Advanced Irrigation Engineering： Precision and Precise

Irrigation advances in precision irrigation （PI） or site specific irrigation （SSI） have been considerable in research; however, commercialization lags. SSI/PI has applications when soil texture variability affects soil water holding capacity or when crop yield or biotic stresses （insects or diseases） are spatially variable. SSI/PI uses variable rate application technologies, mainly with center-pivots or lateral-move or linear irrigation machines, to match crop needs or soil water holding constraints. Variable rate applications are achieved by variable nozzle flow rates, pulsing nozzle flows, or multiple nozzles on separate submains. Newer center pivot and linear machines are controlled by on-board microprocessor systems that can be integrated with supervisory control and data acquisition controllers for both communication and control of the variable rate application for specific sets of nozzles or individual nozzles for management zones. Communication for center pivot or linear controllers typically uses radio telemetry, wireless interact links, or cellular telephones. Precision irrigation has limited utility without precise irrigation scheduling （temporally and spatially）. Plant or soil sensors are used to initiate or complete an irrigation event. Automated weather stations provide site information for determining the irrigation requirement using crop models or simpler reference evapotranspiration （ET）, data to be used with crop coefficients. Remote sensing is being used to measure crop water status or crop development from spectral reflectance. Near-surface remote sensing with sensors mounted on moving irrigation systems provide critical spatial integration from point weather networks and feedback on crop ET and irrigation controls in advanced automated systems for SSI/PI.

Automated Irrigation System Using Improved Fuzzy Neural Network in Wireless Sensor Networks

Irrigation plays a significant role in various agricultural cropping methods deployed in semiarid and arid regions where valuable water applications and managing are considered crucial concerns.Multiple factors such as weather,soil,water,and crop data need to be considered for irrigation maintenance in an efficient besides uniform manner from multifaceted and different information-based systems.A Multi-Agent System(MAS)has been proposed recently based on diverse agent subsystems with definite objectives for attaining global MAS objective and is deployed on Cloud Computing paradigm capable of gathering information from Wireless Sensor Networks(WSNs)positioned in rice,cotton,cassava crops for knowledge discovery and decision making.The radial basis function network has been used for irrigation prediction.However,in recent work,the security of data has not focused on where intruder involvement might corrupt the data at the time of data transferring to the cloud,which would affect the accuracy of decision making.To handle the above mentioned issues,an efficient method for irrigation prediction is used in this work.The factors considered for decision making are soil moisture,temperature,plant height,root depth.The above-mentioned data will be gathered from the sensors that are attached to the cropfield.Sensed data will be forwarded to the local server,where data encryption will be performed using Adaptive Elliptic Curve Cryptography(AECC).After the encryption process,the data will be forwarded to the cloud.Then the data stored in the cloud will be decrypted key before being given to the deci-sion-making module.Finally,the uniform distribution-based fuzzy neural network is formulated based on the received data information in the decisionmaking module.Thefinal decision regarding the level of water required for cropfields would be taken.Based on this outcome,the water volve opening duration and the level of fertilizers required will be considered.Experimental results demonstrate the effectiveness of the proposed model for the United States Geological Survey(USGS)database in terms of precision,accuracy,recall,and packet delivery ratio.

Review of conceptual and systematic progress of precision irrigation

Precision irrigation,defined as accurate and appropriate agricultural techniques characterized by optimal management and best collaboration of various irrigation factors,attracts great attention and obtains wide employments in different irrigation conditions or cultivation processes.Moreover,it becomes well-established in major areas of agricultural researches and across the broad spectrum of agricultural techniques especially in specific sectors of scientific frontiers,including soil quality,irrigation scheduling,water resource distribution,crop productivity,tillage management,climate adaptation,and environment monitoring,etc.This paper reviews the research developments and integrated applications of precision irrigation in typical domains of mechanism and performance,covering key aspects such as process optimization,schedule modelling,and effectiveness evaluation,indicating that advanced irrigation optimization methods support higher productivity of crop field and better environmental conditions of soil;Current schedule modelling techniques provide a set of instructive demonstrations and heuristic descriptions for the working principles of precision irrigation and the quantitative assessments of irrigation productivity;The novel investigation on effectiveness evaluation is extremely significant to obtain higher infiltration efficiency,simultaneously to achieve the optimized irrigation qualities for water balance condition,soil water redistribution,and soil moisture uniformity so that the effectiveness quality of irrigation infiltration could be improved remarkably.It is concluded that precision irrigation owns an outstanding collaborating capability and possesses much better working advancement in typical calibration indexes of cultivation accuracy and infiltration efficiency,meanwhile,a high agreement between the predicted and actual irrigation effectiveness could be expected.This novel irrigation review concentrating on the conceptual and systematic progress should be promoted constructively to improve the quality uniformity for precision irrigation and its constructive influences in different applications,and to facilitate the integrated management of agricultural production by higher irrigation efficiency consequently.

IoT-based monitoring and data-driven modelling of drip irrigation system for mustard leaf cultivation experiment

The changing dynamics,non-linearity of soil moisture content,as well as other weather and plant variables requires real-time monitoring and accurate predictive model for effective irrigation and crop management.In this paper,an improved monitoring and datadriven modelling of the dynamics of parameters affecting the irrigation of mustard leaf plant is presented.An IoT-based monitoring framework is implemented using ESPresso Lite V2.0 module interfaced with different soil moisture sensors(VH-400),flowmeter(YF-S201)as well as Davis vantage pro 2 weather station to measure soil moisture content,irrigation volume,and computation of the reference evapotranspiration(ETo).The data collected including plant images were transmitted to the Raspberry Pi 3 controller for onward online storage and the data are displayed on the IoT dashboard.The combination of both soil moisture and ETo values was used for scheduling a drip irrigated plant grown in a greenhouse for 35 days.A total number of 20,703 experimental data samples are collected from the IoT-based platform was further used for data driven modelling through system identification in MATLAB.The result shows the development of different predictive models for soil moisture content prediction.The ARX prediction model is found to perform better than the ARMX,BJ and State space model in terms of estimated fit of 91.31%,91.09%,91.08%,and 90.75%respectively.Therefore,a robust monitoring framework for irrigation system has been developed,while the performance of the identified ARX model is promising to predict the volumetric soil water content.