properties and genetic variations in the crop across the field. Adaptive control strategies can be used to locally control water applications in response to in-field temporal and spatial variability with the aim of maximising both crop development and water use efficiency. A simulation framework ‘VARIwise’ has been created to aid the development, evaluation and management of spatially and temporally varied adaptive irrigation control strategies (McCarthy et al., 2010). VARIwise enables alternative control strategies to be simulated with different crop and environmental conditions and at a range of spatial resolutions. An iterative learning controller and model predictive controller have been implemented in VARIwise to improve the irrigation of cotton. The iterative learning control strategy involves using the soil moisture response to the previous irrigation volume to adjust the applied irrigation volume applied at the next irrigation event. For field implementation this controller has low data requirements as only soil moisture data is required after each irrigation event. In contrast, a model predictive controller has high data requirements as measured soil and plant data are required at a high spatial resolution in a field implementation. Model predictive control involves using a calibrated model to determine the irrigation application and/or timing which results in the highest predicted yield or water use efficiency. The implementation of these strategies is described and a case study is presented to demonstrate the operation of the strategies with various levels of data availability. It is concluded that in situations of sparse data, the iterative learning controller performs significantly better than a model predictive controller

무선 통신 기반의 스마트 관개 모니터링 시스템

학위논문 (석사) -- 서울대학교 대학원 : 공과대학 기계공학부, 2020. 8. 안성훈.농업은 개발 도상국들의 경제적 중추임에도 불구하고 대부분의 개발 도상국에서는 자동화된 장비나 데이터 모니터링 등의 지능형 시스템이 거의 적용되지 못한 상태에서 인력에 의해 농업의 모든 과정을 수행하고 있다. 관개는 농작물의 생산성에 결정적 영향을 미치는 필수적인 농업 공정중 하나로서, 연중 강우량의 변동에 대한 대응을 위하여 대부분의 농촌지역에는 농업용수 관개 시스템의 구축을 위해 노력하고 있다. 하지만, 이러한 인력에 의한 농업 방법에서의 관개 시스템은 스마트 센서를 이용한 모니터링 및 제어 등의 기술적 요소가 적용되지 못하여 효율적인 수자원의 활용이 제한되고 이로 인해 농작물의 생산성 또한 낮은 실정이다. 본 논문에서는 개발 도상국의 농촌 지역에서 적용 가능한 무선통신(RF: Radio Frequency) 기반의 스마트 관개 모니터링 시스템 및 요금 선불 시스템을 제안한다. 본 연구는 탄자니아 아루샤(Arusha) 지역의 응구루도토(Ngurudoto) 마을을 대상으로 수행되었다. 본 연구에서 제안하는 시스템은 기상 데이터와 토양 수분 데이터를 하이브리드로 분석하여 농업 용수의 소요를 모니터링한다. 하드웨어 시스템은 기상 측정 컨트롤러, 토양 수분 센서, 수류 센서, 솔레노이드 밸브 및 요금 선불 시스템 등으로 구성된다. 시스템의 각 센서는 무선 통신을 통해 서버로 수집된 데이터를 전송하도록 구축되었는데, 이러한 무선 통신 시스템 아키텍처는 인터넷의 운용이 제한되는 네트워크 오지 지역에 적합하도록 설계되었다. 수집된 데이터에 대한 분석 및 예측은 데이터 분석 알고리즘을 통해 수행되는데, 이를 통하여 농장에 용수를 공급할 시기 및 수량과 함께 요구되는 전력량이 자동으로 판단된다. 한편, 선불시스템은 데이터 분석 결과에 기반하여 용수 사용자가 용수를 공급받기 전에 비용을 우선 지불하도록 개발되었다. 본 시스템의 모든 센서에서 수집된 정보는 실시간으로 모니터링되도록 그래픽 기반의 사용자 인터페이스를 활용하여 정보를 제공한다. 본 연구를 통하여 개발된 무선 통신 기반 스마트 관개 모니터링 시스템은 사용자 중심의 편의성과 경제적인 관개 및 모니터링 시스템을 제공하여 개발 도상국의 경제적 기반인 농업 분야의 발전에 긍정적인 영향을 미칠것으로 기대한다.Agriculture is the backbone of the economy of most developing countries. In these countries, agriculture or farming is mostly done manually with little integration of machinery, intelligent systems and data monitoring. Irrigation is an essential process that influences crop production. The fluctuating amount of rainfall per year has led to the adaption of irrigation systems in most farms. This manual type of farming has proved to yield fair results, however, due to the absence of smart sensors monitoring methods and control, it has failed to be a better type of farming and thus leading to low harvests and draining water sources. In this paper, we introduce an RF (Radio Frequency) based Smart Irrigation Meter System and a water prepayment system in rural areas of Tanzania. Specifically, Ngurudoto area in Arusha region where it will be used as a case study for data collection. The proposed system is hybrid, comprising of both weather data (evapotranspiration) and soil moisture data. The architecture of the system has on-site weather measurement controllers, soil moisture sensors buried on the ground, water flow sensors, solenoid valve, and a prepayment system. These sensors send data to the server through wireless RF based communication architecture, which is suitable for areas where the internet is not reliable and, it is interpreted and decisions and predictions are made on the data by our data analysis algorithm. The decisions made are, when to automatically irrigate a farm and the amount of water and the power needed. Then, the user has to pay first before being supplied with water. All these sensors and water usage are monitored in real time and displaying the information on a custom built graphical user interface. The RF-based smart irrigation monitoring system has both economical and social impact on the developing countries' societies by introducing a convenient and affordable means of Irrigation system and autonomous monitoring.Chapter 1. Introduction 1 Chapter 2 Background of the study and Literature review 3 1.1.Purpose of Research 17 Chapter 3. Requirements and System Design 21 3.1. Key Components 21 3.1.1. System Architecture 21 3.1.2. The Smart Irrigation Meter 22 3.1.2. Parts of Smart Irrigation Meter 23 3.1.3. The pre-paid system and the monitoring device 26 3.2. The Monitoring Application and Cloud Server. 27 Chapter 4. Experiment Setup 30 4.1. Testing Location 30 4.2. Hardware & Software Setup 31 Chapter 5 Results and Analysis 36 5.1 Optimization and anomaly detection algorithm 36 5.1.1 Dynamic Regression Model 36 5.1.2 Nave classifier algorithm for anomaly detection. 38 Chapter 6. Conclusion 44 References 46 초 록 49Maste

Air pollution and livestock production

The air in a livestock farming environment contains high concentrations of dust particles and gaseous pollutants. The total inhalable dust can enter the nose and mouth during normal breathing and the thoracic dust can reach into the lungs. However, it is the respirable dust particles that can penetrate further into the gas-exchange region, making it the most hazardous dust component. Prolonged exposure to high concentrations of dust particles can lead to respiratory health issues for both livestock and farming staff. Ammonia, an example of a gaseous pollutant, is derived from the decomposition of nitrous compounds. Increased exposure to ammonia may also have an effect on the health of humans and livestock. There are a number of technologies available to ensure exposure to these pollutants is minimised. Through proactive means, (the optimal design and management of livestock buildings) air quality can be improved to reduce the likelihood of risks associated with sub-optimal air quality. Once air problems have taken hold, other reduction methods need to be applied utilising a more reactive approach. A key requirement for the control of concentration and exposure of airborne pollutants to an acceptable level is to be able to conduct real-time measurements of these pollutants. This paper provides a review of airborne pollution including methods to both measure and control the concentration of pollutants in livestock buildings