Search results for: IoT based agriculture monitoring
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30189

Search results for: IoT based agriculture monitoring

29829 Real-Time Radiological Monitoring of the Atmosphere Using an Autonomous Aerosol Sampler

Authors: Miroslav Hyza, Petr Rulik, Vojtech Bednar, Jan Sury

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An early and reliable detection of an increased radioactivity level in the atmosphere is one of the key aspects of atmospheric radiological monitoring. Although the standard laboratory procedures provide detection limits as low as few µBq/m³, their major drawback is the delayed result reporting: typically a few days. This issue is the main objective of the HAMRAD project, which gave rise to a prototype of an autonomous monitoring device. It is based on the idea of sequential aerosol sampling using a carrousel sample changer combined with a gamma-ray spectrometer. In our hardware configuration, the air is drawn through a filter positioned on the carrousel so that it could be rotated into the measuring position after a preset sampling interval. Filter analysis is performed via a 50% HPGe detector inside an 8.5cm lead shielding. The spectrometer output signal is then analyzed using DSP electronics and Gamwin software with preset nuclide libraries and other analysis parameters. After the counting, the filter is placed into a storage bin with a capacity of 250 filters so that the device can run autonomously for several months depending on the preset sampling frequency. The device is connected to a central server via GPRS/GSM where the user can view monitoring data including raw spectra and technological data describing the state of the device. All operating parameters can be remotely adjusted through a simple GUI. The flow rate is continuously adjustable up to 10 m³/h. The main challenge in spectrum analysis is the natural background subtraction. As detection limits are heavily influenced by the deposited activity of radon decay products and the measurement time is fixed, there must exist an optimal sample decay time (delayed spectrum acquisition). To solve this problem, we adopted a simple procedure based on sequential spectrum acquisition and optimal partial spectral sum with respect to the detection limits for a particular radionuclide. The prototyped device proved to be able to detect atmospheric contamination at the level of mBq/m³ per an 8h sampling.

Keywords: aerosols, atmosphere, atmospheric radioactivity monitoring, autonomous sampler

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29828 Self-Carried Theranostic Nanoparticles for in vitro and in vivo Cancer Therapy with Real-Time Monitoring of Drug Release

Authors: Jinfeng Zhang, Chun-Sing Lee

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The use of different nanocarriers for delivering hydrophobic pharmaceutical agents to tumor sites has garnered major attention. Despite the merits of these nanocarriers, further studies are needed for improving their drug loading capacities (typically less than 10%) and reducing their potential systemic toxicity. So development of alternative self-carried nanodrug delivery strategies without using any inert carriers is highly desirable. In this study, we developed a self-carried theranostic curcumin (Cur) nanodrug for highly effective cancer therapy in vitro and in vivo with real-time monitoring of drug release. With a biocompatible C18PMH-PEG functionalization, the Cur nanoparticles (NPs) showed excellent dispersibility and outstanding stability in physiological environment, with drug loading capacity higher than 78 wt.%. Both confocal microscopy and flow cytometry confirmed the cellular fluorescent “OFF-ON” activation and real-time monitoring of Cur molecule release, showing its potential for cancer diagnosis. In vitro and in vivo experiments clearly show that therapeutic efficacy of the PEGylated Cur NPs is much better than that of free Cur. This self-carried theranostic strategy with real-time monitoring of drug release may open a new way for simultaneous cancer therapy and diagnosis.

Keywords: drug delivery, in vitro and in vivo cancer therapy, real-time monitoring, self-carried

Procedia PDF Downloads 381
29827 Residual Life Prediction for a System Subject to Condition Monitoring and Two Failure Modes

Authors: Akram Khaleghei, Ghosheh Balagh, Viliam Makis

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In this paper, we investigate the residual life prediction problem for a partially observable system subject to two failure modes, namely a catastrophic failure and a failure due to the system degradation. The system is subject to condition monitoring and the degradation process is described by a hidden Markov model with unknown parameters. The parameter estimation procedure based on an EM algorithm is developed and the formulas for the conditional reliability function and the mean residual life are derived, illustrated by a numerical example.

Keywords: partially observable system, hidden Markov model, competing risks, residual life prediction

Procedia PDF Downloads 391
29826 Conservation Agriculture in North America

Authors: Ying Chen

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Conservation Agriculture in a sustainable way of farming, as it brings many benefits, such as preventing soil from erosion and degradation, improving soil health, conserving energy, and sequestrating carbon. However, adoption of conservation agriculture has been progressing slowly in some part of the world due to some challenges. Among them, seeding in heavy crop residue is challenging, especially in corn production systems. Weed control is also challenging in conservation agriculture. This research aimed to investigate some technologies that can address these challenges. For crop residue management, vertical tillage and vertical seeding have been studied in multiple research projects. Results showed that vertical tillage and seeding were able to deal with crop residue through cutting residue into small segments, which would not plug seeder in the sub-sequent seeding. Vertical tillage is a conservation tillage system, as it leaves more than 30% crop residue on soil surface while incorporating some residue into the shallow soil layer for fast residue decomposition. For weed control, mechanical weeding can reduce chemical inputs in crop production. A tine weeder was studied for weed control during the early growing season of several field crops (corn, soybean, flax, and pea). Detail results of these studies will be shared at the conference.

Keywords: tillage, seeding, mechanical weeding, crop residue

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29825 Monitoring and Evaluation of Web-Services Quality and Medium-Term Impact on E-Government Agencies' Efficiency

Authors: A. F. Huseynov, N. T. Mardanov, J. Y. Nakhchivanski

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This practical research is aimed to improve the management quality and efficiency of public administration agencies providing e-services. The monitoring system developed will provide continuous review of the websites compliance with the selected indicators, their evaluation based on the selected indicators and ranking of services according to the quality criteria. The responsible departments in the government agencies were surveyed; the questionnaire includes issues of management and feedback, e-services provided, and the application of information systems. By analyzing the main affecting factors and barriers, the recommendations will be given that lead to the relevant decisions to strengthen the state agencies competencies for the management and the provision of their services. Component 1. E-services monitoring system. Three separate monitoring activities are proposed to be executed in parallel: Continuous tracing of e-government sites using built-in web-monitoring program; this program generates several quantitative values which are basically related to the technical characteristics and the performance of websites. The expert assessment of e-government sites in accordance with the two general criteria. Criterion 1. Technical quality of the site. Criterion 2. Usability/accessibility (load, see, use). Each high-level criterion is in turn subdivided into several sub-criteria, such as: the fonts and the color of the background (Is it readable?), W3C coding standards, availability of the Robots.txt and the site map, the search engine, the feedback/contact and the security mechanisms. The on-line survey of the users/citizens – a small group of questions embedded in the e-service websites. The questionnaires comprise of the information concerning navigation, users’ experience with the website (whether it was positive or negative), etc. Automated monitoring of web-sites by its own could not capture the whole evaluation process, and should therefore be seen as a complement to expert’s manual web evaluations. All of the separate results were integrated to provide the complete evaluation picture. Component 2. Assessment of the agencies/departments efficiency in providing e-government services. - the relevant indicators to evaluate the efficiency and the effectiveness of e-services were identified; - the survey was conducted in all the governmental organizations (ministries, committees and agencies) that provide electronic services for the citizens or the businesses; - the quantitative and qualitative measures are covering the following sections of activities: e-governance, e-services, the feedback from the users, the information systems at the agencies’ disposal. Main results: 1. The software program and the set of indicators for internet sites evaluation has been developed and the results of pilot monitoring have been presented. 2. The evaluation of the (internal) efficiency of the e-government agencies based on the survey results with the practical recommendations related to the human potential, the information systems used and e-services provided.

Keywords: e-government, web-sites monitoring, survey, internal efficiency

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29824 Coping with Climate Change in Agriculture: Perception of Farmers in Oman

Authors: B. S. Choudri

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Introduction: Climate change is a major threat to rural livelihoods and to food security in the developing world, including Oman. The aim of this study is to provide a basis for policymakers and researchers in order to understand the impacts of climate change on agriculture and developing adaptation strategies in Oman. Methodology: The data was collected from different agricultural areas across the country with the help of a questionnaire survey among farmers, discussion with community, and observations at the field level. Results: The analysis of data collected from different areas within the country shows a shift in the sowing period of major crops and increased temperatures over recent years. Farmer community is adopting through diversification of crops, use of heat-tolerant species, and improved measures of soil and water conservation. Agriculture has been the main livelihood for most of the farmer communities in rural areas in the country. Conclusions: In order to reduce the effects of climate change at the local and farmer communities, risk reduction would be important along with an in-depth analysis of the vulnerability. Therefore, capacity building of local farmers and providing them with scientific knowledge, mainstreaming adaptation into development activities would be essential with additional funding and subsidies.

Keywords: agriculture, climate change, vulnerability, adaptation

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29823 Landslide Hazard Assessment Using Physically Based Mathematical Models in Agricultural Terraces at Douro Valley in North of Portugal

Authors: C. Bateira, J. Fernandes, A. Costa

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The Douro Demarked Region (DDR) is a production Porto wine region. On the NE of Portugal, the strong incision of the Douro valley developed very steep slopes, organized with agriculture terraces, have experienced an intense and deep transformation in order to implement the mechanization of the work. The old terrace system, based on stone vertical wall support structure, replaced by terraces with earth embankments experienced a huge terrace instability. This terrace instability has important economic and financial consequences on the agriculture enterprises. This paper presents and develops cartographic tools to access the embankment instability and identify the area prone to instability. The priority on this evaluation is related to the use of physically based mathematical models and develop a validation process based on an inventory of the past embankment instability. We used the shallow landslide stability model (SHALSTAB) based on physical parameters such us cohesion (c’), friction angle(ф), hydraulic conductivity, soil depth, soil specific weight (ϱ), slope angle (α) and contributing areas by Multiple Flow Direction Method (MFD). A terraced area can be analysed by this models unless we have very detailed information representative of the terrain morphology. The slope angle and the contributing areas depend on that. We can achieve that propose using digital elevation models (DEM) with great resolution (pixel with 40cm side), resulting from a set of photographs taken by a flight at 100m high with pixel resolution of 12cm. The slope angle results from this DEM. In the other hand, the MFD contributing area models the internal flow and is an important element to define the spatial variation of the soil saturation. That internal flow is based on the DEM. That is supported by the statement that the interflow, although not coincident with the superficial flow, have important similitude with it. Electrical resistivity monitoring values which related with the MFD contributing areas build from a DEM of 1m resolution and revealed a consistent correlation. That analysis, performed on the area, showed a good correlation with R2 of 0,72 and 0,76 at 1,5m and 2m depth, respectively. Considering that, a DEM with 1m resolution was the base to model the real internal flow. Thus, we assumed that the contributing area of 1m resolution modelled by MFD is representative of the internal flow of the area. In order to solve this problem we used a set of generalized DEMs to build the contributing areas used in the SHALSTAB. Those DEMs, with several resolutions (1m and 5m), were built from a set of photographs with 50cm resolution taken by a flight with 5km high. Using this maps combination, we modelled several final maps of terrace instability and performed a validation process with the contingency matrix. The best final instability map resembles the slope map from a DEM of 40cm resolution and a MFD map from a DEM of 1m resolution with a True Positive Rate (TPR) of 0,97, a False Positive Rate of 0,47, Accuracy (ACC) of 0,53, Precision (PVC) of 0,0004 and a TPR/FPR ratio of 2,06.

Keywords: agricultural terraces, cartography, landslides, SHALSTAB, vineyards

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29822 Identification of the Relationship Between Signals in Continuous Monitoring of Production Systems

Authors: Maciej Zaręba, Sławomir Lasota

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Understanding the dependencies between the input signal, that controls the production system and signals, that capture its output, is of a great importance in intelligent systems. The method for identification of the relationship between signals in continuous monitoring of production systems is described in the paper. The method discovers the correlation between changes in the states derived from input signals and resulting changes in the states of output signals of the production system. The method is able to handle system inertia, which determines the time shift of the relationship between the input and output.

Keywords: manufacturing operation management, signal relationship, continuous monitoring, production systems

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29821 A Flute Tracking System for Monitoring the Wear of Cutting Tools in Milling Operations

Authors: Hatim Laalej, Salvador Sumohano-Verdeja, Thomas McLeay

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Monitoring of tool wear in milling operations is essential for achieving the desired dimensional accuracy and surface finish of a machined workpiece. Although there are numerous statistical models and artificial intelligence techniques available for monitoring the wear of cutting tools, these techniques cannot pin point which cutting edge of the tool, or which insert in the case of indexable tooling, is worn or broken. Currently, the task of monitoring the wear on the tool cutting edges is carried out by the operator who performs a manual inspection, causing undesirable stoppages of machine tools and consequently resulting in costs incurred from lost productivity. The present study is concerned with the development of a flute tracking system to segment signals related to each physical flute of a cutter with three flutes used in an end milling operation. The purpose of the system is to monitor the cutting condition for individual flutes separately in order to determine their progressive wear rates and to predict imminent tool failure. The results of this study clearly show that signals associated with each flute can be effectively segmented using the proposed flute tracking system. Furthermore, the results illustrate that by segmenting the sensor signal by flutes it is possible to investigate the wear in each physical cutting edge of the cutting tool. These findings are significant in that they facilitate the online condition monitoring of a cutting tool for each specific flute without the need for operators/engineers to perform manual inspections of the tool.

Keywords: machining, milling operation, tool condition monitoring, tool wear prediction

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29820 Multitemporal Satellite Images for Agriculture Change Detection in Al Jouf Region, Saudi Arabia

Authors: Ali A. Aldosari

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Change detection of Earth surface features is extremely important for better understanding of our environment in order to promote better decision making. Al-Jawf is remarkable for its abundant agricultural water where there is fertile agricultural land due largely to underground water. As result, this region has large areas of cultivation of dates, olives and fruits trees as well as other agricultural products such as Alfa Alfa and wheat. However this agricultural area was declined due to the reduction of government supports in the last decade. This reduction was not officially recorded or measured in this region at large scale or governorate level. Remote sensing data are primary sources extensively used for change detection in agriculture applications. This study is applied the technology of GIS and used the Normalized Difference Vegetation Index (NDVI) which can be used to measure and analyze the spatial and temporal changes in the agriculture areas in the Aljouf region.

Keywords: spatial analysis, geographical information system, change detection

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29819 Vibration-Based Data-Driven Model for Road Health Monitoring

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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29818 Improving Monitoring and Fault Detection of Solar Panels Using Arduino Mega in WSN

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

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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

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29817 Impact of Agriculture on the Groundwater Quality: Case of the Alluvial Plain of Nil River (North-Eastern Algerian)

Authors: S. Benessam, T. H. Debieche, A. Drouiche, F. Zahi, S. Mahdid

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The intensive use of the chemical fertilizers and the pesticides in agriculture often produces a contamination of the groundwater by organic pollutants. The irrigation and/or rainwater transport the pollutants towards groundwater or water surface. Among these pollutants, one finds the nitrogen, often observed in the agricultural zones in the nitrate form. In order to understand the form and chemical mobility of nitrogen in groundwater, this study was conducted. A two-monthly monitoring of the parameters physicochemical and chemistry of water of the alluvial plain of Nil river (North-eastern Algerian) were carried out during the period from November 2013 to January 2015 as well as an in-situ investigation of the various chemical products used by the farmers. The results show a raise concentration of nitrates in the wells (depth < 20 m) of the plain, which the concentrations arrive at 50 mg/L (standard of potable water). On the other hand in drillings (depth > 20 m), one observes two behaviors. The first in the upstream part, where the aquifer is unconfined and the medium is oxidizing, one observes the weak nitrate concentrations, indicating its absorption by the ground during the infiltration of water towards the groundwater. The second in the central and downstream parts, where the groundwater is locally confined and the reducing medium, one observes an absence of nitrates and the appearance of nitrites and ammonium, indicating the reduction of nitrates. The projection of the analyses on diagrams Eh-pH of nitrogen has enabled to us to determine the intervals of variation of the nitrogen forms. This study also highlighted the effect of the rains, the pumping and the nature of the geological formations in the form and the mobility of nitrogen in the plain.

Keywords: groundwater, nitrogen, mobility, speciation

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29816 Evaluation of Collect Tree Protocol for Structural Health Monitoring System Using Wireless Sensor Networks

Authors: Amira Zrelli, Tahar Ezzedine

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Routing protocol may enhance the lifetime of sensor network, it has a highly importance, especially in wireless sensor network (WSN). Therefore, routing protocol has a big effect in these networks, thus the choice of routing protocol must be studied before setting up our network. In this work, we implement the routing protocol collect tree protocol (CTP) which is one of the hierarchic protocols used in structural health monitoring (SHM). Therefore, to evaluate the performance of this protocol, we choice to work with Contiki system and Cooja simulator. By throughput and RSSI evaluation of each node, we will deduce about the utility of CTP in structural monitoring system.

Keywords: CTP, WSN, SHM, routing protocol

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29815 A Study to Examine the Use of Traditional Agricultural Practices to Fight the Effects of Climate Change

Authors: Rushva Parihar, Anushka Barua

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The negative repercussions of a warming planet are already visible, with biodiversity loss, water scarcity, and extreme weather events becoming ever so frequent. The agriculture sector is perhaps the most impacted, and modern agriculture has failed to defend farmers from the effects of climate change. This, coupled with the added pressure of higher demands for food production caused due to population growth, has only compounded the impact. Traditional agricultural practices that are routed in indigenous knowledge have long safeguarded the delicate balance of the ecosystem through sustainable production techniques. This paper uses secondary data to explore these traditional processes (like Beejamrita, Jeevamrita, sheep penning, earthen bunding, and others) from around the world that have been developed over centuries and focuses on how they can be used to tackle contemporary issues arising from climate change (such as nutrient and water loss, soil degradation, increased incidences of pests). Finally, the resulting framework has been applied to the context of Indian agriculture as a means to combat climate change and improve food security, all while encouraging documentation and transfer of local knowledge as a shared resource among farmers.

Keywords: sustainable food systems, traditional agricultural practices, climate smart agriculture, climate change, indigenous knowledge

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29814 Application of Transform Fourier for Dynamic Control of Structures with Global Positioning System

Authors: J. M. de Luis Ruiz, P. M. Sierra García, R. P. García, R. P. Álvarez, F. P. García, E. C. López

Abstract:

Given the evolution of viaducts, structural health monitoring requires more complex techniques to define their state. two alternatives can be distinguished: experimental and operational modal analysis. Although accelerometers or Global Positioning System (GPS) have been applied for the monitoring of structures under exploitation, the dynamic monitoring during the stage of construction is not common. This research analyzes whether GPS data can be applied to certain dynamic geometric controls of evolving structures. The fundamentals of this work were applied to the New Bridge of Cádiz (Spain), a worldwide milestone in bridge building. GPS data were recorded with an interval of 1 second during the erection of segments and turned to the frequency domain with Fourier transform. The vibration period and amplitude were contrasted with those provided by the finite element model, with differences of less than 10%, which is admissible. This process provides a vibration record of the structure with GPS, avoiding specific equipment.

Keywords: Fourier transform, global position system, operational modal analysis, structural health monitoring

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29813 A Non-Invasive Blood Glucose Monitoring System Using near-Infrared Spectroscopy with Remote Data Logging

Authors: Bodhayan Nandi, Shubhajit Roy Chowdhury

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This paper presents the development of a portable blood glucose monitoring device based on Near-Infrared Spectroscopy. The system supports Internet connectivity through WiFi and uploads the time series data of glucose concentration of patients to a server. In addition, the server is given sufficient intelligence to predict the future pathophysiological state of a patient given the current and past pathophysiological data. This will enable to prognosticate the approaching critical condition of the patient much before the critical condition actually occurs.The server hosts web applications to allow authorized users to monitor the data remotely.

Keywords: non invasive, blood glucose concentration, microcontroller, IoT, application server, database server

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29812 Co-Participation: Towards the Sustainable Micro-Rural Complex in China

Authors: Danhua Xu, Zhenlan Qian, Zhu Wang, Jiayan Fu, Ling Wang

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A new business mode called rural complex is proposed by the China’s government to promote the development the economy in the rural area. However, for the sake of current national conditions including the great number of labor farmers owning the small scale farmlands and the uncertain enthusiasm from the enterprises, it is challenging to develop the big scale rural complex. To react to the dilemmas, this paper puts forward the micro-rural complex to boost the small scale farms by co-participation from a bottom-up mode. By analyzing the potential opportunities to find the suitable mode, exploring the interdisciplinary and interdepartmental co-participation way beyond architecture design and spatial planning between different actors, the paper tries to find a complete process towards the sustainable micro-rural complex and conducts an ongoing practice to optimize it, to bring new insights and reference to the rural development. According to the transformation of the economy, the micro-rural complex will develop into two phases, both of which can be discussed in three parts, the economic mode, the spatial support, and the Cooperating mechanism. The first stage is the agriculture co-participation based on the rise of Community supported agriculture (CSA) in which the consumers buy the products planted in an organic way from the farmers directly with a higher price to support the small-scale agriculture and overcome the food safety issues. The following stage sets up the agritourism catering the citizens with the restaurants, inns and other tourist service facilities to be planned and designed. In the whole process, the interdisciplinary co-participation will play an important role to provide the guidelines and consultation from the agronomists, architects and rural planners to the farmers. This mode has been applied to an on-going farm project, from which to explore the mode in a more practical way. In conclusion, the micro-rural complex aims at creating a balanced urban-rural relationship by co-participation taking advantage of the different actors. The spatial development is considered from the economic mode and social organization. The integration of the mode based on the small-scale agriculture will contribute to a sustainable growth and realize the long run development in the rural area.

Keywords: micro-rural complex, co-participation, sustainable development, China

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29811 Smart Sensor Data to Predict Machine Performance with IoT-Based Machine Learning and Artificial Intelligence

Authors: C. J. Rossouw, T. I. van Niekerk

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The global manufacturing industry is utilizing the internet and cloud-based services to further explore the anatomy and optimize manufacturing processes in support of the movement into the Fourth Industrial Revolution (4IR). The 4IR from a third world and African perspective is hindered by the fact that many manufacturing systems that were developed in the third industrial revolution are not inherently equipped to utilize the internet and services of the 4IR, hindering the progression of third world manufacturing industries into the 4IR. This research focuses on the development of a non-invasive and cost-effective cyber-physical IoT system that will exploit a machine’s vibration to expose semantic characteristics in the manufacturing process and utilize these results through a real-time cloud-based machine condition monitoring system with the intention to optimize the system. A microcontroller-based IoT sensor was designed to acquire a machine’s mechanical vibration data, process it in real-time, and transmit it to a cloud-based platform via Wi-Fi and the internet. Time-frequency Fourier analysis was applied to the vibration data to form an image representation of the machine’s behaviour. This data was used to train a Convolutional Neural Network (CNN) to learn semantic characteristics in the machine’s behaviour and relate them to a state of operation. The same data was also used to train a Convolutional Autoencoder (CAE) to detect anomalies in the data. Real-time edge-based artificial intelligence was achieved by deploying the CNN and CAE on the sensor to analyse the vibration. A cloud platform was deployed to visualize the vibration data and the results of the CNN and CAE in real-time. The cyber-physical IoT system was deployed on a semi-automated metal granulation machine with a set of trained machine learning models. Using a single sensor, the system was able to accurately visualize three states of the machine’s operation in real-time. The system was also able to detect a variance in the material being granulated. The research demonstrates how non-IoT manufacturing systems can be equipped with edge-based artificial intelligence to establish a remote machine condition monitoring system.

Keywords: IoT, cyber-physical systems, artificial intelligence, manufacturing, vibration analytics, continuous machine condition monitoring

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29810 The Rail Traffic Management with Usage of C-OTDR Monitoring Systems

Authors: Andrey V. Timofeev, Dmitry V. Egorov

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This paper presents development results of usage of C-OTDR monitoring systems for rail traffic management. The C-OTDR method is based on vibrosensitive properties of optical fibers. Analysis of Rayleigh backscattering radiation parameters changes which take place due to microscopic seismoacoustic impacts on the optical fiber allows to determine seismoacoustic emission source positions and to identify their types. This approach proved successful for rail traffic management (moving block system, weigh- in-motion system etc).

Keywords: C-OTDR systems, moving block-sections, rail traffic management, Rayleigh backscattering, weigh-in-motion

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29809 Feasibility of Voluntary Deep Inspiration Breath-Hold Radiotherapy Technique Implementation without Deep Inspiration Breath-Hold-Assisting Device

Authors: Auwal Abubakar, Shazril Imran Shaukat, Noor Khairiah A. Karim, Mohammed Zakir Kassim, Gokula Kumar Appalanaido, Hafiz Mohd Zin

Abstract:

Background: Voluntary deep inspiration breath-hold radiotherapy (vDIBH-RT) is an effective cardiac dose reduction technique during left breast radiotherapy. This study aimed to assess the accuracy of the implementation of the vDIBH technique among left breast cancer patients without the use of a special device such as a surface-guided imaging system. Methods: The vDIBH-RT technique was implemented among thirteen (13) left breast cancer patients at the Advanced Medical and Dental Institute (AMDI), Universiti Sains Malaysia. Breath-hold monitoring was performed based on breath-hold skin marks and laser light congruence observed on zoomed CCTV images from the control console during each delivery. The initial setup was verified using cone beam computed tomography (CBCT) during breath-hold. Each field was delivered using multiple beam segments to allow a delivery time of 20 seconds, which can be tolerated by patients in breath-hold. The data were analysed using an in-house developed MATLAB algorithm. PTV margin was computed based on van Herk's margin recipe. Results: The setup error analysed from CBCT shows that the population systematic error in lateral (x), longitudinal (y), and vertical (z) axes was 2.28 mm, 3.35 mm, and 3.10 mm, respectively. Based on the CBCT image guidance, the Planning target volume (PTV) margin that would be required for vDIBH-RT using CCTV/Laser monitoring technique is 7.77 mm, 10.85 mm, and 10.93 mm in x, y, and z axes, respectively. Conclusion: It is feasible to safely implement vDIBH-RT among left breast cancer patients without special equipment. The breath-hold monitoring technique is cost-effective, radiation-free, easy to implement, and allows real-time breath-hold monitoring.

Keywords: vDIBH, cone beam computed tomography, radiotherapy, left breast cancer

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29808 Participatory Monitoring Strategy to Address Stakeholder Engagement Impact in Co-creation of NBS Related Project: The OPERANDUM Case

Authors: Teresa Carlone, Matteo Mannocchi

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In the last decade, a growing number of International Organizations are pushing toward green solutions for adaptation to climate change. This is particularly true in the field of Disaster Risk Reduction (DRR) and land planning, where Nature-Based Solutions (NBS) had been sponsored through funding programs and planning tools. Stakeholder engagement and co-creation of NBS is growing as a practice and research field in environmental projects, fostering the consolidation of a multidisciplinary socio-ecological approach in addressing hydro-meteorological risk. Even thou research and financial interests are constantly spread, the NBS mainstreaming process is still at an early stage as innovative concepts and practices make it difficult to be fully accepted and adopted by a multitude of different actors to produce wide scale societal change. The monitoring and impact evaluation of stakeholders’ participation in these processes represent a crucial aspect and should be seen as a continuous and integral element of the co-creation approach. However, setting up a fit for purpose-monitoring strategy for different contexts is not an easy task, and multiple challenges emerge. In this scenario, the Horizon 2020 OPERANDUM project, designed to address the major hydro-meteorological risks that negatively affect European rural and natural territories through the co-design, co-deployment, and assessment of Nature-based Solution, represents a valid case study to test a monitoring strategy from which set a broader, general and scalable monitoring framework. Applying a participative monitoring methodology, based on selected indicators list that combines quantitative and qualitative data developed within the activity of the project, the paper proposes an experimental in-depth analysis of the stakeholder engagement impact in the co-creation process of NBS. The main focus will be to spot and analyze which factors increase knowledge, social acceptance, and mainstreaming of NBS, promoting also a base-experience guideline to could be integrated with the stakeholder engagement strategy in current and future similar strongly collaborative approach-based environmental projects, such as OPERANDUM. Measurement will be carried out through survey submitted at a different timescale to the same sample (stakeholder: policy makers, business, researchers, interest groups). Changes will be recorded and analyzed through focus groups in order to highlight causal explanation and to assess the proposed list of indicators to steer the conduction of similar activities in other projects and/or contexts. The idea of the paper is to contribute to the construction of a more structured and shared corpus of indicators that can support the evaluation of the activities of involvement and participation of various levels of stakeholders in the co-production, planning, and implementation of NBS to address climate change challenges.

Keywords: co-creation and collaborative planning, monitoring, nature-based solution, participation & inclusion, stakeholder engagement

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29807 The Results of Longitudinal Water Quality Monitoring of the Brandywine River, Chester County, Pennsylvania by High School Students

Authors: Dina L. DiSantis

Abstract:

Strengthening a sense of responsibility while relating global sustainability concepts such as water quality and pollution to a local water system can be achieved by teaching students to conduct and interpret water quality monitoring tests. When students conduct their own research, they become better stewards of the environment. Providing outdoor learning and place-based opportunities for students helps connect them to the natural world. By conducting stream studies and collecting data, students are able to better understand how the natural environment is a place where everything is connected. Students have been collecting physical, chemical and biological data along the West and East Branches of the Brandywine River, in Pennsylvania for over ten years. The stream studies are part of the advanced placement environmental science and aquatic science courses that are offered as electives to juniors and seniors at the Downingtown High School West Campus in Downingtown, Pennsylvania. Physical data collected includes: temperature, turbidity, width, depth, velocity, and volume of flow or discharge. The chemical tests conducted are: dissolved oxygen, carbon dioxide, pH, nitrates, alkalinity and phosphates. Macroinvertebrates are collected with a kick net, identified and then released. Students collect the data from several locations while traveling by canoe. In the classroom, students prepare a water quality data analysis and interpretation report based on their collected data. The summary of the results from longitudinal water quality data collection by students, as well as the strengths and weaknesses of student data collection will be presented.

Keywords: place-based, student data collection, sustainability, water quality monitoring

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29806 Challenges of Water License in Agriculture Sector in British Columbia: An Exploratory Sociological Inquiry

Authors: Mandana Karimi, Martha McMahon

Abstract:

One of the most important consequences of water scarcity worldwide is the increase in conflicts over water issues, reduced access to clean water, food shortages, energy shortages, and reduced economic development. The extreme weather conditions in British Columbia are because of climate change, which is leading to water scarcity becoming a serious issue affecting British Columbians, aquatic ecosystems, the BC water policy, agriculture, and the economy. In light of climate change and water stress, the British Columbia government introduced a new water legislation in 2016 named the Water Sustainability Act to manage water resources in British Columbia. So, this study aimed to present a deep understanding emanating from the political and social dimensions of the new water policy in BC in the agriculture sector and which sociological paradigm governs the current water policy (WSA) in BC. Policy analysis based on the water problem representation approach was used to present the problem and solutions identified by the water policy in the agricultural sector in BC. The results of the policy analysis highlighted that the Water Sustainability Act is governed by a positivist and modernist approach because the groundwater license is the measurable situation to access the adequate quantity of water for the farmers. In addition, by the positivist paradigm water resources are conceptualized as a commodity to be bought and sold. Under the positivist approach, the measurable parameter of groundwater is also applied based on the top-down approach for water management to show the use of water resources for economic development. In addition, the findings of the policy analysis suggest that alternative paradigms, such as relational ontology, ecofeminism, and indigenous knowledge, could be applied in introducing water policies to shift from the positivist or modernist paradigm. These new paradigms present the potential for environmental policies like the Water Sustainability Act, based on partnership, and collaboration and with an explicit emphasis on protecting water for nature.

Keywords: water governance, Water Sustainability Act, water policy, small-scale farmer, policy analysis

Procedia PDF Downloads 52
29805 A Case Study on the Long-Term Stability Monitoring of Underground Powerhouse Complex Using Geotechnical Instrumentation

Authors: Sudhakar Kadiyala, Sripad R. Naik

Abstract:

Large cavern in Bhutan Himalayas is being monitored since the construction period. The behavior of the cavern is being monitored for last 16 years. Instrumentation includes measurement of convergence of high walls by geodetic monitoring, load on the support systems with load cells and instrumented bolts. Analysis of the results of instrumentation showed that during the construction period of the cavern, the convergence of the cavern varied from 181 - 233 mm in the unit bay area with maximum convergence rate of 2.80mm/day. Whereas during the operational period the total convergence observed was in the range of 21 to 45 mm during a period of 11.30 years with convergence rate of 0.005 to 0.011 mm/day. During the last five years, there were no instances of high tensile stress recorded by the instrumented bolts. Load on the rock bolts have shown stabilization trend at most of the locations. This paper discusses in detail the results of long-term monitoring using the geotechnical instruments and how the data is being used in 3D numerical model to confirm the stability of the cavern.

Keywords: convergence, displacements, geodetic monitoring, long-term stability

Procedia PDF Downloads 162
29804 A Hybrid Normalized Gradient Correlation Based Thermal Image Registration for Morphoea

Authors: L. I. Izhar, T. Stathaki, K. Howell

Abstract:

Analyzing and interpreting of thermograms have been increasingly employed in the diagnosis and monitoring of diseases thanks to its non-invasive, non-harmful nature and low cost. In this paper, a novel system is proposed to improve diagnosis and monitoring of morphoea skin disorder based on integration with the published lines of Blaschko. In the proposed system, image registration based on global and local registration methods are found inevitable. This paper presents a modified normalized gradient cross-correlation (NGC) method to reduce large geometrical differences between two multimodal images that are represented by smooth gray edge maps is proposed for the global registration approach. This method is improved further by incorporating an iterative-based normalized cross-correlation coefficient (NCC) method. It is found that by replacing the final registration part of the NGC method where translational differences are solved in the spatial Fourier domain with the NCC method performed in the spatial domain, the performance and robustness of the NGC method can be greatly improved. It is shown in this paper that the hybrid NGC method not only outperforms phase correlation (PC) method but also improved misregistration due to translation, suffered by the modified NGC method alone for thermograms with ill-defined jawline. This also demonstrates that by using the gradients of the gray edge maps and a hybrid technique, the performance of the PC based image registration method can be greatly improved.

Keywords: Blaschko’s lines, image registration, morphoea, thermal imaging

Procedia PDF Downloads 291
29803 A Literature Review of Precision Agriculture: Applications of Diagnostic Diseases in Corn, Potato, and Rice Based on Artificial Intelligence

Authors: Carolina Zambrana, Grover Zurita

Abstract:

The food loss production that occurs in deficient agricultural production is one of the major problems worldwide. This puts the population's food security and the efficiency of farming investments at risk. It is to be expected that this food security will be achieved with the own and efficient production of each country. It will have an impact on the well-being of its population and, thus, also on food sovereignty. The production losses in quantity and quality occur due to the lack of efficient detection of diseases at an early stage. It is very difficult to solve the agriculture efficiency using traditional methods since it takes a long time to be carried out due to detection imprecision of the main diseases, especially when the production areas are extensive. Therefore, the main objective of this research study is to perform a systematic literature review, of the latest five years, of Precision Agriculture (PA) to be able to understand the state of the art of the set of new technologies, procedures, and optimization processes with Artificial Intelligence (AI). This study will focus on Corns, Potatoes, and Rice diagnostic diseases. The extensive literature review will be performed on Elsevier, Scopus, and IEEE databases. In addition, this research will focus on advanced digital imaging processing and the development of software and hardware for PA. The convolution neural network will be handling special attention due to its outstanding diagnostic results. Moreover, the studied data will be incorporated with artificial intelligence algorithms for the automatic diagnosis of crop quality. Finally, precision agriculture with technology applied to the agricultural sector allows the land to be exploited efficiently. This system requires sensors, drones, data acquisition cards, and global positioning systems. This research seeks to merge different areas of science, control engineering, electronics, digital image processing, and artificial intelligence for the development, in the near future, of a low-cost image measurement system that allows the optimization of crops with AI.

Keywords: precision agriculture, convolutional neural network, deep learning, artificial intelligence

Procedia PDF Downloads 60
29802 Model of a Context-Aware Middleware for Mobile Workers

Authors: Esraa Moustafa, Gaetan Rey, Stephane Lavirotte, Jean-Yves Tigli

Abstract:

With the development of Internet of Things and Web of Things, computing becomes more pervasive, invisible and present everywhere. In fact, in our environment, we are surrounded by multiple devices that deliver (web) services that meet the needs of the users. However, the mobility of these devices as the users has important repercussions that challenge software design of these applications because the variability of the environment cannot be anticipated at the design time. Thus, it will be interesting to dynamically discover the environment and adapt the application during its execution to the new contextual conditions. We, therefore, propose a model of a context-aware middleware that can address this issue through a monitoring service that is capable of reasoning and observation channels capable of calculating the context during the runtime. The monitoring service evaluates the pre-defined X-Query predicates in the context manager and uses Prolog to deduce the services needed to respond back. An independent Observation Channel for each different predicate is then dynamically generated by the monitoring service depending on the current state of the environment. Each channel sends its result directly to the context manager which consequently calculates the context based on all the predicates’ results while preserving the reactivity of the self-adaptive system.

Keywords: auto-adaptation, context-awareness, middleware, reasoning engine

Procedia PDF Downloads 231
29801 Role of Agriculture Equipment toward Food Security: Case Study of Agriculture Equipment Assistance during President Joko Widodo Era in Indonesia

Authors: Raihan Zahirah Mauludy Ridwan, Frisca Devi Choirina

Abstract:

Indonesia is an agrarian country endowed by fertile soil, supportive weather, and natural resources which can support agricultural activities. There are commodities which produced by local farmers. Even though Indonesia had commodities, it still imports stocks of staple food. To reduce the dependency on imported staple food, President Joko Widodo wants to generate more locally-produced staple food by giving 69.000 tractors, free seeds, and fertilizers to the local farmers. In Indonesia, the problem revolves around the amount of food production especially rice derived from farmers who cannot afford technologies which can support the agricultural activities. Moreover, they cannot afford seeds and fertilizers which can make the production of commodities more effective and have high quality. Therefore, the paper would like to answer how agriculture equipment assistance during President Joko Widodo era can give significant impact towards food security. The purpose of this paper is to explore the role of agriculture equipment assistance and its impact towards Indonesia’s food security. This paper uses Boserup and Ruthenberg theory of agricultural intensification to link agriculture equipment and intensification of production which in the end will have impact towards food security through case study method. The paper affirms that the role of agricultural equipment assistance toward food security in Indonesia is significant toward Indonesia’s food production and security.

Keywords: agricultural equipment, agricultural intensification, Boserup, Indonesia, Joko Widodo, Ruthenberg

Procedia PDF Downloads 163
29800 A Different Approach to Smart Phone-Based Wheat Disease Detection System Using Deep Learning for Ethiopia

Authors: Nathenal Thomas Lambamo

Abstract:

Based on the fact that more than 85% of the labor force and 90% of the export earnings are taken by agriculture in Ethiopia and it can be said that it is the backbone of the overall socio-economic activities in the country. Among the cereal crops that the agriculture sector provides for the country, wheat is the third-ranking one preceding teff and maize. In the present day, wheat is in higher demand related to the expansion of industries that use them as the main ingredient for their products. The local supply of wheat for these companies covers only 35 to 40% and the rest 60 to 65% percent is imported on behalf of potential customers that exhaust the country’s foreign currency reserves. The above facts show that the need for this crop in the country is too high and in reverse, the productivity of the crop is very less because of these reasons. Wheat disease is the most devastating disease that contributes a lot to this unbalance in the demand and supply status of the crop. It reduces both the yield and quality of the crop by 27% on average and up to 37% when it is severe. This study aims to detect the most frequent and degrading wheat diseases, Septoria and Leaf rust, using the most efficiently used subset of machine learning technology, deep learning. As a state of the art, a deep learning class classification technique called Convolutional Neural Network (CNN) has been used to detect diseases and has an accuracy of 99.01% is achieved.

Keywords: septoria, leaf rust, deep learning, CNN

Procedia PDF Downloads 55