Wearable sensors are a revolutionary tool in agriculture because they collect accurate data on plant environmental conditions that affect plant growth in real-time. Moreover, this technology is crucial in increasing agricultural sustainability and productivity by improving irrigation strategies and water resource management. This review examines the role of wearable sensors in measuring plant water content, leaf and air humidity, stem flow, plant and air temperature, light, and soil moisture sensors. Wearable sensors are designed to monitor various plant physiological parameters in real-time. These data, obtained through wearable sensors, provide information on plant water use and physiology, making our agricultural choices more informed and accurate. Internet of Things (IoT) technologies can improve irrigation strategies and reduce water consumption by analyzing data from wearable sensors and adapting it to automate the irrigation system. The review also highlights the importance of using Artificial Intelligence (AI) to predict plant water needs accurately. This review concludes that wearable sensors provide accurate and real-time data on the stress state of plants and their surroundings, improving water management efficiency and agricultural production sustainability. These IOT and AI-enabled technologies are a crucial milestone toward smart and sustainable agriculture, which shows the importance of innovation in responding to enhanced climate threats.
An evaluation the performance of the irrigation system for the Al-Ishaqi irrigation project for the Eastern Canal was conducted to identify management strategies that can be used to improve the operation and performance of the irrigation system. The study area is located in Salah al-Din G.0overnorate, Iraq. The field work included determining the moisture content of the soil before and after irrigation, measuring the inflow of the field to find the depth of the applied water, field monitoring, and measuring the depth of the root zone for each irrigation process. Field measurements showed that the average efficiency of water application for the two fields (A, and B) are 59.81% and 38.6%, respectively. The results of the efficiency of
... Show MoreOne of the most effective systems for managing water is subsurface trickle irrigation. Finding empirical formulas and studying the effect of soil texture are the main purposes of this paper. In order to reach an ideal irrigation system as a modern technique to save water, especially in arid regions, soil textures of loam, silt, and silt loam were studied on a subsurface trickle irrigation system by utilizing HYDRUS/2D. The trickle system is usually operated at low pressure, in this paper the used pressure is 30 cm with an emitter buried at 10, 15, and 20 cm at different diameters. Patterns of wetting fronts in both directions at various times depending on soil texture are gathered to
Abstract
The study aimed to prepare a practical guide for procedures for auditing the strategies of municipal institutions in achieving sustainable development by adopting the idea of the audit matrix through which a classified report is prepared according to the dimensions of sustainable development, by preparing a specialized audit program for the purpose of auditing strategies for achieving sustainable development and emptying the results of the application of each of the paragraphs The program in the audit matrix that was prepared for the purpose of determining the impact of each observation and linkin
... Show MoreInformation hiding strategies have recently gained popularity in a variety of fields. Digital audio, video, and images are increasingly being labelled with distinct but undetectable marks that may contain a hidden copyright notice or serial number, or even directly help to prevent unauthorized duplication. This approach is extended to medical images by hiding secret information in them using the structure of a different file format. The hidden information may be related to the patient. In this paper, a method for hiding secret information in DICOM images is proposed based on Discrete Wavelet Transform (DWT). Firstly. segmented all slices of a 3D-image into a specific block size and collecting the host image depend on a generated key
... Show MoreIn this study, we review the ARIMA (p, d, q), the EWMA and the DLM (dynamic linear moodelling) procedures in brief in order to accomdate the ac(autocorrelation) structure of data .We consider the recursive estimation and prediction algorithms based on Bayes and KF (Kalman filtering) techniques for correlated observations.We investigate the effect on the MSE of these procedures and compare them using generated data.
In this paper, integrated quantum neural network (QNN), which is a class of feedforward
neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that
... Show MoreIn this study, the mobile phone traces concern an ephemeral event which represents important densities of people. This research aims to study city pulse and human mobility evolution that would be arise during specific event (Armada festival), by modelling and simulating human mobility of the observed region, depending on CDRs (Call Detail Records) data. The most pivot questions of this research are: Why human mobility studied? What are the human life patterns in the observed region inside Rouen city during Armada festival? How life patterns and individuals' mobility could be extracted for this region from mobile DB (CDRs)? The radius of gyration parameter has been applied to elaborate human life patterns with regards to (work, off) days for
... Show MoreDifferent ANN architectures of MLP have been trained by BP and used to analyze Landsat TM images. Two different approaches have been applied for training: an ordinary approach (for one hidden layer M-H1-L & two hidden layers M-H1-H2-L) and one-against-all strategy (for one hidden layer (M-H1-1)xL, & two hidden layers (M-H1-H2-1)xL). Classification accuracy up to 90% has been achieved using one-against-all strategy with two hidden layers architecture. The performance of one-against-all approach is slightly better than the ordinary approach
Data hiding is the process of encoding extra information in an image by making small modification to its pixels. To be practical, the hidden data must be perceptually invisible yet robust to common signal processing operations. This paper introduces a scheme for hiding a signature image that could be as much as 25% of the host image data and hence could be used both in digital watermarking as well as image/data hiding. The proposed algorithm uses orthogonal discrete wavelet transforms with two zero moments and with improved time localization called discrete slantlet transform for both host and signature image. A scaling factor ? in frequency domain control the quality of the watermarked images. Experimental results of signature image
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