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.
The removal of heavy metal ions from wastewater by ion exchange resins ( zeolite and purolite C105), was investigated. The adsorption process, which is pH dependent, shows maximum removal of metal ions at pH 6 and 7 for zeolite and purolite C105 for initial metal ion
concentrations of 50-250 mg/l, with resin dose of 0.25-3 g. The maximum ion exchange capacity was found to be 9.74, 9.23 and 9.71 mg/g for Cu2+, Pb2+, and Ni2+ on zeolite respectively, while on purolite C105 the maximum ion exchange capacity was found to be 9.64 ,8.73 and 9.39 for Cu2+, Pb2+, and Ni2+ respectively. The maximum removal was 97-98% for Cu2+ and Ni2+ and 92- 93% for Pb2+ on zeolite, while it was 93-94% for Cu2+, 96-97% for Ni2+, and 87-88% for Pb2+ on puroli
The purpose of this study is to diagnose factors that effect Thi-Qar behavioral intention to use internet. A sample of (127) internet users of university staff was taken in the study and were analyzed by using path analyze . The study concluded that there is a set of affecting correlation. It was founded that exogenous variables (gender, income, perceived fun, perceived usefulness, Image, and ease of use) has significant effect on endogenous (behavioral intention) . The result of analysis indicated that image hopeful gained users comes first, ease of use secondly, perceived fan and perceived usefulness on (dependent variables (daily internet usage and diversity of internet usage. Implication of these result are discussed . the st
... Show MoreLaser scanning has become a popular technique for the acquisition of digital models in the field of cultural heritage conservation and restoration nowadays. Many archaeological sites were lost, damaged, or faded, rather than being passed on to future generations due to many natural or human risks. It is still a challenge to accurately produce the digital and physical model of the missing regions or parts of our cultural heritage objects and restore damaged artefacts. The typical manual restoration can become a tedious and error-prone process; also can cause secondary damage to the relics. Therefore, in this paper, the automatic digital application process of 3D laser modelling of arte
Twitter data analysis is an emerging field of research that utilizes data collected from Twitter to address many issues such as disaster response, sentiment analysis, and demographic studies. The success of data analysis relies on collecting accurate and representative data of the studied group or phenomena to get the best results. Various twitter analysis applications rely on collecting the locations of the users sending the tweets, but this information is not always available. There are several attempts at estimating location based aspects of a tweet. However, there is a lack of attempts on investigating the data collection methods that are focused on location. In this paper, we investigate the two methods for obtaining location-based dat
... Show MoreThe current study sheds light on the measurement and estimation of the radioactivity of radionuclides (238U, 226Ra, 232Th, and 40k) in natural waters of different regions of Nineveh Governorate in Iraq.15 samples were collected from different sources of natural waters, where gamma-ray spectroscopy was used using NaI)TI) sodium iodide detector to determine the concentration of radioactivity in the samples. According to the results, the radioactivity concentration in the tested water sample were ranged from 0.36 ± 0.04-1.57 ± 0.09with an average value of 0.69 ± 0.06 Bq/l for 238U, and 2.9 ± 0.02-0.88 ± 0.03 with an average value of 0.65 ± 0.03 Bq/l for 226Ra Bq/l
... Show MoreWith the increasing demands to use remote sensing approaches, such as aerial photography, satellite imagery, and LiDAR in archaeological applications, there is still a limited number of studies assessing the differences between remote sensing methods in extracting new archaeological finds. Therefore, this work aims to critically compare two types of fine-scale remotely sensed data: LiDAR and an Unmanned Aerial Vehicle (UAV) derived Structure from Motion (SfM) photogrammetry. To achieve this, aerial imagery and airborne LiDAR datasets of Chun Castle were acquired, processed, analyzed, and interpreted. Chun Castle is one of the most remarkable ancient sites in Cornwall County (Southwest England) that had not been surveyed and explored
... Show MoreThe experiment was conducted in Al- Mahaweel Research Station in Babel Governorate, Ministry of Agriculture during autumn season 2016-2017 to determine the role of irrigation management processes and micronutrient fertilization in growth and productivity of two varieties of wheat IPA 99 and Al-Rasheed 22 in clay loam soil classified as Typic Torriflovent. The experiment included four irrigation treatments and six fertilization treatments. The experiment was designed under randomized complete block design (RCBD) with three replications. Wheat grain IPA 99 and Al-Rasheed 22 varieties were planted in 23/11/2016 and harvested in 13/5/2017. The amount and periods of irrigation depended on sensors reading of volumetric water content was measured
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