Search results for: IoT based agriculture monitoring

Authors: Ahmed Noor Al-Qayyim

Abstract:

During the past decades, the bridge structures are considered very important portions of transportation networks, due to the fast urban sprawling. With the failure of bridges that under operating conditions lead to focus on updating the default bridge inspection methodology. The structures health monitoring (SHM) using the vibration response appeared as a promising method to evaluate the condition of structures. The rapid development in the sensors technology and the condition assessment techniques based on the vibration-based damage detection made the SHM an efficient and economical ways to assess the bridges. SHM is set to assess state and expects probable failures of designated bridges. In this paper, a presentation for Frequency Response function method that uses the captured vibration test information of structures to evaluate the structure condition. Furthermore, the main steps of the assessment of bridge using the vibration information are presented. The Frequency Response function method is applied to the experimental data of a full-scale bridge.

Keywords: bridge assessment, health monitoring, damage detection, frequency response function (FRF), signal processing, structure identification

Procedia PDF Downloads 348

Authors: Yonwaba Atyosi, Moses Cho, Abel Ramoelo, Nobuhle Majozi, Cecilia Masemola, Yoliswa Mkhize

Abstract:

Spectroscopy has been widely used to understand the hyperspectral remote sensing of soils. Accurate and efficient measurement of soil moisture is essential for precision agriculture. The aim of this study was to understand the spectral behavior of soil at different soil water content levels and identify the significant spectral bands for soil moisture content retrieval at field-scale. The study consisted of 60 soil samples from a maize farm, divided into four different treatments representing different moisture levels. Spectral signatures were measured for each sample in laboratory under artificial light using an Analytical Spectral Device (ASD) spectrometer, covering a wavelength range from 350 nm to 2500 nm, with a spectral resolution of 1 nm. The results showed that the absorption features at 1450 nm, 1900 nm, and 2200 nm were particularly sensitive to soil moisture content and exhibited strong correlations with the water content levels. Continuum removal was developed in the R programming language to enhance the absorption features of soil moisture and to precisely understand its spectral behavior at different water content levels. Statistical analysis using partial least squares regression (PLSR) models were performed to quantify the correlation between the spectral bands and soil moisture content. This study provides insights into the spectral behavior of soil at different water content levels and identifies the significant spectral bands for soil moisture content retrieval. The findings highlight the potential of spectroscopy for non-destructive and rapid soil moisture measurement, which can be applied to various fields such as precision agriculture, hydrology, and environmental monitoring. However, it is important to note that the spectral behavior of soil can be influenced by various factors such as soil type, texture, and organic matter content, and caution should be taken when applying the results to other soil systems. The results of this study showed a good agreement between measured and predicted values of Soil Moisture Content with high R2 and low root mean square error (RMSE) values. Model validation using independent data was satisfactory for all the studied soil samples. The results has significant implications for developing high-resolution and precise field-scale soil moisture retrieval models. These models can be used to understand the spatial and temporal variation of soil moisture content in agricultural fields, which is essential for managing irrigation and optimizing crop yield.

Keywords: soil moisture content retrieval, precision agriculture, continuum removal, remote sensing, machine learning, spectroscopy

Procedia PDF Downloads 99

Authors: Eugene Aninagyei-Bonsu

Abstract:

Introduction: Agriculture has been a cornerstone of human civilization, ensuring food security and livelihoods for billions of people worldwide. In recent decades, rapid advancements in technology have revolutionized the agricultural sector, offering innovative solutions to enhance productivity, sustainability, and efficiency. This abstract summarizes key findings from a research study that explores the impacts of technology in modern agriculture and its implications for future food production systems. Methodologies: The research study employed a mixed-methods approach, combining quantitative data analysis with qualitative interviews and surveys to gain a comprehensive understanding of the role of technology in agriculture. Data was collected from various stakeholders, including farmers, agricultural technicians, and industry experts, to capture diverse perspectives on the adoption and utilization of agricultural technologies. The study also utilized case studies and literature reviews to contextualize the findings within the broader agricultural landscape. Major Findings: The research findings reveal that technology plays a pivotal role in transforming traditional farming practices and driving innovation in agriculture. Advanced technologies such as precision agriculture, drone technology, genetic engineering, and smart irrigation systems have significantly improved crop yields, reduced environmental impact, and optimized resource utilization. Farmers who have embraced these technologies have reported increased productivity, enhanced profitability, and improved resilience to environmental challenges. Furthermore, the study highlights the importance of accessible and affordable technology solutions for smallholder farmers in developing countries. Mobile applications, sensor technologies, and digital platforms have enabled small-scale farmers to access market information, weather forecasts, and agricultural best practices, empowering them to make informed decisions and improve their livelihoods. The research emphasizes the need for targeted policies and investments to bridge the digital divide and promote equitable technology adoption in agriculture. Conclusion: In conclusion, this research underscores the transformative potential of technology in agriculture and its critical role in advancing sustainable food production systems. The findings suggest that harnessing technology can address key challenges facing the agricultural sector, including climate change, resource scarcity, and food insecurity. By embracing innovation and leveraging technology, farmers can enhance their productivity, profitability, and resilience in a rapidly evolving global food system. Moving forward, policymakers, researchers, and industry stakeholders must collaborate to facilitate the adoption of appropriate technologies, support capacity building, and promote sustainable agricultural practices for a more resilient and food-secure future.

Keywords: technology development in modern agriculture, the influence of information technology access in agriculture, analyzing agricultural technology development, analyzing of the frontier technology of agriculture loT

Procedia PDF Downloads 35

Authors: Georgii Emelianov, Mikhail Polikarpov, Fabian Hübner, Jochen Deuse, Jochen Schiemann

Abstract:

Recycling refrigerating appliances plays a major role in protecting the Earth's atmosphere from ozone depletion and emissions of greenhouse gases. The performance of refrigerator recycling plants in terms of material retention is the subject of strict environmental certifications and is reviewed periodically through specialized audits. The continuous collection of Refrigerator data required for the input-output analysis is still mostly manual, error-prone, and not digitalized. In this paper, we propose an automated data collection system for recycling plants in order to deduce expected material contents in individual end-of-life refrigerating appliances. The system utilizes laser scanner measurements and optical data to extract attributes of individual refrigerators by applying transfer learning with pre-trained vision models and optical character recognition. Based on Recognized features, the system automatically provides material categories and target values of contained material masses, especially foaming and cooling agents. The presented data collection system paves the way for continuous performance monitoring and efficient control of refrigerator recycling plants.

Keywords: automation, data collection, performance monitoring, recycling, refrigerators

Procedia PDF Downloads 164

Authors: Simonida S. Djuric, Timea I. Hajnal Jafari, Dragana R. Stamenov

Abstract:

The use of plant growth promoting fungi (PGPF) has significantly increased in the last decade mostly due to their multi-level properties, and their expected success as biofertilizers in agriculture. Beneficial fungi with broad-host range undergo long-term interactions with a large variety of plants thereby playing a significant role in managed ecosystems and in the adaptation of crops to global climate changes. Trichoderma spp. are promising fungi toward the development of sustainable agriculture. The aim of our experiment was to investigate the effect of seed inoculation of sunflower, maize, soybean, paprika, melon, and watermelon seeds with Trichoderma sp. on early seed germination energy and initial growth of the plant. The seed inoculation with Trichoderma sp. increased the seedling emergence from 7, 85% in melon to 156,70% in watermelon. The inoculation had the best effect on initial growth of maize shoot (+23,80%) and soybean root (+106,30%). The different response of seed and young plants on Trichoderma sp. inoculation implicate the need for future investigations of successful inoculation systems and modes of their integration in sustainable agriculture production systems.

Keywords: initial growth, inoculation, seedling, Trichoderma sp.

Procedia PDF Downloads 240

Authors: Yu-Tzu Chen, Luh-Maan Chang

Abstract:

Construction is an inherently risky industry. The projects have been dominated by reactive actions owing to non-routine in nature. The on-site activities are especially crucial for successful project control. In order to alter actions from reactive to proactive, this paper presents an on-site data collection system utilizing advanced technology RFID and GPS in assisting on-site management with near real time progress monitoring.

Keywords: On-Site management, progress monitoring, RFID, GPS

Procedia PDF Downloads 568

Authors: Felipe B. Martinez, Imelda C. Galera

Abstract:

This paper presents an update on the physico-chemical properties of the Taal Lake for local government officials and representatives of non-government organizations by monitoring and evaluating a total of nine (9) water quality parameters. The study further shows that the Taal Lakes surface temperature, pH, total dissolved solids, total suspended solids, color, and dissolved oxygen content conform to the standards set by the Department of Environment and Natural resources (DENR); while phosphate, chlorine, and 5-Day 20°C BOD are below the standard. Likewise, the T-test result shows no significant difference in the overall average of the two sites at the Taal Lake (P > 0.05). Based on the data, the Lake is safe for primary contact recreation such as bathing, swimming and skin diving, and can be used for aqua culture purposes.

Keywords: cool dry season, hot dry season, rainy season, Taal Lake, water quality

Procedia PDF Downloads 308

Authors: Arun Dhakal, Geoff Cockfield

Abstract:

This paper examines the emission potential of different farming practices that the farmers have adopted in Dhanusha District of Nepal and scope of these practices in climate change mitigation. Which practice is more climate-smarter is the question that this aims to address through a life cycle assessment (LCA) of greenhouse gas (GHG) emissions. The LCA was performed to assess if there is difference in emission potential of broadly two farming systems (agroforestry–based and traditional agriculture) but specifically four farming systems. The required data for this was collected through household survey of randomly selected households of 200. The sources of emissions across the farming systems were paddy cultivation, livestock, chemical fertilizer, fossil fuels and biomass (fuel-wood and crop residue) burning. However, the amount of emission from these sources varied with farming system adopted. Emissions from biomass burning appeared to be the highest while the source ‘fossil fuel’ caused the lowest emission in all systems. The emissions decreased gradually from agriculture towards the highly integrated agroforestry-based farming system (HIS), indicating that integrating trees into farming system not only sequester more carbon but also help in reducing emissions from the system. The annual emissions for HIS, Medium integrated agroforestry-based farming system (MIS), LIS (less integrated agroforestry-based farming system and subsistence agricultural system (SAS) were 6.67 t ha-1, 8.62 t ha-1, 10.75 t ha-1 and 17.85 t ha-1 respectively. In one agroforestry cycle, the HIS, MIS and LIS released 64%, 52% and 40% less GHG emission than that of SAS. Within agroforestry-based farming systems, the HIS produced 25% and 50% less emissions than those of MIS and LIS respectively. Our finding suggests that a tree-based farming system is more climate-smarter than a traditional farming. If other two benefits (carbon sequestered within the farm and in the natural forest because of agroforestry) are to be considered, a considerable amount of emissions is reduced from a climate-smart farming. Some policy intervention is required to motivate farmers towards adopting such climate-friendly farming practices in developing countries.

Keywords: life cycle assessment, greenhouse gas, climate change, farming systems, Nepal

Procedia PDF Downloads 619

Authors: Marc S. Paolella, Pawel Polak

Abstract:

The paper proposes a framework for large-scale portfolio optimization which accounts for all the major stylized facts of multivariate financial returns, including volatility clustering, dynamics in the dependency structure, asymmetry, heavy tails, and non-ellipticity. It introduces a so-called risk fear portfolio strategy which combines portfolio optimization with active risk monitoring. The former selects optimal portfolio weights. The latter, independently, initiates market exit in case of excessive risks. The strategy agrees with the stylized fact of stock market major sell-offs during the initial stage of market downturns. The advantages of the new framework are illustrated with an extensive empirical study. It leads to superior multivariate density and Value-at-Risk forecasting, and better portfolio performance. The proposed risk fear portfolio strategy outperforms various competing types of optimal portfolios, even in the presence of conservative transaction costs and frequent rebalancing. The risk monitoring of the optimal portfolio can serve as an early warning system against large market risks. In particular, the new strategy avoids all the losses during the 2008 financial crisis, and it profits from the subsequent market recovery.

Keywords: comfort, financial crises, portfolio optimization, risk monitoring

Procedia PDF Downloads 525

Authors: C. Lanzerstorfer

Abstract:

Liquid sprays of water are frequently used in air pollution control for gas cooling purposes and for gas cleaning. Twin-fluid nozzles with internal mixing are often used for these purposes because of the small size of the drops produced. In these nozzles the liquid is dispersed by compressed air or another pressurized gas. In high efficiency scrubbers for particle separation, several nozzles are operated in parallel because of the size of the cross section. In such scrubbers, the scrubbing water has to be re-circulated. Precipitation of some solid material can occur in the liquid circuit, caused by chemical reactions. When such precipitations are detached from the place of formation, they can partly or totally block the liquid flow to a nozzle. Due to the resulting unbalanced supply of the nozzles with water and gas, the efficiency of separation decreases. Thus, the nozzles have to be cleaned if a certain fraction of blockages is reached. The aim of this study was to provide a tool for continuously monitoring the status of the nozzles of a scrubber based on the available operation data (water flow, air flow, water pressure and air pressure). The difference between the air pressure and the water pressure is not well suited for this purpose, because the difference is quite small and therefore very exact calibration of the pressure measurement would be required. Therefore, an equation for the reference air flow of a nozzle at the actual water flow and operation pressure was derived. This flow can be compared with the actual air flow for assessment of the status of the nozzles.

Keywords: condition monitoring, dual flow nozzles, flow equation, operation data

Procedia PDF Downloads 266

Authors: Theodrose Sisay, Kindie Tesfaye, Mengistu Ketema, Nigussie Dechassa, Mezegebu Getnet

Abstract:

Agriculture is a sector that is very vulnerable to the effects of climate change and contributes to anthropogenic greenhouse gas (GHG) emissions in the atmosphere. By lowering emissions and adjusting to the change, it can also help to reduce climate change. Utilizing Climate-Smart Agriculture (CSA) technology that can sustainably boost productivity, improve resilience, and lower GHG emissions is crucial. This study sought to identify the CSA technologies used by farmers and assess adoption levels and factors that influence them. In order to gather information from 384 smallholder farmers in the Great Rift Valley (GRV) of Ethiopia, a cross-sectional survey was carried out. Data were analysed using percentage, chi-square test, t-test, and multivariate probit model. Results showed that crop diversification, agroforestry, and integrated soil fertility management were the most widely practiced technologies. The results of the Chi-square and t-tests showed that there are differences and significant and positive connections between adopters and non-adopters based on various attributes. The chi-square and t-test results confirmed that households who were older had higher incomes, greater credit access, knowledge of the climate, better training, better education, larger farms, higher incomes, and more frequent interactions with extension specialists had a positive and significant association with CSA technology adopters. The model result showed that age, sex, and education of the head, farmland size, livestock ownership, income, access to credit, climate information, training, and extension contact influenced the selection of CSA technologies. Therefore, effective action must be taken to remove barriers to the adoption of CSA technologies, and taking these adoption factors into account in policy and practice is anticipated to support smallholder farmers in adapting to climate change while lowering emissions.

Keywords: climate change, climate-smart agriculture, smallholder farmers, multivariate probit model

Procedia PDF Downloads 127

Authors: M. Cuevas-González, O. Monserrat, A. Barra, C. Reyes-Carmona, R.M. Mateos, J. P. Galve, R. Sarro, M. Cantalejo, E. Peña, M. Martínez-Corbella, J. A. Luque, J. M. Azañón, A. Millares, M. Béjar, J. A. Navarro, L. Solari

Abstract:

Geohazard prone areas require continuous monitoring to detect risks, understand the phenomena occurring in those regions and prevent disasters. Satellite interferometry (InSAR) has come to be a trustworthy technique for ground movement detection and monitoring in the last few years. InSAR based techniques allow to process large areas providing high number of displacement measurements at low cost. However, the results provided by such techniques are usually not easy to interpret by non-experienced users hampering its use for decision makers. This work presents a set of tools developed in the framework of different projects (Momit, Safety, U-Geohaz, Riskcoast) and an example of their use in the Granada Coastal area (Spain) is shown. The ADA (Active Displacement Areas) tool have been developed with the aim of easing the management, use and interpretation of InSAR based results. It provides a semi-automatic extraction of the most significant ADAs through the application ADAFinder tool. This tool aims to support the exploitation of the European Ground Motion Service (EU-GMS), which will provide consistent, regular and reliable information regarding natural and anthropogenic ground motion phenomena all over Europe.

Keywords: ground displacements, InSAR, natural hazards, satellite imagery

Procedia PDF Downloads 219

Authors: Bikramjit Goswami, Manoranjan Kalita

Abstract:

Active microwave remote sensing is useful in remote sensing applications in cloud-covered regions in the world. Because of high spatial resolution, the spatial variations of land cover can be monitored in greater detail using synthetic aperture radar (SAR). Inundation is studied using the SAR images obtained from Sentinel-1A in both VH and VV polarizations in the present experimental study. The temporal variation of the SAR scattering coefficient values for the area gives a good indication of flood and its boundary. The study area is the district of Morigaon in the state of Assam in India. The period of flood monitoring study is the monsoon season of the year 2017, during which high flood occurred in the state of Assam. The variation of microwave scattering value shows a distinctive indication of flood from the non-flooded period. Frequent monitoring of flood in a large area (10 km x 10 km) using passive microwave sensing and pin-pointing the actual flooded portions (5 m x 5 m) within the flooded area using active microwave sensing, can be a highly useful combination, as revealed by the present experimental results.

Keywords: active remote sensing, flood monitoring, microwave remote sensing, synthetic aperture radar

Procedia PDF Downloads 151

Authors: Flavio Cannavo

Abstract:

Continuous evaluation of the status of potentially hazardous volcanos plays a key role for civil protection purposes. The importance of monitoring volcanic activity, especially for energetic paroxysms that usually come with tephra emissions, is crucial not only for exposures to the local population but also for airline traffic. Presently, real-time surveillance of most volcanoes worldwide is essentially delegated to one or more human experts in volcanology, who interpret data coming from different kind of monitoring networks. Unfavorably, the high nonlinearity of the complex and coupled volcanic dynamics leads to a large variety of different volcanic behaviors. Moreover, continuously measured parameters (e.g. seismic, deformation, infrasonic and geochemical signals) are often not able to fully explain the ongoing phenomenon, thus making the fast volcano state assessment a very puzzling task for the personnel on duty at the control rooms. With the aim of aiding the personnel on duty in volcano surveillance, here we introduce a system based on an ensemble of data-driven classifiers to infer automatically the ongoing volcano status from all the available different kind of measurements. The system consists of a heterogeneous set of independent classifiers, each one built with its own data and algorithm. Each classifier gives an output about the volcanic status. The ensemble technique allows weighting the single classifier output to combine all the classifications into a single status that maximizes the performance. We tested the model on the Mt. Etna (Italy) case study by considering a long record of multivariate data from 2011 to 2015 and cross-validated it. Results indicate that the proposed model is effective and of great power for decision-making purposes.

Keywords: Bayesian networks, expert system, mount Etna, volcano monitoring

Procedia PDF Downloads 246

Authors: Andrés Calvillo Téllez, Marianne Martínez Zanzarric, José Cruz Núñez Pérez

Abstract:

A modular system that performs basic monitoring of both water and air quality is presented. Monitoring is essential for environmental, aquaculture, and agricultural disciplines, where this type of instrumentation is necessary for data collection. The system uses low-cost components, which allows readings close to those with high-cost probes. The probe collects readings such as the coordinates of the geographical position, as well as the time it records the target parameters of the monitored. The modules or subsystems that make up the probe are the global positioning (GPS), which shows the altitude, latitude, and longitude data of the point where the reading will be recorded, a real-time clock stage, the date marking the time, the module SD memory continuously stores data, data acquisition system, central processing unit, and energy. The system acquires parameters to measure water quality, conductivity, pressure, and temperature, and for air, three types of ammonia, dioxide, and carbon monoxide gases were censored. The information obtained allowed us to identify the schedule of modification of the parameters and the identification of the ideal conditions for the growth of microorganisms in the water.

Keywords: calibration, conductivity, datalogger, monitoring, real time clock, water quality

Procedia PDF Downloads 103

Authors: Ishiyaku Abdulkadir, Satish Kumar J

Abstract:

Land Productivity is a measure of the greenness of above-ground biomass in health and potential gain and is not related to agricultural productivity. Monitoring land productivity dynamics is essential to identify, especially when and where the trend is characterized degraded for mitigation measures. This research aims to monitor the land productivity trend of Gombe State between 2001 and 2015. QGIS was used to compute NDVI from AVHRR/MODIS datasets in a cloud-based method. The result appears that land area with improving productivity account for 773sq.km with 4.31%, stable productivity traced to 4,195.6 sq.km with 23.40%, stable but stressed productivity represent 18.7sq.km account for 0.10%, early sign of decline productivity occupied 5203.1sq.km with 29%, declining productivity account for 7019.7sq.km, represent 39.2%, water bodies occupied 718.7sq.km traced to 4% of the state’s area.

Keywords: above-ground biomass, dynamics, land productivity, man-environment relationship

Procedia PDF Downloads 145

Authors: Zheng-Yan Ruan, Chien-Hao Wang, Hong-Jen Lin, Chien-Peng Huang, Ying-Hao Chen, En-Cheng Yang, Chwan-Lu Tseng, Joe-Air Jiang

Abstract:

Bees play a vital role in pollination. This paper focuses on the weighing process of honey. Honey is usually stored at the comb in a hive. Bee farmers brush bees away from the comb and then collect honey, and the collected honey is weighed afterward. However, such a process brings strong negative influences on bees and even leads to the death of bees. This paper therefore presents an Internet of Things-based weight monitoring system which uses weight sensors to measure the weight of honey and simplifies the whole weighing procedure. To verify the system, the weight measured by the system is compared to the weight of standard weights used for calibration by employing a linear regression model. The R² of the regression model is 0.9788, which suggests that the weighing system is highly reliable and is able to be applied to obtain actual weight of honey. In the future, the weight data of honey can be used to find the relationship between honey production and different ecological parameters, such as bees’ foraging behavior and weather conditions. It is expected that the findings can serve as critical information for honey production improvement.

Keywords: internet of things, weight, honey, bee

Procedia PDF Downloads 459

Authors: Sangeeta Palekar, Neeraj Rangwani, Akash Poddar, Jayu Kalambe

Abstract:

The bio-medical analysis is an indispensable procedure for identifying health-related diseases like diabetes. Monitoring the glucose level in our body regularly helps us identify hyperglycemia and hypoglycemia, which can cause severe medical problems like nerve damage or kidney diseases. This paper presents a method for predicting the glucose concentration in blood samples using image processing and machine learning algorithms. The glucose solution is prepared by the glucose oxidase (GOD) and peroxidase (POD) method. An experimental database is generated based on the colorimetric technique. The image of the glucose solution is captured by the raspberry pi camera and analyzed using image processing by extracting the RGB, HSV, LUX color space values. Regression algorithms like multiple linear regression, decision tree, RandomForest, and XGBoost were used to predict the unknown glucose concentration. The multiple linear regression algorithm predicts the results with 97% accuracy. The image processing and machine learning-based approach reduce the hardware complexities of existing platforms.

Keywords: artificial intelligence glucose detection, glucose oxidase, peroxidase, image processing, machine learning

Procedia PDF Downloads 203

Authors: Kolade Olawande Owoeye, George Weir

Abstract:

Terrorism and extremism activities on the internet are becoming the most significant threats to national security because of their potential dangers. In response to this challenge, law enforcement and security authorities are actively implementing comprehensive measures by countering the use of the internet for terrorism. To achieve the measures, there is need for intelligence gathering via the internet. This includes real-time monitoring of potential websites that are used for recruitment and information dissemination among other operations by extremist groups. However, with billions of active webpages, real-time monitoring of all webpages become almost impossible. To narrow down the search domain, there is a need for efficient webpage classification techniques. This research proposed a new approach tagged: SentiPosit-based method. SentiPosit-based method combines features of the Posit-based method and the Sentistrenght-based method for classification of terrorism and extremism webpages. The experiment was carried out on 7500 webpages obtained through TENE-webcrawler by International Cyber Crime Research Centre (ICCRC). The webpages were manually grouped into three classes which include the ‘pro-extremist’, ‘anti-extremist’ and ‘neutral’ with 2500 webpages in each category. A supervised learning algorithm is then applied on the classified dataset in order to build the model. Results obtained was compared with existing classification method using the prediction accuracy and runtime. It was observed that our proposed hybrid approach produced a better classification accuracy compared to existing approaches within a reasonable runtime.

Keywords: sentiposit, classification, extremism, terrorism

Procedia PDF Downloads 278

Authors: Marilena Ianculescu, Adriana Alexandru

Abstract:

Internet of Health Things (IoHT) has already proved to be a persuasive means to support a proper assessment of the living conditions by collecting a huge variety of data. For a customized health management of a senior patient, IoHT provides the capacity to build a dynamic solution for sustaining the shift inside the patient-physician relationship by allowing a real-time and continuous remote monitoring of the health status, well-being, safety and activities of the senior, especially in a non-clinical environment. Thus, is created a win-win solution in which both the patient and the physician enhance their involvement and shared decision-making, with significant outcomes. Health monitoring systems in smart environments are becoming a viable alternative to traditional healthcare solutions. The ongoing “Non-invasive monitoring and health assessment of the elderly in a smart environment (RO-SmartAgeing)” project aims to demonstrate that the existence of complete and accurate information is critical for assessing the health condition of the seniors, improving wellbeing and quality of life in relation to health. The researches performed inside the project aim to highlight how the management of IoHT devices connected to the RO-SmartAgeing platform in a secure way by using a role-based access control system, can allow the physicians to provide health services at a high level of efficiency and accessibility, which were previously only available in hospitals. The project aims to identify deficient aspects in the provision of health services tailored to a senior patient’s specificity and to offer a more comprehensive perspective of proactive and preventive medical acts.

Keywords: health management, internet of health things, remote monitoring, senior patient

Procedia PDF Downloads 100

Authors: Kechnit Djamel, Ammarri Abdelhadi, Raphael Tshimang, Mark Trrig

Abstract:

One of the most important aspects of monitoring rivers is navigation. The variation of discharge in the river generally produces a change in available draft for a vessel, particularly in the low flow season, which can impact the navigable water path, especially when the water depth is less than the normal one, which allows safe navigation for boats. The water depth is related to the bathymetry of the channel as well as the discharge. For a seasonal update of the navigation maps, a daily discharge value is required. Many novel approaches based on earth observation and remote sensing have been investigated for large rivers. However, it should be noted that most of these approaches are not currently able to directly estimate river discharge. This paper discusses the application of remote sensing tools using the analysis of the reflectance value of MODIS imagery and is combined with field measurements for the estimation of discharge. This approach is applied in the lower reach of the Congo River (Pool Malebo) for the period between 2019 and 2021. The correlation obtained between the observed discharge observed in the gauging station and the reflectance ratio time series is 0.81. In this context, a Discharge Reflectance Model (DRM) was developed to express discharge as a function of reflectance. This model introduces a non-contact method that allows discharge monitoring using earth observation. DRM was validated by field measurements using ADCP, in different sections on the Pool Malebo, over two different periods (dry and wet seasons), as well as by the observed discharge in the gauging station. The observed error between the estimated and measured discharge values ranges from 1 to 8% for the ADCP and from (1% to 11%) for the gauging station. The study of the uncertainties will give us the possibility to judge the robustness of the DRM.

Keywords: discharge monitoring, navigation, MODIS, empiric, ADCP, Congo River

Procedia PDF Downloads 91

Authors: Fang-Bo Yu, Li-Bo Guan, Sheng-Dao Shan

Abstract:

Biogas slurry was mixed with six commercial fungicides and screening against 11 phytopathogens was carried out. Results showed that inhibition of biogas slurry was different for the test strains and no significant difference between treatments of Didymella bryoniae, Fusarium oxysporum f. sp. vasinfectum, Aspergillus niger, Rhizoctonia cerealis, F. graminearum and Septoria tritici was observed. However, significant differences were found among Penicillium sp., Botrytis cinerea, Alternaria sonali, F. oxysporum F. sp. melonis and Sclerotinia sclerotiorum. The approach described here presents a promising alternative to current manipulation although some issues still need further examination. This study could contribute to the development of sustainable agriculture and better utilization of biogas slurry.

Keywords: anaerobic digestion, biogas slurry, phytopathogen, sustainable agriculture

Procedia PDF Downloads 333

Authors: Mirza Waseem Abbas, Syed Danish Raza

Abstract:

For many countries agriculture is still the major force driving the economy and a critically important socioeconomic sector, despite exceptional industrial development across the globe. In countries like Pakistan, this sector is considered the backbone of the economy, and most of the economic decision making revolves around agricultural outputs and data. Timely and accurate facts and figures about this vital sector hold immense significance and have serious implications for the long-term development of the economy. Therefore, any significant improvements in the statistics and other forms of data regarding agriculture sector are considered important by all policymakers. This is especially true for decision making for the betterment of crops and the agriculture sector in general. Provincial and federal agricultural departments collect data for all cash and non-cash crops and the sector, in general, every year. Traditional data collection for such a large sector i.e. agriculture, being time-consuming, prone to human error and labor-intensive, is slowly but gradually being replaced by remote sensing techniques. For this study, remotely sensed data were used for change detection (machine learning, supervised & unsupervised classification) to assess the increase or decrease in area under agriculture over the last fifteen years due to urbanization. Detailed Landsat Images for the selected agricultural districts were acquired for the year 2000 and compared to images of the same area acquired for the year 2016. Observed differences validated through detailed analysis of the areas show that there was a considerable decrease in vegetation during the last fifteen years in four major agricultural districts of the Punjab province due to urbanization (housing societies).

Keywords: change detection, area estimation, machine learning, urbanization, remote sensing

Procedia PDF Downloads 249

Authors: Abubakar O. Sulaiman

Abstract:

Agriculture was the main stay of Nigeria’s economy before the oil boom of the 1970s caused a gradual but steady shift from agriculture to crude oil as the major source of revenue and foreign exchange. The economy later experienced many symptoms of the 'Dutch disease', with exchange rate appreciation and erosion of competitiveness of the non-oil tradable goods. In order to reverse the worsening economic situations -high unemployment, galloping inflation, deteriorating balance of payment, declining economic growth, and fiscal deficits among others- the government, embarked on austerity measures in 1982 and Structure Adjustment Programme (SAP) in 1986. One of the cornerstones of SAP is the diversification of the economy from oil to non-oil. In the form of stocktaking, this paper investigates the impact of non-oil revenue on economic growth in Nigeria using quarterly time-series data from 1980 to 2019. The findings revealed that a long-run relationship exists between the variables (non-oil variables) and economic growth in Nigeria. Among the variables, (agriculture revenue, manufacturing revenue, revenue from services, and company income tax) contributed substantially to economic growth. The paper recommends that the government should continue to intensify efforts and policies in the diversification of the economy as it will bring about sustainable non-oil revenue and economic growth.

Keywords: non-oil revenue, economic growth, export, long run relationship

Procedia PDF Downloads 158

Authors: Nunila Ferreira de Oliveira, Silvana Martins Mishima

Abstract:

Diabetes mellitus type 2 (DM2) prevalence, is increasing on the world, in Brazil is considered a public health problem. Treatment focuses on glycemic control depending primarily of lifestyle changes - not drug treatment (NDT), may involve drug therapy (DT) and requires continuous health monitoring. In Brazil this monitoring is performed by the Unified Health System (SUS) through Primary Health Care (PHC), which stimulate people with DM2 empowerment for care management. SUS was approved in 1988 and the PHC operationalization was strengthened with the creation of the Family Health Strategy (FHS) in 1994. Our aim was to analyze the people with DM2 participation in front of the care management health monitoring in the FHS. Qualitative research was carried out through non-participant observation of attendance of 25 people with DM2 in the FHS and interviewed at home. Ethical guidelines were followed. It was found that people with DM2 only follow professionals’ recommendations that make sense according to their own conceptions of health/disease; most of them emphasize the importance of (DT) with little emphasis on the NDT, was found great difficulty in the NDT and lack of knowledge about the disease and care. As regards monitoring the FHS, were observed therapeutic practices based on the bio medical model, although the APS search for another care perspective; NDT is not systematically accompanied by the health team and takes place a few educational activities on the DM2 in the FHS, with low user adoption. The work of the FHS is done by multidisciplinary teams, but we see the need for greater participation of nurses in clinical-care follow-up of this population and may also act in adapting to the NDT. Finally we emphasize the need for professional practices that consider the difficulties to care management by people with DM2, especially because of the NDT. It is noticed that the measures recommended by the FHS professionals are not always developed by people with DM2. We must seek the empowerment of people with DM2 to manage the form of care associated with the FHS team, seeking to reduce the incidence of complications and higher quality of life.

Keywords: diabetes mellitus, primary health care, nursing, management of care

Procedia PDF Downloads 456

Authors: Ana Luiza Da Gama E Souza

Abstract:

This article aims to discuss the problem of food insecurity in Brazil in what it refers to contamination of food by chemical substances such as herbicides, pesticides, and other contaminants. The issue will be faced by analyzing, on the one hand, the standards that guide the food system in the world and, on the other hand, human rights indicators whose purpose is to provide an effective monitoring of the State's obligations to guarantee food security, analyzing the implications of the former for the success of the latter. The methodology adopted in this article was bibliographic-documentary and consists of three moments of analysis. The first moment consists in the analysis of the reports of the Commission on Human Rights of the Organization of American States to identify the set of progress indicators developed by the Commission. This analysis will involve the new methodology used to evaluate the efficiency in monitoring food security in Brazil the case of using pesticides in the production of food at levels of toxicity not admitted by the inspection bodies. The second moment consists in evaluating the mechanism for monitoring food security in Brazil, which was initially established by the National Food Security Plan (PLANSAN) for 2012-2015 and improved by the II National Food Security Plan for 2016-2019. Those mechanisms were prepared by the Chamber (CAISAN), and have the function to compare the monitoring proposals with the results presented by CAISAN on the Indicators and Results Report of the National Plan for Food and Nutrition Security 2012-2015. The third moment was intended to understand, analyze and evaluate the standardization process of the agri-food system, especially regarding the level of toxicity standards, that is related to food safety monitoring as a guarantee of pesticide-free food. The results show the dependence between private standards of toxicity and the indicators of food safety that leads to inefficiency on monitoring that mechanism in Brazil.

Keywords: standards, indicators, human rights, food security

Procedia PDF Downloads 333

Authors: Melikhaya Skhephe, Robert Mawuli Kwasi Boadzo, Zanoxolo Berington Gobingca

Abstract:

This research study sought to examine parental monitoring of learners’ cell phone use in the Eastern Cape, South Africa. To this end, the researchers employed a quantitative approach. Data were obtained through questionnaires, with a sample of 15 parents having been purposively selected. The findings revealed that parents are unaware that they have to monitor the learner’s cell phone. Another finding was that parents in the 21-century did not support the use of mobile phones in education. The researchers recommend that parent’s discussion forums be created to educate parents on how a cell phone can be used in education. Cellphone companies need to be encouraged to educate parents on how they monitor cell phones used by learners. Another recommendation was that network providers need to restrict access to searching on the internet according to age.

Keywords: parental monitoring, app blocking services, learner’s cell phone use, cell phone

Procedia PDF Downloads 160

Authors: J. W. Ahn, I. Y. Choi, T. V. Dinh, J. C. Kim

Abstract:

A cooler has been widely employed in the extractive system of the continuous emission monitoring system (CEMS) to remove water vapor in the gas stream. The effect of the cooler on analytical target gases was investigated in this research. A commercial cooler for the CEMS operated at 4 C was used. Several gases emitted from a coal power plant (i.e. CO2, SO2, NO, NO2 and CO) were mixed with humid air, and then introduced into the cooler to observe its effect. Concentrations of SO2, NO, NO2 and CO were made as 200 ppm. The CO2 concentration was 8%. The inlet absolute humidity was produced as 12.5% at 100 C using a bubbling method. It was found that the reduction rate of SO2 was the highest (~21%), followed by NO2 (~17%), CO2 (~11%) and CO (~10%). In contrast, the cooler was not affected by NO gas. The result indicated that the cooler caused a significant effect on the water soluble gases due to condensate water in the cooler. To overcome this problem, a correction factor may be applied. However, water vapor might be different, and emissions of target gases are also various. Therefore, the correction factor is not only a solution, but also a better available method should be employed.

Keywords: cooler, CEMS, monitoring, reproductive, sampling

Procedia PDF Downloads 361

Authors: Rajeshwari Madli, Santhosh Hebbar, Vishwanath Heddoori, G. V. Prasad

Abstract:

Agriculture is the major occupation in India and forms the backbone of Indian economy in which irrigation plays a crucial role for increasing the quality and quantity of crop yield. In spite of many revolutionary advancements in agriculture, there has not been a dramatic increase in agricultural performance. Lack of irrigation infrastructure and agricultural knowledge are the critical factors influencing agricultural performance. However, by using advanced agricultural equipment, the effect of these factors can be curtailed.  The presented system aims at increasing the yield of crops by using an intelligent irrigation controller that makes use of wireless sensors. Sensors are used to monitor primary parameters such as soil moisture, soil pH, temperature and humidity. Irrigation decisions are taken based on the sensed data and the type of crop being grown. The system provides a mobile application in which farmers can remotely monitor and control the irrigation system. Also, the water pump is protected against damages due to voltage variations and dry running.

Keywords: android application, Bluetooth, wireless sensors, irrigation, temperature, soil pH

Procedia PDF Downloads 382

Authors: Rong-Terng Juang

Abstract:

Autonomous vehicles offer the possibility of significant benefits to social welfare. However, fully automated cars might not be going to happen in the near further. To speed the adoption of the self-driving technologies, many governments worldwide are passing laws requiring data recorders for the testing of autonomous vehicles. Currently, the self-driving vehicle, (e.g., shuttle bus) has to be monitored from a remote control center. When an autonomous vehicle encounters an unexpected driving environment, such as road construction or an obstruction, it should request assistance from a remote operator. Nevertheless, large amounts of data, including images, radar and lidar data, etc., have to be transmitted from the vehicle to the remote center. Therefore, this paper proposes a data compression method of in-vehicle networks for remote monitoring of autonomous vehicles. Firstly, the time-series data are rearranged into a multi-dimensional signal space. Upon the arrival, for controller area networks (CAN), the new data are mapped onto a time-data two-dimensional space associated with the specific CAN identity. Secondly, the data are sampled based on differential sampling. Finally, the whole set of data are encoded using existing algorithms such as Huffman, arithmetic and codebook encoding methods. To evaluate system performance, the proposed method was deployed on an in-house built autonomous vehicle. The testing results show that the amount of data can be reduced as much as 1/7 compared to the raw data.

Keywords: autonomous vehicle, data compression, remote monitoring, controller area networks (CAN), Lidar

Procedia PDF Downloads 163