Search results for: irrigation canal monitoring

Authors: Sakshi Dhumale, Madhushree C., Amba Shetty

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The effect of station density on the geostatistical prediction of groundwater levels is of critical importance to ensure accurate and reliable predictions. Monitoring station density directly impacts the accuracy and reliability of geostatistical predictions by influencing the model's ability to capture localized variations and small-scale features in groundwater levels. This is particularly crucial in regions with complex hydrogeological conditions and significant spatial heterogeneity. Insufficient station density can result in larger prediction uncertainties, as the model may struggle to adequately represent the spatial variability and correlation patterns of the data. On the other hand, an optimal distribution of monitoring stations enables effective coverage of the study area and captures the spatial variability of groundwater levels more comprehensively. In this study, we investigate the effect of station density on the predictive performance of groundwater levels using the geostatistical technique of Ordinary Kriging. The research utilizes groundwater level data collected from 121 observation wells within the semi-arid Berambadi watershed, gathered over a six-year period (2010-2015) from the Indian Institute of Science (IISc), Bengaluru. The dataset is partitioned into seven subsets representing varying sampling densities, ranging from 15% (12 wells) to 100% (121 wells) of the total well network. The results obtained from different monitoring networks are compared against the existing groundwater monitoring network established by the Central Ground Water Board (CGWB). The findings of this study demonstrate that higher station densities significantly enhance the accuracy of geostatistical predictions for groundwater levels. The increased number of monitoring stations enables improved interpolation accuracy and captures finer-scale variations in groundwater levels. These results shed light on the relationship between station density and the geostatistical prediction of groundwater levels, emphasizing the importance of appropriate station densities to ensure accurate and reliable predictions. The insights gained from this study have practical implications for designing and optimizing monitoring networks, facilitating effective groundwater level assessments, and enabling sustainable management of groundwater resources.

Keywords: station density, geostatistical prediction, groundwater levels, monitoring networks, interpolation accuracy, spatial variability

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Authors: Hounyèmè Romuald, Maxime Logez, Mama Daouda, Argillier Christine

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In view of the very strong degradation of aquatic ecosystems, it is urgent to set up monitoring systems that are best able to report on the effects of the stresses they undergo. This is particularly true in developing countries, where specific and relevant quality standards and funding for monitoring programs are lacking. The objective of this study was to make a relevant and objective choice of physicochemical parameters informative of the main stressors occurring on African lakes and to identify their alteration thresholds. Based on statistical analyses of the relationship between several driving forces and the physicochemical parameters of the Nokoué lagoon, relevant Physico-chemical parameters were selected for its monitoring. An innovative method based on Bayesian statistical modeling was used. Eleven Physico-chemical parameters were selected for their response to at least one stressor and their threshold quality standards were also established: Total Phosphorus (<4.5mg/L), Orthophosphates (<0.2mg/L), Nitrates (<0.5 mg/L), TKN (<1.85 mg/L), Dry Organic Matter (<5 mg/L), Dissolved Oxygen (>4 mg/L), BOD (<11.6 mg/L), Salinity (7.6 .), Water Temperature (<28.7 °C), pH (>6.2), and Transparency (>0.9 m). According to the System for the Evaluation of Coastal Water Quality, these thresholds correspond to” good to medium” suitability classes, except for total phosphorus. One of the original features of this study is the use of the bounds of the credibility interval of the fixed-effect coefficients as local weathering standards for the characterization of the Physico-chemical status of this anthropized African ecosystem.

Keywords: driving forces, alteration thresholds, acadjas, monitoring, modeling, human activities

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Authors: Mohammed Ahmed Alghamdi

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Field experiment were carried out to investigate the effect of the plant growth regulator on vegetative growth and yield components of reduced height isogenic lines of the wheat (Triticum aestivum L.) cultivar Mercia. The Field experiment compared the growth regulator response of seven isogenic lines of Mercia. Growth regulators reduced plant height significantly in all lines. Growth regulator decreased total dry matter and grain yield with greatest reduction generally for the control and Rht8 lines. Rht1 was the least affected. There were few significant effects of growth regulator on gas exchange and chlorophyll fluorescence but the trend was for greater values with growth regulator. In this field experiment, a rate of 2.0 l ha-1 applied just before the third node detectable stage under non water stressed and water stressed conditions gave slight increases in yield of up to 14% except for line Rht10 which increased significantly in non-stressed conditions. In the second glasshouse experiment, a rate of 2.5 l ha-1 applied at the start of stem elongation under 30% FC and 100% FC gave reductions in yield up to 16% for the growth regulator and 55% under water stress. In the field experiment, rates of 2.5 and 3.0 l ha-1 applied at the start of stem elongation gave reductions in yield up to 20% mainly through individual seed weight. In the final glasshouse experiment, rates of 2.5 and 3.0 l ha-1 applied at 6 leaves unfolded and 1st node detectable both reduced grain yield.

Keywords: growth regulator, irrigation, isogenic lines, yield, winter wheat

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Authors: Reyhan Azeriansyah, Yudo Prasetyo, Bambang Darmo Yuwono

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Land subsidence is one of the problems that occur in the coastal areas of Java Island, one of which is the Semarang and Demak areas located in the northern region of Central Java. The impact of sea erosion, rising sea levels, soil structure vulnerable and economic development activities led to both these areas often occurs on land subsidence. To know how much land subsidence that occurred in the region needs to do the monitoring carried out by remote sensing methods such as PS-InSAR method. PS-InSAR is a remote sensing technique that is the development of the DInSAR method that can monitor the movement of the ground surface that allows users to perform regular measurements and monitoring of fixed objects on the surface of the earth. PS InSAR processing is done using Standford Method of Persistent Scatterers (StaMPS). Same as the recent analysis technique, Persistent Scatterer (PS) InSAR addresses both the decorrelation and atmospheric problems of conventional InSAR. StaMPS identify and extract the deformation signal even in the absence of bright scatterers. StaMPS is also applicable in areas undergoing non-steady deformation, with no prior knowledge of the variations in deformation rate. In addition, this method can also cover a large area so that the decline in the face of the land can cover all coastal areas of Semarang and Demak. From the PS-InSAR method can be known the impact on the existing area in Semarang and Demak region per year. The PS-InSAR results will also be compared with the GPS monitoring data to determine the difference in land decline that occurs between the two methods. By utilizing remote sensing methods such as PS-InSAR method, it is hoped that the PS-InSAR method can be utilized in monitoring the land subsidence and can assist other survey methods such as GPS surveys and the results can be used in policy determination in the affected coastal areas of Semarang and Demak.

Keywords: coastal area, Demak, land subsidence, PS-InSAR, Semarang, StaMPS

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Authors: Ayman El Sabagh, Celaleddin Barutçular, Hirofumi Saneoka

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Drought is one of the most serious problems posing a grave threat to cereals production including maize. Maize improvement in drought-stress tolerance poses a great challenge as the global need for food and bio-enegry increases. Thus, the current study was planned to explore the variations and determine the performance of target traits of maize hybrids at grain growth stage under drought conditions during 2014 under Adana, Mediterranean climate conditions, Turkey. Maize hybrids (Sancia, Indaco, 71May69, Aaccel, Calgary, 70May82, 72May80) were evaluated under (irrigated and water stress). Results revealed that, grain yield and yield traits had a negative effects because of water stress conditions compared with the normal irrigation. As well as, based on the result under normal irrigation, the maximum biological yield and harvest index were recorded. According to the differences among hybrids were found that, significant differences were observed among hybrids with respect to yield and yield traits under current research. Based on the results, grain weight had more effect on grain yield than grain number during grain filling growth stage under water stress conditions. In this concern, according to low drought susceptibility index (less grain yield losses), the hybrid (Indaco) was more stable in grain number and grain weight. Consequently, it may be concluded that this hybrid would be recommended for use in the future breeding programs for production of drought tolerant hybrids.

Keywords: drought susceptibility index, grain growth, grain yield, maize, water stress

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Authors: Mosab Aljeri, Ali Abdulraheem

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The water quality of five water types at Al-Wuhaib farm, Al-Wafra area, was studies through onsite field measurements, including pH, temperature, electrical conductivity (EC), and dissolved oxygen (DO), for four different water types. Biweekly samples were collected and analyzed for two months to obtain data of chemicals, nutrients, organics, and heavy metals. The field and laboratory results were compared with irrigation standards of Kuwait Environmental Public Authority (KEPA). The pH values of the five samples sites were within the maximum and minimum limits of KEPA standards. Based on EC values, two groups of water types were observed. The first group represents freshwater quality originated from freshwater Ministry of Electricity & Water & Renewable Energy (MEWRE) line or from freshwater tanks or treated wastewater. The second group represents brackish water type originated from groundwater or treated water mixed with groundwater. The study indicated that all nitrogen forms (ammonia, Total Kjeldahl nitrogen (TKN), Total nitrogen (TN)), total phosphate concentrations and all tested heavy metals for the five water types were below KEPA standards. These macro and micro nutrients are essential for plant growth and can be used as fertilizers. The study suggest that the groundwater should be treated and disinfected in the farming area. Also, these type of studies shall be carried out routinely to all farm areas to ensure safe water use and safe agricultural produce.

Keywords: salinity, heavy metals, ammonia, phosphate

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Authors: Karl Mabiala Dondia, Jing Ma

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In recent years, networks based on the 802.11 standards have gained a prolific deployment. The reason for this massive acceptance of the technology by both home users and corporations is assuredly due to the "plug-and-play" nature of the technology and the mobility. The lack of physical containment due to inherent nature of the wireless medium makes maintenance very challenging from a security standpoint. This study examines via continuous monitoring various predictable threats that 802.11 networks can face, how they are executed, where each attack may be executed and how to effectively defend against them. The key goal is to identify the key components of an effective wireless security policy.

Keywords: wireless LAN, IEEE 802.11 standards, continuous monitoring, security policy

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Authors: Amreth Chandrasehar

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Machine Learning (ML) Models are developed and run in production to solve various use cases that help organizations to be more efficient and help drive the business. But this comes at a massive development cost and lost business opportunities. According to the Gartner report, 85% of data science projects fail, and one of the factors impacting this is not paying attention to Model Observability. Model Observability helps the developers and operators to pinpoint the model performance issues data drift and help identify root cause of issues. This paper focuses on providing insights into incorporating model observability in model development and operationalizing it in production.

Keywords: model observability, monitoring, drift detection, ML observability platform

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Authors: Moulfi Bouchra, Ferouani Souheyla, Ziani Kerarti Djalal, Moulessehoul Wassila

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The wireless body network (WBAN) is the most interesting network these days and especially with the appearance of contagious illnesses such as covid 19, which require surveillance in the house. In this article, we have designed a circular microstrip antenna. Gold is the material used respectively for the patch and the ground plane and Gallium (εr=12.94) is chosen as the dielectric substrate. The dimensions of the antenna are 82.10*62.84 μm2 operating at a frequency of 3.85 THz. The proposed, designed antenna has a return loss of -46.046 dB and a gain of 3.74 dBi, and it can measure various physiological parameters and sensors that help in the overall monitoring of an individual's health condition.

Keywords: circular patch antenna, Terahertz transmission, WBAN applications, real-time monitoring

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Authors: T. Nishido, S. Fukumoto

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The functions of movable bearings decline due to corrosion and sediments. As the result, they cannot move or rotate according to the behaviors of girders. Because of the constraints, the bending moments are generated by the horizontal reaction forces and the heights of girders. Under these conditions, the authors obtained the following results by analysis and experiment. Tensile stresses due to the moments occurred at temperature fluctuations. The large tensile stresses on concrete slabs around the bearings caused cracks. Even if concrete slabs are newly replaced, cracks will come out again with function declined bearings. The functional declines of bearings are generally found by using displacement gauges. However the method is not suitable for long-term measurements. We focused on the change in the strains at the bearings and the lower flanges near them at temperature fluctuations. It was found that their strains were particularly large when the movements of the bearings were constrained. Therefore, we developed a long-term health monitoring wireless system with FBG (Fiber Bragg Grating) sensors which were attached to bearings and lower flanges. The FBG sensors have the characteristics such as non-electrical influence, resistance to weather, and high strain sensitivity. Such characteristics are suitable for long-term measurements. The monitoring system was inexpensive because it was limited to the purpose of measuring strains and temperature. Engineers can monitor the behaviors of bearings in real time with the wireless system. If an office is away from bridge sites, the system will save traveling time and cost.

Keywords: bridge bearing, concrete slab, 　FBG sensor, health monitoring

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Authors: Maryam Kiani

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The self-sensing capability opens up new possibilities for structural health monitoring, offering real-time information on the condition and performance of constructions. The synthesis and characterization of these functional 2D material geopolymers will be explored in this study. Various fabrication techniques, including mixing, dispersion, and coating methods, will be employed to ensure uniform distribution and integration of the 2D materials within the geopolymers. The resulting composite materials will be evaluated for their mechanical strength, electrical conductivity, and sensing capabilities through rigorous testing and analysis. The potential applications of these self-sensing geopolymers are vast. They can be used in infrastructure projects, such as bridges, tunnels, and buildings, to provide continuous monitoring and early detection of structural damage or degradation. This proactive approach to maintenance and safety can significantly improve the lifespan and efficiency of constructions, ultimately reducing maintenance costs and enhancing overall sustainability. In conclusion, the development of functional 2D material geopolymers as self-sensing materials presents an exciting advancement in the construction industry. By integrating these innovative materials into structures, we can create a new generation of intelligent, self-monitoring constructions that can adapt and respond to their environment.

Keywords: 2D materials, geopolymers, electrical properties, self-sensing

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Authors: Nicolae Constantin, Ştefan Sorohan

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The small and medium wind turbines are running in quite different conditions as compared to the big ones. Consequently, they need also a different approach concerning the structural health monitoring (SHM) issues. There are four main differences between the above mentioned categories: (i) significantly smaller dimensions, (ii) considerably higher rotation speed, (iii) generally small distance between the turbine and the energy consumer and (iv) monitoring assumed in many situations by the owner. In such conditions, nondestructive inspections (NDI) have to be made as much as possible with affordable, yet effective techniques, requiring portable and accessible equipment. Additionally, the turbines and accessories should be easy to mount, dispose and repair. As the materials used for such unit can be metals, composites and combined, the technologies should be adapted accordingly. An example in which the two materials co-exist is the situation in which the damaged metallic skin of a blade is repaired with a composite patch. The paper presents the inspection of the bonding state of the patch, using portable ultrasonic equipment, able to put in place the Lamb wave method, which proves efficient in global and local inspections as well. The equipment is relatively easy to handle and can be borrowed from specialized laboratories or used by a community of small wind turbine users, upon the case. This evaluation is the first in a row, aimed to evaluate efficiency of NDI performed with rather accessible, less sophisticated equipment and related inspection techniques, having field inspection capabilities. The main goal is to extend such inspection procedures to other components of the wind power unit, such as the support tower, water storage tanks, etc.

Keywords: structural health monitoring, small wind turbines, non-destructive inspection, field inspection capabilities

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Authors: Suraj Jena, Rabindra Kumar Panda

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The study region of the reported study was in Eastern India, having a sub-humid sub-tropical climate and sandy loam soil. The rainfall in this region has wide temporal and spatial variation. Due to lack of adequate surface water to meet the irrigation and household demands, groundwater is being over exploited in that region leading to continuous depletion of groundwater level. Therefore, there is an obvious urgency in reversing the depleting groundwater level through induced recharge, which becomes more critical under the climate change scenarios. The major goal of the reported study was to investigate the effects of climate change on groundwater recharge and subsequent adaptation strategies. Groundwater recharge was modelled using HELP3, a quasi-two-dimensional, deterministic, water-routing model along with global climate models (GCMs) and three global warming scenarios, to examine the changes in groundwater recharge rates for a 2030 climate under a variety of soil and vegetation covers. The relationship between the changing mean annual recharge and mean annual rainfall was evaluated for every combination of soil and vegetation using sensitivity analysis. The relationship was found to be statistically significant (p<0.05) with a coefficient of determination of 0.81. Vegetation dynamics and water-use affected by the increase in potential evapotranspiration for large climate variability scenario led to significant decrease in recharge from 49–658 mm to 18–179 mm respectively. Therefore, appropriate conjunctive use, irrigation schedule and enhanced recharge practices under the climate variability and land use/land cover change scenarios impacting the groundwater recharge needs to be understood properly for groundwater sustainability.

Keywords: Groundwater recharge, climate variability, Land use/cover, GCM

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Authors: Yiannis Vacanas, Kyriacos Themistocleous, Athos Agapiou, Diofantos Hadjimitsis

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Building Information Modelling (BIM) technology is considered by construction professionals as a very valuable process in modern design, procurement and project management. Construction professionals of all disciplines can use a single 3D model which BIM technology provides, to design a project accurately and furthermore monitor the progress of construction works effectively and efficiently. Unmanned Aerial Vehicles (UAVs), a technology initially developed for military applications, is now without any difficulty accessible and has already been used by commercial industries, including the construction industry. UAV technology has mainly been used for collection of images that allow visual monitoring of building and civil engineering projects conditions in various circumstances. UAVs, nevertheless, have undergone significant advances in equipment capabilities and now have the capacity to acquire high-resolution imagery from many angles in a cost effective manner, and by using photogrammetry methods, someone can determine characteristics such as distances, angles, areas, volumes and elevations of an area within overlapping images. In order to examine the potential of using a combination of BIM and UAV technologies in construction project management, this paper presents the results of a case study of a typical road construction project where the combined use of the two technologies was used in order to achieve efficient and accurate as-built data collection of the works progress, with outcomes such as volumes, and production of sections and 3D models, information necessary in project progress monitoring and efficient project management.

Keywords: BIM, project management, project monitoring, UAV

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Authors: Danika Tynes

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Telehealth is a promising advancement in health care, though there are certain conditions under which telehealth has a greater chance of success. This research sought to further the understanding of what conditions compel the success of telehealth adoption at the systems level applying Diffusion of Innovations (DoI) theory (Rogers, 1962). System-level indicators were selected to represent four components of DoI theory (relative advantage, compatibility, complexity, and observability) and regressed on 5 types of telehealth (teleradiology, teledermatology, telepathology, telepsychology, and remote monitoring) using multiple logistic regression. The analyses supported relative advantage and compatibility as the strongest influencers of telehealth adoption, remote monitoring in particular. These findings help to quantitatively clarify the factors influencing the adoption of innovation and advance the ability to make recommendations on the viability of state telehealth adoption. In addition, results indicate when DoI theory is most applicable to the understanding of telehealth diffusion. Ultimately, this research may contribute to more focused allocation of scarce health care resources through consideration of existing state conditions available foster innovation.

Keywords: adoption, diffusion of innovation theory, remote monitoring, system-level indicators

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Authors: Christian Gabriel Mariveles, Darelle Jay Gallardo, Leslie Dayaoen, Laurenz Paul Diaz

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True experimental research with descriptive analysis was conducted. Utilizing Quicklime (Calcium Oxide) for self-healing properties of coconut husk fibre concrete brick. There are 2 setups established: the first one has the 1:1:2 ratio of calcium oxide, cement and sand, and the second one has a 2:1:2 ratio of the same variables. The bricks are made from the residences along Barangay Greater Lagro. The mixture of sand and cement is mixed with coconut husk fibers and then molded with different ratios in the molder. After the drying of cement, the researchers tested the bricks in the laboratory for compressive strength. The brick with the highest PSI is picked by the researchers to drop into freefall testing, and it makes remarkable remarks as it is deformed after dropping to different heights with a maximum of 20 feet. Unfortunately, the self-healing capabilities were not observed during the 12 weeks of monitoring. However, the brick was weighed after 12 weeks of monitoring, and it increased in weight by 0.030 kg. from 1.833 kg. to 1.863 kg. meaning that this ratio 2 has the potential to self-heal, but 12 weeks of monitoring by the researchers is not enough to conclude that it has a significant difference.

Keywords: self healing, coconut husk bricks, research, calcium oxide, utilizing quicklime

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Authors: Bernabeo R. Alberto

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Unmanned aerial vehicles (UAV) platforms or remotely piloted aircraft system (Rpas) - with dedicated sensors - are fundamental support to the planning, running, and control of the territory in which public safety is or may be at risk for post-disaster assessments such as flooding or landslides, for searching lost people, for crime and accident scene photography, for assisting traffic control at major events, for teaching geography, history, natural science and all those subjects that require a continuous cyclical process of observation, evaluation and interpretation. Through the use of proximal remote sensing information related to anthropic landscape and nature integration, there is an opportunity to improve knowledge and management decision-making for the safeguarding of the environment, for farming, wildlife management, land management, mapping, glacier monitoring, atmospheric monitoring, for the conservation of archeological, historical, artistic and architectural sites, allowing an exact delimitation of the site in the territory. This paper will go over many different mission types. Within each mission type, it will give a broad overview to familiarize the reader but not make them an expert. It will also give detailed information on the payloads and other testing parameters the Unmanned Aerial Vehicles (UAV) use to complete a mission. The project's goal is to improve satellite maps about the stress of the plants, air quality monitoring, and related health issues.

Keywords: proximal remote sensing, remotely piloted aircraft system, risk, safety, unmanned aerial vehicle

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Authors: Veruska C. Dutra, Afonso R. Aquino

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Since the 1980s, global tourism activity has consolidated worldwide to become an important economic contributor, and consequently, the sociocultural and environmental impacts are starting to become evidenced. This raises the need of discussing about actions for sustainable tourism that should be linked not only to the economy, but also to the environment and social aspects. The work that is going to be presented is part of a doctoral research project in Sciences undertaken at the Sao Paulo University, Brazil. It aims to analyze whether the monitoring of the tourism sector with a focus on sustainability is applicable or not, through those indicators, put in a case study in the Jalapão State Park (JSP) conservation unit, in the state of Tocantins, Brazil. This is a study of an interdisciplinary nature that had the deductive method as its guide. We concluded that the key points of the sustainable tourism, when analyzed with the focal point in environmental indicators, are an important evaluation and quantification tool of that activity in the study locus. It displayed itself as an adequate tool for monitoring, thus decoding, the main environmental impacts that occur in tourism regions and their intensity, which is made possible through analysis, and has the objective to trace ways to prevent and correct the presented impacts.

Keywords: indicators, tourism, sustainability, Jalapão

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Authors: Christos Spandonidis, Stefanos Tsantilas, Elias Sedikos, Nektarios Galiatsatos, Fotios Giannopoulos, Panagiotis Papadopoulos, Nikolaos Demagos, Dimitrios Reppas, Christos Giordamlis

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In the present paper, a low cost, compact and modular Internet of Things (IoT) platform for air quality monitoring in urban areas is presented. This platform comprises of dedicated low cost, low power hardware and the associated embedded software that enable measurement of particles (PM2.5 and PM10), NO, CO, CO₂ and O₃ concentration in the air, along with relative temperature and humidity. This integrated platform acts as part of a greater air pollution data collecting wireless network that is able to monitor the air quality in various regions and neighborhoods of an urban area, by providing sensor measurements at a high rate that reaches up to one sample per second. It is therefore suitable for Big Data analysis applications such as air quality forecasts, weather forecasts and traffic prediction. The first real world test for the developed platform took place in Thessaloniki, Greece, where 16 devices were installed in various buildings in the city. In the near future, many more of these devices are going to be installed in the greater Thessaloniki area, giving a detailed air quality map of the city.

Keywords: distributed sensor system, environmental monitoring, Internet of Things, smart cities

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Authors: Mohamed R. Mhereeg

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The paper discusses the implementation of the MultiAgent classification System (MACS) and utilizing it to provide an automated and accurate classification of end users developing applications in the spreadsheet domain. However, different technologies have been brought together to build MACS. The strength of the system is the integration of the agent technology with the FIPA specifications together with other technologies, which are the .NET widows service based agents, the Windows Communication Foundation (WCF) services, the Service Oriented Architecture (SOA), and Oracle Data Mining (ODM). Microsoft's .NET windows service based agents were utilized to develop the monitoring agents of MACS, the .NET WCF services together with SOA approach allowed the distribution and communication between agents over the WWW. The Monitoring Agents (MAs) were configured to execute automatically to monitor excel spreadsheets development activities by content. Data gathered by the Monitoring Agents from various resources over a period of time was collected and filtered by a Database Updater Agent (DUA) residing in the .NET client application of the system. This agent then transfers and stores the data in Oracle server database via Oracle stored procedures for further processing that leads to the classification of the end user developers.

Keywords: MACS, implementation, multi-agent, SOA, autonomous, WCF

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Authors: Carlos Arias-Alcaide, Cristina Soguero-Ruiz, Paloma Santos-Álvarez, Adrián García-Romero, Inmaculada Mora-Jiménez

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Analysing clinical data with computers in such a way that have an impact on the practitioners’ workflow is a challenge nowadays. This paper provides a first approach for monitoring the health status of COVID-19 patients through the use of some biomarkers (blood tests) and the simplest Naïve Bayes classifier. Data of two Spanish hospitals were considered, showing the potential of our approach to estimate reasonable posterior probabilities even some days before the event.

Keywords: Bayesian model, blood biomarkers, classification, health tracing, machine learning, posterior probability

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Authors: Yegetaneh T. Dejenu, Delesa Kejela, Abdulak Alemu

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From the earliest time of humankind, the trenches were used for water to flow along and for soldiers to hide in during enemy attacks. Now a day due to civilization, the needs of the human being become endless, and the living condition becomes sophisticated. The unbalance between the needs and resource obligates them to find the way to manage this condition. The attempt to use the scares resource in very efficient and effective way makes the trench an endeavor practice in the world in all countries. A trencher is a construction equipment used to dig trenches, especially for laying pipes or cables, installing drainage, irrigation, installing fencing, and in preparation for trench warfare. It is a machine used to make a ditch by cutting the soil ground and effectively used in agricultural irrigation. The most common types of trencher are wheel trencher, chain trencher, micro trencher, portable trencher. In Ethiopia people have been trenching the ditch for many purposes and the tools they are using are Pickaxe, Shovel and some are using Micro Excavators. The adverse effect of using traditional equipment is, time and energy consuming, less productive, difficult and more man power is required. Hence it is necessary to design and produce low price, and simple machine to narrow this gap. Our objective is to design and model a light duty trencher that is used for trenching the ground or soil for making ditch and used for agricultural, ground cabling, ground piping, and drainage system. The designed machine trenches, maximum of 1-meter depth, 30 cm width, and the required length. The working mechanism is fully hydraulic, and the engine with 12.7 hp will provide suitable power for the pump that delivers 23 l/min at 1500 rpm to drive hydraulic motors and actuators.

Keywords: hydraulics, modelling, trenching, ditch

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Authors: Andrey V. Timofeev

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An adaptive nonparametric method is proposed for stable real-time detection of seismoacoustic sources in multichannel C-OTDR systems with a significant number of channels. This method guarantees given upper boundaries for probabilities of Type I and Type II errors. Properties of the proposed method are rigorously proved. The results of practical applications of the proposed method in a real C-OTDR-system are presented in this report.

Keywords: guaranteed detection, multichannel monitoring systems, change point, interval estimation, adaptive detection

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Authors: Guru Prakash, Revanth Dugalam

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A road’s condition often deteriorates due to harsh loading such as overload due to trucks, and severe environmental conditions such as heavy rain, snow load, and cyclic loading. In absence of proper maintenance planning, this results in potholes, wide cracks, bumps, and increased roughness of roads. In this paper, a data-driven model will be developed to detect these damages using vibration and image signals. The key idea of the proposed methodology is that the road anomaly manifests in these signals, which can be detected by training a machine learning algorithm. The use of various machine learning techniques such as the support vector machine and Radom Forest method will be investigated. The proposed model will first be trained and tested with artificially simulated data, and the model architecture will be finalized by comparing the accuracies of various models. Once a model is fixed, the field study will be performed, and data will be collected. The field data will be used to validate the proposed model and to predict the future road’s health condition. The proposed will help to automate the road condition monitoring process, repair cost estimation, and maintenance planning process.

Keywords: SVM, data-driven, road health monitoring, pot-hole

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Authors: Ivan Gunass Govender, Andrea Giampiccoli

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A developmental state should use community engagement to facilitate socio-economic development for disadvantaged groups and individual members of society through empowerment, social justice, sustainability, and self-reliance. In this regard, community-based tourism (CBT) as a growing market should be an indigenous effort aided by external facilitation. Since this form of tourism presents its own preconditions, characteristics, and challenges, it could be guided by higher education institutions engagement. In particular, the facilitation should not only serve to assist the community members to reach their own goals; but rather also focus on learning through knowledge creation and sharing with the engagement of higher education institutions. While the increased relevance of CBT has produced various CBT manuals (or handbooks/guidelines) documents aimed to ‘teach’ and assist various entities in CBT development, this research aims to analyse the current monitoring & evaluation (M&E) manuals and thereafter, propose an M&E model for CBT. It is important to mention that all too often effective monitoring is seldom carried out thus risking the long-term sustainability and improvement of the CBT ventures. Therefore, the proposed model will also consider some inputs external to the tourism field, but in relation to local economic development (LED) matters from the previously proposed development monitoring and evaluation system framework. M&E should be seen as fundamental components of any CBT initiative, and the whole CBT intervention should be evaluated. In this context, M&E in CBT should go beyond strict ‘numerical’ economic matters and should be understood in a holistic development. In addition, M&E in CBT should not consider issues in various ‘compartments’ such as tourists, tourism attractions, CBT owners/participants, and stakeholder engagement but as interdependent components of a macro-ecosystem. Finally, the external facilitation process should be structured in a way to promote community self-reliance in both the intervention and the M&E process. The research will attempt to propose an M&E model for CBT so as to enhance the CBT possibilities of long-term growth and success through effective collaborations with key stakeholders.

Keywords: community-based tourism, community-engagement, monitoring and evaluation, stakeholders

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Authors: Ali Al-Dahoud, Mohamed Fezari, Thamer Al-Rawashdeh, Ismail Jannoud

Abstract:

Monitoring and detecting faults on a set of Solar panels, using a wireless sensor network (WNS) is our contribution in this paper, This work is part of the project we are working on at Al-Zaytoonah University. The research problem has been exposed by engineers and technicians or operators dealing with PV panels maintenance, in order to monitor and detect faults within solar panels which affect considerably the energy produced by the solar panels. The proposed solution is based on installing WSN nodes with appropriate sensors for more often occurred faults on the 45 solar panels installed on the roof of IT faculty. A simulation has been done on nodes distribution and a study for the design of a node with appropriate sensors taking into account the priorities of the processing faults. Finally, a graphic user interface is designed and adapted to telemonitoring panels using WSN. The primary tests of hardware implementation gave interesting results, the sensors calibration and interference transmission problem have been solved. A friendly GUI using high level language Visial Basic was developed to carry out the monitoring process and to save data on Exel File.

Keywords: Arduino Mega microcnotroller, solar panels, fault-detection, simulation, node design

Procedia PDF Downloads 459

Authors: Thomas P. Roper, Brad Forbes, Jurij Karlovšek

Abstract:

Shear displacement along bedding defects is a well-recognised behaviour when tunnelling and mining in stratified rock. This deformation can affect the durability and integrity of installed rock bolts. In-situ monitoring of rock bolt deformation under bedding shear cannot be accurately derived from traditional strain gauge bolts as sensors are too large and spaced too far apart to accurately assess concentrated displacement along discrete defects. A possible solution to this is the use of fiber optic technologies developed for precision monitoring. Distributed Optic Sensor (DOS) embedded rock bolts were installed in a tunnel project with the aim of measuring the bolt deformation profile under significant shear displacements. This technology successfully measured the 3D strain distribution along the bolts when subjected to bedding shear and resolved the axial and lateral strain constituents in order to determine the deformational geometry of the bolts. The results are compared well with the current visual method for monitoring shear displacement using borescope holes, considering this method as suitable.

Keywords: distributed optical strain sensing, rock bolt, bedding shear, sandstone tunnel

Procedia PDF Downloads 159

Authors: Mohamed Dakki, Genevieve Robin, Marie Suet, Abdeljebbar Qninba, Mohamed A. El Agbani, Asmâa Ouassou, Rhimou El Hamoumi, Hichem Azafzaf, Sami Rebah, Claudia Feltrup-Azafzaf, Nafouel Hamouda, Wed a.L. Ibrahim, Hosni H. Asran, Amr A. Elhady, Haitham Ibrahim, Khaled Etayeb, Essam Bouras, Almokhtar Saied, Ashrof Glidan, Bakar M. Habib, Mohamed S. Sayoud, Nadjiba Bendjedda, Laura Dami, Clemence Deschamps, Elie Gaget, Jean-Yves Mondain-Monval, Pierre Defos Du Rau

Abstract:

In biodiversity monitoring, large datasets are becoming more and more widely available and are increasingly used globally to estimate species trends and con- servation status. These large-scale datasets challenge existing statistical analysis methods, many of which are not adapted to their size, incompleteness and heterogeneity. The development of scalable methods to impute missing data in incomplete large-scale monitoring datasets is crucial to balance sampling in time or space and thus better inform conservation policies. We developed a new method based on penalized Poisson models to impute and analyse incomplete monitoring data in a large-scale framework. The method al- lows parameterization of (a) space and time factors, (b) the main effects of predic- tor covariates, as well as (c) space–time interactions. It also benefits from robust statistical and computational capability in large-scale settings. The method was tested extensively on both simulated and real-life waterbird data, with the findings revealing that it outperforms six existing methods in terms of missing data imputation errors. Applying the method to 16 waterbird species, we estimated their long-term trends for the first time at the entire North African scale, a region where monitoring data suffer from many gaps in space and time series. This new approach opens promising perspectives to increase the accuracy of species-abundance trend estimations. We made it freely available in the r package ‘lori’ (https://CRAN.R-project.org/package=lori) and recommend its use for large- scale count data, particularly in citizen science monitoring programmes.

Keywords: biodiversity monitoring, high-dimensional statistics, incomplete count data, missing data imputation, waterbird trends in North-Africa

Procedia PDF Downloads 148

Authors: Adekunle Kolawole Ojo, Idowu Peter Adebayo, Egwuche Sylvester O.

Abstract:

Chronic Kidney Disease (CKD) is a significant cause of morbidity and mortality across developed and developing nations and is associated with increased risk. There are no existing electronic means of capturing and monitoring CKD in Nigeria. The work is aimed at developing a spatial data model that can be used to implement renal registries required for tracking and monitoring the spatial distribution of renal diseases by public health officers and patients. In this study, we have developed a spatial data model for a functional renal registry.

Keywords: renal registry, health informatics, chronic kidney disease, interface

Procedia PDF Downloads 199

Authors: Mira Trebar

Abstract:

Logistics processes of perishable food in the supply chain include the distribution activities and the real time temperature monitoring to fulfil the cold chain requirements. The paper presents the use of RFID (Radio Frequency Identification) technology as an identification tool of receiving and shipping activities in the cold store. At the same time, the use of RFID data loggers with temperature sensors is presented to observe and store the temperatures for the purpose of analyzing the processes and having the history data available for traceability purposes and efficient recall management.

Keywords: logistics, warehouse, RFID device, cold chain

Procedia PDF Downloads 622