Search results for: smart agriculture

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

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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

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Authors: Vasiliki Kolake, Christos Kavalaris, Sofia Megoudi, Maria Maxouri, Panagiotis A. Karas, Aris Kyparissis, Efi Levizou

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Conservation agriculture (CA), is a production system approach that can tackle the challenges of climate change mainly through facilitating carbon storage into the soil and increasing crop resilience. This is extremely important for the vulnerable Mediterranean agroecosystems, which already face adverse environmental conditions. The agronomic practices used in CA, i.e. permanent soil cover and no-tillage, result in reduced soil erosion and increased soil organic matter, preservation of water and improvement of quality and fertility of the soil in the long-term. Thus the functional characteristics and processes of the soil are considerably affected by the implementation of CA. The aim of the present work was to assess the effects of CA on soil nitrification potential and mycorrhizal colonization about the above-ground production in a wheat field. Two adjacent but independent field sites of 1.5ha each were used (Thessaly plain, Central Greece), comprising the no-till and conventional tillage treatments. The no-tillage site was covered by residues of the previous crop (cotton). Potential nitrification and the nitrate and ammonium content of the soil were measured at two different soil depths (3 and 15cm) at 20-days intervals throughout the growth period. Additionally, the leaf area index (LAI) was monitored at the same time-course. The mycorrhizal colonization was measured at the commencement and end of the experiment. At the final harvest, total yield and plant biomass were also recorded. The results indicate that wheat yield was considerably favored by CA practices, exhibiting a 42% increase compared to the conventional tillage treatment. The superior performance of the CA crop was also depicted in the above-ground plant biomass, where a 26% increase was recorded. LAI, which is considered a reliable growth index, did not show statistically significant differences between treatments throughout the growth period. On the contrary, significant differences were recorded in endomycorrhizal colonization one day before the final harvest, with CA plants exhibiting 20% colonization, while the conventional tillage plants hardly reached 1%. The on-going analyses of potential nitrification measurements, as well as nitrate and ammonium determination, will shed light on the effects of CA on key processes in the soil. These results will integrate the assessment of CA impact on certain below and above-ground processes during wheat cultivation under the Mediterranean climate.

Keywords: conservation agriculture, LAI, mycorrhizal colonization, potential nitrification, wheat, yield

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Authors: Innocent Pangapanga, Eric Mungatana

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Tropical cyclones–related floods (TCRFs) in Malawi have devastating effects on smallholder agriculture, thereby threatening the food security agenda, which is already constrained by poor agricultural innovations, low use of improved varieties, and unaffordable inorganic fertilizers, and fragmenting landholding sizes. Accordingly, households have engineered and indigenously implemented sustainable landscape management (SLM) innovations to contain the adverse effects of TCRFs on farm productivity. This study, therefore, interrogated the efficacy of SLM adoption on farm productivity under varying TCRFs, while controlling for the potential selection bias and unobservable heterogeneity through the application of the Endogenous Switching Regression Model. In this study, we further investigated factors driving SLM adoption. Substantively, we found TCRFs reducing farm productivity by 31 percent, on the one hand, and influencing the adoption of SLM innovations by 27 percent, on the other hand. The study also observed that households that interacted SLM with TCRFs were more likely to enhance farm productivity by 24 percent than their counterparts. Interestingly, the study results further demonstrated that multiple adoptions of SLM-related innovations, including intercropping, agroforestry, and organic manure, enhanced farm productivity by 126 percent, suggesting promoting SLM adoption as a package to appropriately inform existing sustainable development goals’ agricultural productivity initiatives under intensifying TCRFs in the country.

Keywords: tropical cyclones–related floods, sustainable landscape management innovations, farm productivity, endogeneity, endogenous switching regression model, panel data, smallholder agriculture

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Authors: Saba Gachpaz, Hamid Reza Heidari

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The sharp increase in population growth leads to more pressure on agricultural areas to satisfy the food supply. To achieve this, more resources should be consumed and, besides other environmental concerns, highlight sustainable agricultural development. Land-use management is a crucial factor in obtaining optimum productivity. Machine learning is a widely used technique in the agricultural sector, from yield prediction to customer behavior. This method focuses on learning and provides patterns and correlations from our data set. In this study, nine physical control factors, namely, soil classification, electrical conductivity, normalized difference water index (NDWI), groundwater level, elevation, annual precipitation, pH of water, annual mean temperature, and slope in the alluvial plain in Khuzestan (an agricultural hotspot in Iran) are used to decide the best agricultural land use for both rainfed and irrigated agriculture for ten different crops. For this purpose, each variable was imported into Arc GIS, and a raster layer was obtained. In the next level, by using training samples, all layers were imported into the python environment. A random forest model was applied, and the weight of each variable was specified. In the final step, results were visualized using a digital elevation model, and the importance of all factors for each one of the crops was obtained. Our results show that despite 62% of the study area being allocated to agricultural purposes, only 42.9% of these areas can be defined as a suitable class for cultivation purposes.

Keywords: land suitability, machine learning, random forest, sustainable agriculture

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Authors: Toshifumi Hiramatsu, Satoshi Morita, Manuel Pencelli, Marta Niccolini, Matteo Ragaglia, Alfredo Argiolas

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Automation technologies for agriculture field are needed to promote labor-saving. One of the most relevant problems in automated agriculture is represented by controlling the robot along a predetermined path in presence of rough terrain or incline ground. Unfortunately, disturbances originating from interaction with the ground, such as slipping, make it quite difficult to achieve the required accuracy. In general, it is required to move within 5-10 cm accuracy with respect to the predetermined path. Moreover, lateral velocity caused by gravity on the incline field also affects slipping. In this paper, a path-tracking controller for tracked mobile robots moving on rough terrains of incline field such as vineyard is presented. The controller is composed of a disturbance observer and an adaptive controller based on the kinematic model of the robot. The disturbance observer measures the difference between the measured and the reference yaw rate and linear velocity in order to estimate slip. Then, the adaptive controller adapts “virtual” parameter of the kinematics model: Instantaneous Centers of Rotation (ICRs). Finally, target angular velocity reference is computed according to the adapted parameter. This solution allows estimating the effects of slip without making the model too complex. Finally, the effectiveness of the proposed solution is tested in a simulation environment.

Keywords: the agricultural robot, autonomous control, path-tracking control, tracked mobile robot

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Authors: Sun-Young Jang, Sung-Ah Kim, Dongyoun Shin

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The Intelligent transportation system is essential to build smarter cities. Machine learning based transportation prediction could be highly promising approach by delivering invisible aspect visible. In this context, this research aims to make a prototype model that predicts transportation network by using big data and machine learning technology. In detail, among urban transportation systems this research chooses bus system.  The research problem that existing headway model cannot response dynamic transportation conditions. Thus, bus delay problem is often occurred. To overcome this problem, a prediction model is presented to fine patterns of bus delay by using a machine learning implementing the following data sets; traffics, weathers, and bus statues. This research presents a flexible headway model to predict bus delay and analyze the result. The prototyping model is composed by real-time data of buses. The data are gathered through public data portals and real time Application Program Interface (API) by the government. These data are fundamental resources to organize interval pattern models of bus operations as traffic environment factors (road speeds, station conditions, weathers, and bus information of operating in real-time). The prototyping model is designed by the machine learning tool (RapidMiner Studio) and conducted tests for bus delays prediction. This research presents experiments to increase prediction accuracy for bus headway by analyzing the urban big data. The big data analysis is important to predict the future and to find correlations by processing huge amount of data. Therefore, based on the analysis method, this research represents an effective use of the machine learning and urban big data to understand urban dynamics.

Keywords: big data, machine learning, smart city, social cost, transportation network

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Authors: Getaneh Berie Tarekegn

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A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. It also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Rafeza Begum, Mohammad Mokhlesur Rahman, Safikul Moula, Rafiqul Islam

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Potassium (K) is crucial for healthy soil and plant growth. However, K fertilization is either disregarded or poorly underutilized in Bangladesh agriculture, despite the great demand for crops. This could eventually result in a significant depletion of the soil's potassium reserves, irreversible alteration of the minerals that contain potassium, and detrimental effects on crop productivity. Soil K mining in Bangladesh is a worrying problem, and we need to evaluate it thoroughly and find remedies. A pot culture experiment was conducted in the greenhouse of Bangladesh Institute of Nuclear Agriculture (BINA) using eleven soil series of Bangladesh in order to see the depletion behaviour of potassium (K) by continuous cropping using rice (var. Iratom-24) as the test crop. The soil series were Ranishankhail, Kaonia. Sonatala, Silmondi, Gopalpur, Ishurdi, Sara, Kongsha, Nunni, Lauta and Amnura on which four successive rice plants (45 days duration) were raised with (100 ppm K) or without addition of potassium. Nitrogen, phosphorus, sulfur and zinc were applied as basal to all pots. Potassium application resulted in higher dry matter yield, increased K concentration and uptake in all the soils compared with no K treatment; which gradually decreased in the subsequent harvests. Furthermore, plant takes up K not only from exchangeable pool but also from non-exchangeable sites and a minimum replenishment of K from the soil reserve was observed. Continuous cropping has resulted in the depletion of available K of the soil. The result indicated that in order to sustain higher crop yield under intensive cultivation, the addition of potash fertilizer is necessary.

Keywords: potassium, exchangeable pool, depletion behavior., Soil series

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Authors: Anil Kumar Gupta, Dronadula Venkata Sai Praneeth, Brajesh Dubey, Arundhuti Devi, Suravi Kalita, Khanindra Sharma

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Increase in urbanization and industrialization have led to improve in the standard of living. However, at the same time, the challenges due to improper solid waste management are also increasing. Municipal Solid Waste management is considered as a vital step in the development of urban infrastructure. The present study focuses on developing a solid waste management plan for an urban area in a developing country. The current scenario of solid waste management practices at various urban bodies in India is summarized. Guwahati city in the northeastern part of the country and is also one of the targeted smart cities (under the governments Smart Cities program) was chosen as case study to develop and implement the solid waste management plan. The whole city was divided into various divisions and waste samples were collected according to American Society for Testing and Materials (ASTM) - D5231-92 - 2016 for each division in the city and a composite sample prepared to represent the waste from the entire city. The solid waste characterization in terms of physical and chemical which includes mainly proximate and ultimate analysis were carried out. Existing primary and secondary collection systems were studied and possibilities of enhancing the collection systems were discussed. The composition of solid waste for the overall city was found to be as: organic matters 38%, plastic 27%, paper + cardboard 15%, Textile 9%, inert 7% and others 4%. During the conference presentation, further characterization results in terms of Thermal gravimetric analysis (TGA), pH and water holding capacity will be discussed. The waste management options optimizing activities such as recycling, recovery, reuse and reduce will be presented and discussed.

Keywords: proximate, recycling, thermal gravimetric analysis (TGA), solid waste management

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Authors: Lilian Mbinya Muasa

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Climate change is inevitable and a global challenge with long term implications to the sustainable development of many countries today. The negative impacts of climate change are creating far reaching social, economic and environmental problems threatening lives and livelihoods of millions of people in the world. Developing countries especially sub-Saharan countries are more vulnerable to climate change due to their weak ecosystem, low adaptive capacity and high dependency on rain fed agriculture. Countries in Sub-Saharan Africa are more vulnerable to climate change impacts due to their weak adaptive capacity and over-reliance on rain fed agriculture. In Kenya, 78% of the rural communities are poor farmers who heavily rely on rain fed agriculture thus are directly affected by climate change impacts.Currently, many parts of Kenya are experiencing successive droughts which are contributing to persistently unstable and declining agricultural productivity especially in semi arid eastern Kenya. As a result, thousands of rural communities repeatedly experience food insecurity which plunge them to an ever over-reliance on relief food from the government and Non-Governmental Organization In addition, they have adopted poverty coping strategies to diversify their income, for instance, deforestation to burn charcoal, sand harvesting and overgrazing which instead contribute to environmental degradation.This research was conducted in Makueni County which is classified as one of the most food insecure counties in Kenya and experiencing acute environmental degradation. The study aimed at analyzing the adaptive capacity to climate change across farming households of Makueni County in Kenya by, 1) analyzing adaptive capacity to climate change and agricultural productivity across farming households, 2) identifying factors that contribute to differences in adaptive capacity across farming households, and 3) understanding the relationship between climate change, agricultural productivity and adaptive capacity. Analytical Hierarchy Process (AHP) was applied to determine adaptive capacity and Total Factor Productivity (TFP) to determine Agricultural productivity per household. Increase in frequency of prolonged droughts and scanty rainfall. Preliminary findings indicate a magnanimous decline in agricultural production in the last 10 years in Makueni County. In addition, there is an over reliance of households on indigenous knowledge which is no longer reliable because of the unpredictability nature of climate change impacts. These findings on adaptive capacity across farming households provide the first step of developing and implementing action-oriented climate change policies in Makueni County and Kenya.

Keywords: adaptive capacity, agricultural productivity, climate change, vulnerability

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Authors: Amira Abdelrasoul

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This study aimed to ascertain the controlled permeability of biomimetic cellulose triacetate (CTA) membranes by investigating the electrical oscillatory behavior across impregnated membranes (IM). The biomimetic CTA membranes were infused with a fatty acid to induce electrical oscillatory behavior and, hence, to ensure controlled permeability. In situ synchrotron radiation micro-computed tomography (SR-μCT) at the BioMedical Imaging and Therapy (BMIT) Beamline at the Canadian Light Source (CLS) was used to evaluate the main morphology of IMs compared to neat CTA membranes to ensure fatty acid impregnation inside the pores of the membrane matrices. A monochromatic beam at 20 keV was used for the visualization of the morphology of the membrane. The X-ray radiographs were recorded by means of a beam monitor AA-40 (500 μm LuAG scintillator, Hamamatsu, Japan) coupled with a high-resolution camera, providing a pixel size of 5.5 μm and a field of view (FOV) of 4.4 mm × 2.2 mm. Changes were evident in the phase transition temperatures of the impregnated CTA membrane at the melting temperature of the fatty acid. The pulsations of measured voltages were related to changes in the salt concentration of KCl in the vicinity of the electrode. Amplitudes and frequencies of voltage pulsations were dependent on the temperature and concentration of the KCl solution, which controlled the permeability of the biomimetic membranes. The presented smart biomimetic membrane successfully combined porous polymer support and impregnating liquid not only imitate the main barrier properties of the biological membranes but could be easily modified to achieve some new properties, such as facilitated and active transport, regulation by chemical, physical and pharmaceutical factors. These results open new frontiers for the facilitation and regulation of active transport and permeability through biomimetic smart membranes for a variety of biomedical and drug delivery applications.

Keywords: biomimetic, membrane, synchrotron, permeability, morphology

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Authors: Rogelio Omar Corona-Núñez, Alma Mendoza-Ponce

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The Tropical Dry Forest not only is one of the most important tropical ecosystems in terms of area, but also it is one of the most degraded ecosystems. However, little is known about the degradation impacts on carbon stocks, therefore in carbon emissions. There are different studies which explain its deforestation dynamics, but there is still a lack of understanding of how they correlate to carbon losses. Recently different authors have built current biomass maps for the tropics and Mexico. However, it is not clear how well they predict at the local scale, and how they can be used to estimate carbon emissions. This study quantifies the forest net carbon losses by comparing the potential carbon stocks and the different current biomass maps in the Southern Pacific coast in Oaxaca, Mexico. The results show important differences in the current biomass estimates with not a clear agreement. However, by the aggregation of the information, it is possible to infer the general patterns of biomass distribution and it can identify the driving forces of the carbon emissions. This study estimated that currently ~44% of the potential carbon stock estimated for the region is still present. A total of 6,764 GgC has been emitted due to deforestation and degradation of the forest at a rate of above ground biomass loss of 66.4 Mg ha-1. Which, ~62% of the total carbon emissions can be regarded as being due to forest degradation. Most of carbon losses were identified in places suitable for agriculture, close to rural areas and to roads while the lowest losses were accounted in places with high water stress and within the boundaries of the National Protected Area. Moreover, places not suitable for agriculture, but close to the coast showed carbon losses as a result of urban settlements.

Keywords: above ground biomass, deforestation, degradation, driving forces, tropical deciduous forest

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Authors: Esther M. Folarin, Evans Osabuohien, Ademola Onabote

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Agriculture constitutes an important part of development and poverty mitigation in lower-middle-income countries, like Nigeria. The level of agricultural productivity in the Nigerian economy in line with the level of demand necessary to meet the desired expectation of the Nigerian populace is threatening to meeting the standard of the United Nations (UN) Sustainable Development Goals (SDGs); This includes the SDG-2 (achieve food security through agricultural productivity). The overall objective of the study is to reveal the performance of the interaction variable in the model among other factors that help in the achievement of greater Nigerian agricultural productivity. The study makes use of Wave 4 (2018/2019) of the Living Standard Measurement Studies, Integrated Survey on Agriculture (LSMS-ISA). Qualitative analysis of the information was also used to provide complimentary answers to the quantitative analysis done in the study. The study employed human capital theory and Grossman’s theory of health Demand in explaining the relationships that exist between the variables within the model of the study. The study engages the Instrumental Variable Regression technique in achieving the broad objectives among other techniques for the other specific objectives. The estimation results show that there exists a positive relationship between female healthcare and the level of female agricultural productivity in Nigeria. In conclusion, the study emphasises the need for more provision and empowerment for greater female access to healthcare and educational attainment levels that aids higher female agricultural productivity and consequently an improvement in the total agricultural productivity of the Nigerian economy.

Keywords: agricultural productivity, education, female, healthcare, investment

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Authors: L. Masilionyte, S. Maiksteniene

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Alternative farming systems are used to cultivate high quality food products and retain the viability and fertility of soil. The field experiments of different farming systems were conducted at Joniškėlis Experimental Station of the Lithuanian Research Centre for Agriculture and Forestry in 2006–2013. The soil of the experimental site was Endocalcari-Endohypogleyic Cambisol (CMg-n-w-can). In different farming systems, farmyard manure, straw and green manure catch crops used for fertilization both in the soil low in humus and in the soil moderate in humus. In the 0–20 cm depth layer, it had a more significant effect on soil moisture than on other physical soil properties. In the agricultural systems, in which catch crops had been grown, soil physical characteristics did not differ significantly before their biomass incorporation, except for the moisture content, which was lower in rainy periods and higher in drier periods than in the soil without catch crops. Soil bulk density and porosity in the topsoil layer were more dependent on soil humus content than on agricultural measures used: in the soil moderate in humus content, compared with the soil low in humus, bulk density was by 1.4 % lower, and porosity by 1.8 % higher. The research findings create a possibility to make improvements in alternative cropping systems by choosing organic fertilizers and catch crops’ combinations that have the sustainable effect on soil and that maintain the sustainability of soil productivity parameters. Rational fertilization systems, securing the stability of soil productivity parameters and crop rotation productivity will promote a development of organic agriculture.

Keywords: agro-measures, soil physical parameters, organic farming, sustainable farming

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Authors: Samira Kalantary, Sara Taghipour, Mansoure Ghias Abadi

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The Internet of Things (IOT) is a technological revolution that represents the future of computing and communications. IOT is the convergence of Internet with RFID, NFC, Sensor, and smart objects. Fog Computing is the natural platform for IOT. At present, the IOT as a new network communication technology has rapidly shifted from concept to application under fog computing virtual storage computing platform. In this paper, we describe everything about IOT and difference between cloud computing and fog computing.

Keywords: cloud computing, fog computing, Internet of Things (IoT), IOT application

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Authors: Sakshi Singh, Shampa Chakraverty

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One of the essential characteristics of Blockchain is the ability to validate the integrity of new transactions added to the Blockchain. Moreover, one of the essential consensus algorithms, Proof of Work, performs this job. In this work, we implemented the Proof of Work consensus method on the block formed by performing the transaction using Ganache. The primary goal of this implementation is to understand the process and record how Proof of Work works in reality on newly created blocks.

Keywords: proof of work, blockchain, ganache, smart contract

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Authors: Shah Rucksana Akhter Urme

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Agriculture is the main source of food for human consumption and feeding the world huge population, the pressure of food supply is increasing day by day. Undoubtedly, quality strain, improved plantation, farming technology, synthetic fertilizer, readily available irrigation, insecticides and harvesting technology are the main factors those to meet up the huge demand of food consumption all over the world. However, depended on this limited resources and excess amount of consuming lands, water, fertilizers leads to the end of the resources and severe climate effects has been left for our future generation. Agriculture is the most responsible to global warming, emitting more greenhouse gases than all other vehicles largely from nitrous oxide released by from fertilized fields, and carbon dioxide from the cutting of rain forests to grow crops . Farming is the thirstiest user of our precious water supplies and a major polluter, as runoff from fertilizers disrupts fragile lakes, rivers, and coastal ecosystems across the globe which accelerates the loss of biodiversity, crucial habitat and a major driver of wildlife extinction. It is needless to say that we have to more concern on how we can save the nutrients of the soil, storage of the water and avoid excessive depends on synthetic fertilizer and insecticides. In this case, eco- friendly cultivation could be a potential alternative solution to minimize effects of agriculture in our environment. The objective of this review paper is about organic cultivation following in particular biotechnological process focused on bio-fertilizer and bio-pesticides. Intense practice of chemical pesticides, insecticides has severe effect on both in human life and biodiversity. This cultivation process introduces farmer an alternative way which is nonhazardous, cost effective and ecofriendly. Organic fertilizer such as tea residue, ashes might be the best alternative to synthetic fertilizer those play important role in increasing soil nutrient and fertility. Ashes contain different essential and non-essential mineral contents that are required for plant growth. Organic pesticide such as neem spray is beneficial for crop as it is toxic for pest and insects. Recycled and composted crop wastes and animal manures, crop rotation, green manures and legumes etc. are suitable for soil fertility which is free from hazardous chemicals practice. Finally water hyacinth and algae are potential source of nutrients even alternative to soil for cultivation along with storage of water for continuous supply. Inorganic practice of agriculture, consuming fruits and vegetables becomes a threat for both human life and eco-system and synthetic fertilizer and pesticides are responsible for it. Farmers that practice eco-friendly farming have to implement steps to protect the environment, particularly by severely limiting the use of pesticides and avoiding the use of synthetic chemical fertilizers, which are necessary for organic systems to experience reduced environmental harm and health risk.

Keywords: organic farming, biopesticides, organic nutrients, water storage, global warming

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Authors: Yari Vecchio, Margherita Masi, Jorgelina Di Pasquale

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Adoption of Precision Agriculture (PA) is involved in a multidimensional and complex scenario. The process of adopting innovations is complex and social inherently, influenced by other producers, change agents, social norms and organizational pressure. Complexity depends on factors that interact and influence the decision to adopt. Farm and operator characteristics, as well as organizational, informational and agro-ecological context directly affect adoption. This influence has been studied to measure drivers and to clarify 'bottlenecks' of the adoption of agricultural innovation. Making decision process involves a multistage procedure, in which individual passes from first hearing about the technology to final adoption. Awareness is the initial stage and represents the moment in which an individual learns about the existence of the technology. 'Static' concept of adoption has been overcome. Awareness is a precondition to adoption. This condition leads to not encountering some erroneous evaluations, arose from having carried out analysis on a population that is only in part aware of technologies. In support of this, the present study puts forward an empirical analysis among Italian farmers, considering awareness as a prerequisite for adoption. The purpose of the present work is to analyze both factors that affect the probability to adopt and determinants that drive an aware individual to not adopt. Data were collected through a questionnaire submitted in November 2017. A preliminary descriptive analysis has shown that high levels of adoption have been found among younger farmers, better educated, with high intensity of information, with large farm size and high labor-intensive, and whose perception of the complexity of adoption process is lower. The use of a logit model permits to appreciate the weight played by the intensity of labor and complexity perceived by the potential adopter in PA adoption process. All these findings suggest important policy implications: measures dedicated to promoting innovation will need to be more specific for each phase of this adoption process. Specifically, they should increase awareness of PA tools and foster dissemination of information to reduce the degree of perceived complexity of the adoption process. These implications are particularly important in Europe where is pre-announced the reform of Common Agricultural Policy, oriented to innovation. In this context, these implications suggest to the measures supporting innovation to consider the relationship between various organizational and structural dimensions of European agriculture and innovation approaches.

Keywords: adoption, awareness, complexity, precision agriculture

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Authors: Han Song, Tingting Wei, Dong Chen

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The combination of capital and rural areas in China has shown its great significance in promoting urban-rural integration and new-style urbanization, enhancing regional capacity for sustainable rural development and optimizing human settlement environment. The purpose of this study is to find capital operation mechanism in rural area and rural planning guidance in China. Based on case studies in Chinese rural areas, two types of capital operation mechanism in rural areas are summed up: intervention in the field of agriculture promoting the upgrading and innovation of agricultural industry chain, intervention in rural life and leisure areas updating rural connotation and form. In the light of experiences in Japan and Taiwan, it is proposed that government's norms and guidance, rural investment intensity and rural self-organization are three important factors for capital to drive rural development. It is also found that the unique land tenure and rural governance tradition are two important factors effecting the combination of capital and rural regions in China, which requires full attention in rational policy-making and rural planning. It comes to a conclusion as four directions of the overall reform of the rural planning: targeting at enhancing the viability of rural and sustainable capacity, encouraging differences in investment incentives and planning policies, providing land usage in the rural areas with planning support and reforming the village system. Directional guidance is also made for different types of capital investments, suggesting that capital should be rooted in agriculture and rural land to benefit farmers and update human settlements.

Keywords: capital, rural areas, rural planning, rural governance

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Authors: Ahmad Ali Shahid, M Shakil Shaukat

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Agriculture is the backbone of economy of Pakistan and Cotton is the major agricultural export and supreme source of raw fiber for our textile industry. To combat against the developing resistance in the target insects and combating these challenges wholesomely, a novel combination of pyramided/stacked genes was conceptualized and later realized, through the means of biotechnology i.e., transformation of three genes namely, Cry1Ac, Cry2A, and EPSP synthase (glyphosate tolerant) genes in the locally cultivated cotton variety. The progenies of the transformed plants were successfully raised and screened under the tunnel conditions for two generations and the present study focused on the screening of plants which were confirmed for containing all of these three genes and their expressions. Initially, the screening was done through glyphosate spray assay and the plants which were healthy and showed no damage on leaves were selected after 07 days of spray. In the laboratory, the DNA of these plants were isolated and subjected to amplification of the three genes. Thus, seventeen out of twenty were confirmed positive for Cry1Ac gene and ten out of twenty were positive for Cry2A gene and all twenty were positive for presence of EPSP synthase gene. Then, the ten plant samples which were confirmed with presence of all three genes were subjected to expression analysis of these proteins through ELISA. The results showed that eight out of ten plants were actively expressing the three transgenes. Real-time PCR was also done to quantify the expression levels of the EPSP synthase gene. Finally, eight plants were confirmed for the presence and active expression of all three genes in T3 generation of the triple gene transformed cotton. These plants may be subjected to T4 generation to develop a new stable variety in due course of time.

Keywords: agriculture, cotton, transformation, cry genes, ELISA, PCR

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Authors: Moshmi Sangavarapu

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The US healthcare industry has undergone tremendous digital transformation in recent years, but critical care access to lower-income ethnicities is still in its nascency. This population has historically showcased substantial hesitation to seek any medical assistance. While the lack of sufficient financial resources plays a critical role, the existing cultural and knowledge barriers also contribute significantly to widening the access gap. It is imperative to break these barriers to ensure timely access to therapeutic procedures that can save important lives! Based on ongoing research, healthcare access barriers can be best addressed by tapping the untapped potential of caregiver communities first. They play a critical role in patients’ diagnoses, building healthcare knowledge and instilling confidence in required therapeutic procedures. Recent technological advancements have opened many avenues by developing smart ways of reaching the large caregiver community. A digitized go-to-market strategy featuring connected media coupled with smart IoT devices and geo-location targeting can be collectively leveraged to reach this key audience group. AI/ML algorithms can be thoroughly trained to identify relevant data signals from users' location and browsing behavior and determine useful marketing touchpoints. The web behavior can be further assimilated with natural language processing to identify contextually relevant interest topics and decipher potential caregivers on digital avenues to serve that brand message. In conclusion, grasping the true health access journey of any lower-income ethnic group is important to design beneficial touchpoints that can alleviate patients’ concerns and allow them to break their own access barriers and opt for timely and quality healthcare.

Keywords: healthcare access, market access, diversity barriers, patient journey

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Authors: Temple Probyne Abali

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Port Harcourt, Rivers State in the Niger Delta region of Nigeria is bedeviled by the phenomenon of climatechange, posing threat to food security and livelihood. This study examined a 4 decadel (1980-2020) trend of climate change as well as its socio-economic impact on food security in the region. Furthermore, to achieve sustainable food security and livelihood amidst the phenomenon, the study adopted the World Bank Assisted Third National Fadama Development Programme approach. The data source for climate change involved secondary data from Nigeria Meteorological Agency (NIMET). Consequently, the results for climate change over the 4decade period were displayed in tables, charts and maps for the expected changes. Data sources on socio-economic impact of food security and livelihood were acquired through questionnairedesign. A purposive random sampling technique was used in selecting 5 coastal communities inthe region known for viable economic potentials for agricultural development and the resultswere analyzed using Analysis of Variance (ANOVA). The Participatory Rural Appraisal (PRA) technique of the World Bank for needs assessment wasadopted in selecting 5 agricultural sub-project proposals/activities based on groups’ commoneconomic interest from a total of 1,000 farmers each drawn from the 5 communities of differentage groups including men, women, youths and the vulnerable. Based on the farmers’ sub-projectinterests, the various groups’ Strength, Weakness, Opportunities and Threats (SWOT), Problem Listing Matrix, Skill Gap Analysis as well as EIAson their sub-project proposals/activities were analyzed with substantialMonitoring and Evaluation (M & E), using the Specific, Measurable, Attribute, Reliable and Time bound (SMART)approach. Based on the findings from the PRA technique, the farmers recorded considerableincreaseinincomeofover200%withinthe5yearprojectplan(2008-2013).Thestudyrecommends capacity building and advisory services on this PRA innovation. By so doing, there would be a sustainable increase in agricultural production and assured food security in an environmental friendly manner, in line with the United Nation’s Sustainable Development Goals(SDGs).

Keywords: climate change, food security, fadama, world bank, agriculture, sdgs

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Authors: Laura Çami (Vorpsi), Xhon Skënderi

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In today's rapidly evolving technological landscape, the traditional principles of contract law are facing significant challenges. The emergence of new technologies, such as electronic signatures, smart contracts, and online dispute resolution mechanisms, is transforming the way contracts are formed, interpreted, and enforced. This paper examines the implications of these technological advancements on the constitutional principles of contract law. One of the fundamental principles of contract law is freedom of contract, which ensures that parties have the autonomy to negotiate and enter into contracts as they see fit. However, the use of technology in the contracting process has the potential to disrupt this principle. For example, online platforms and marketplaces often offer standard-form contracts, which may not reflect the specific needs or interests of individual parties. This raises questions about the equality of bargaining power between parties and the extent to which parties are truly free to negotiate the terms of their contracts. Another important principle of contract law is the requirement of consideration, which requires that each party receives something of value in exchange for their promise. The use of digital assets, such as cryptocurrencies, has created new challenges in determining what constitutes valuable consideration in a contract. Due to the ambiguity in this area, disagreements about the legality and enforceability of such contracts may arise. Furthermore, the use of technology in dispute resolution mechanisms, such as online arbitration and mediation, may raise concerns about due process and access to justice. The use of algorithms and artificial intelligence to determine the outcome of disputes may also raise questions about the impartiality and fairness of the process. Finally, it should be noted that there are many different and complex effects of technical improvements on the fundamental constitutional foundations of contract law. As technology continues to evolve, it will be important for policymakers and legal practitioners to consider the potential impacts on contract law and to ensure that the principles of fairness, equality, and access to justice are preserved in the contracting process.

Keywords: technological advancements, constitutional principles, contract law, smart contracts, online dispute resolution, freedom of contract

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Authors: Hao-Wei Fu, Chung-Feng Kao

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In the era of rapid technological advancement, information technology (IT) has become integral to modern life, exerting significant influence across diverse sectors and serving as a catalyst for development in various industries. Within agriculture, the integration of IT offers substantial benefits, notably enhancing operational efficiency. Real-time monitoring systems, for instance, have been widely embraced in agriculture, effectively improving crop management practices. This study specifically addresses the management of rice panicle fertilizer, presenting the development of a web application tailored to handle data associated with rice panicle fertilizer management. Leveraging the normalized difference red edge index, this application optimizes the quantity of rice panicle fertilizer used, providing recommendations to agricultural stakeholders and service providers in the agricultural information sector. The overarching objective is to minimize costs while maximizing yields. Furthermore, a robust database system has been established to store and manage relevant data for future reference in rice cultivation management. Additionally, the study utilizes the Representational State Transfer software architectural style to construct an application programming interface (API), facilitating data creation, retrieval, updating, and deletion for users via the HyperText Transfer Protocol methods. Future plans involve integrating this API with third-party services to incorporate it into larger frameworks, thus catering to the diverse requirements of various third-party services.

Keywords: application programming interface, HyperText Transfer Protocol, nitrogen fertilizer intelligent management, web-based application

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Authors: Vedansh Gupta, Allyson Lutz, Ameen Razavi, Fatemeh Shirazi

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The agriculture industry is especially vulnerable to forecasted water shortages. In the fresh and fresh-cut produce sector, conventional flume-based washing with recirculation exhibits high water demand. This leads to a large water footprint and possible cross-contamination of pathogens. These can be alleviated through advanced water reuse processes, such as membrane technologies including reverse osmosis (RO). Water reuse technologies effectively remove dissolved constituents but can easily foul without pre-treatment. Biological treatment is effective for the removal of organic compounds responsible for fouling, but not at the low temperatures encountered at most produce processing facilities. This study showed that the Microvi MicroNiche Engineering (MNE) technology effectively removes organic compounds (> 80%) at low temperatures (6-8 °C) from wash water. The MNE technology uses synthetic microorganism-material composites with negligible solids production, making it advantageously situated as an effective bio-pretreatment for RO. A preliminary technoeconomic analysis showed 60-80% savings in operation and maintenance costs (OPEX) when using the Microvi MNE technology for organics removal. This study and the accompanying economic analysis indicated that the proposed technology process will substantially reduce the cost barrier for adopting water reuse practices, thereby contributing to increased food safety and furthering sustainable water reuse processes across the agricultural industry.

Keywords: biological pre-treatment, innovative technology, vegetable processing, water reuse, agriculture, reverse osmosis, MNE biocatalysts

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Authors: Faith Eweluegim Enahoro-Ofagbe

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Worldwide, every nation is experiencing the effects of global warming. In developing countries, due to the heavy reliance on agriculture for socioeconomic growth and security, among other things, these countries are more affected by climate change, particularly with the availability of water. Floods, droughts, rising temperatures, saltwater intrusion, groundwater depletion, and other severe environmental alterations are all brought on by climatic change. Life depends on water, a vital resource; these ecological changes affect all water use, including agriculture and household water use. Therefore adequate and adaptive water usage strategies for sustainability are essential in developing countries. Therefore, this paper investigates Nigeria's challenges due to climate change and adaptive techniques that have evolved in response to such issues to ensure water management and sustainability for irrigation and provide quality water to residents. Questionnaires were distributed to respondents in the study area, central Nigeria, for quantitative evaluation of sustainable water resource management techniques. Physicochemical analysis was done, collecting soil and water samples from several locations under investigation. Findings show that farmers use different methods, ranging from intelligent technologies to traditional strategies for water resource management. Also, farmers need to learn better water resource management techniques for sustainability. Since more residents obtain their water from privately held sources, the government should enforce legislation to ensure that private borehole construction businesses treat water sources of poor quality before the general public uses them.

Keywords: developing countries, irrigation, strategies, sustainability, water resource management, water usage

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Authors: Flavio Gazzani

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Nitrogen is an important agricultural input that is critical for the production. However, the introduction of large amounts of nitrogen into the environment has a number of undesirable impacts such as: the loss of biodiversity, eutrophication of waters and soils, drinking water pollution, acidification, greenhouse gas emissions, human health risks. It is a challenge to sustain or increase food production and at the same time reduce losses of reactive nitrogen to the environment, but there are many potential benefits associated with improving nitrogen use efficiency. Reducing nutrient losses from agriculture is crucial to the successful implementation of agricultural policy. Traditional regulatory instruments applied to implement environmental policies to reduce environmental impacts from nitrogen fertilizers, despite some successes, failed to address many environmental challenges and imposed high costs on the society to achieve environmental quality objectives. As a result, economic instruments started to be recognized for their flexibility and cost-effectiveness. The objective of the research project is to analyze the potential for increased use of market-based instruments in nitrogen control policy. The report reviews existing knowledge, bringing different studies together to assess the global nitrogen situation and the most relevant environmental management policy that aims to reduce pollution in a sustainable way without affect negatively agriculture production and food price. This analysis provides some guidance on how different market based instruments might be orchestrated in an overall policy framework to the development and assessment of sustainable nitrogen management from the economics, environmental and food security point of view.

Keywords: nitrogen emissions, chemical fertilizers, eutrophication, non-point of source pollution, dairy farm

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Authors: Atakan Aral Ormancı, Tuğçe Arslantaş, Murat Özcü

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This study presents the design and implementation of an experimental chassis-level system for various control applications. Specifically, the height level of the chassis is controlled using proportional integrated derivative, fuzzy logic, and deep learning control methods. Real-time data obtained from height and pressure sensors installed in a 6x2 truck chassis, in combination with pulse-width modulation signal values, are utilized during the tests. A prototype pneumatic system of a 6x2 truck is added to the setup, which enables the Smart Pneumatic Actuators to function as if they were in a real-world setting. To obtain real-time signal data from height sensors, an Arduino Nano is utilized, while a Raspberry Pi processes the data using Matlab/Simulink and provides the correct output signals to control the Smart Pneumatic Actuator in the truck chassis. The objective of this research is to optimize the time it takes for the chassis to level down and up under various loads. To achieve this, proportional integrated derivative control, fuzzy logic control, and deep learning techniques are applied to the system. The results show that the deep learning method is superior in optimizing time for a non-linear system. Fuzzy logic control with a triangular membership function as the rule base achieves better outcomes than proportional integrated derivative control. Traditional proportional integrated derivative control improves the time it takes to level the chassis down and up compared to an uncontrolled system. The findings highlight the superiority of deep learning techniques in optimizing the time for a non-linear system, and the potential of fuzzy logic control. The proposed approach and the experimental results provide a valuable contribution to the field of control, automation, and systems engineering.

Keywords: automotive, chassis level control, control systems, pneumatic system control

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Authors: B. Karabuluter, O. Karaduman

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Traffic management and traffic planning are important issues, especially in big cities. Due to the increase of personal vehicles and the physical constraints of urban roads, the problem of transportation especially in crowded cities over time is revealed. This situation reduces the living standards, and it can put human life at risk because the vehicles such as ambulance, fire department are prevented from reaching their targets. Even if the city planners take these problems into account, emergency planning and traffic management are needed to avoid cases such as traffic congestion, intersections, traffic jams caused by traffic accidents or roadworks. In this study, in smart traffic management issues, proposed solutions using intelligent vehicles acting in cooperation with urban roads are examined. Traffic management is becoming more difficult due to factors such as fatigue, carelessness, sleeplessness, social behavior patterns, and lack of education. However, autonomous vehicles, which remove the problems caused by human weaknesses by providing driving control, are increasing the success of practicing the algorithms developed in city traffic management. Such intelligent vehicles have become an important solution in urban life by using 'swarm intelligence' algorithms and cooperative driving methods to provide traffic flow, prevent traffic accidents, and increase living standards. In this study, studies conducted in this area have been dealt with in terms of traffic jam, intersections, regulation of traffic flow, signaling, prevention of traffic accidents, cooperation and communication techniques of vehicles, fleet management, transportation of emergency vehicles. From these concepts, some taxonomies were made out of the way. This work helps to develop new solutions and algorithms for cities where intelligent vehicles that can perform cooperative driving can take place, and at the same time emphasize the trend in this area.

Keywords: intelligent traffic management, cooperative driving, smart driving, urban road, swarm intelligence, connected vehicles

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Authors: Tunde Puskas, Anita Andersson

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In Swedish early childhood education research, the issues related to religious identifications and practices have often been marginalized or relegated either to the realm of diversity and multiculturalism or to the realm of national traditions. This paper is part of a research project about whether religion is considered as part of Swedish cultural heritage in Swedish preschools. Our aim in this paper is to explore how a Swedish preschool balance between keeping the education non-confessional and at the same time introducing the traditions associated with advent and Christmas. Christmas was chosen because of the religious background of the holiday and because it is a tradition widely celebrated in Swedish preschools. In Swedish education system, the concept of freedom of religion is understood in the sense that education is declared to be non-confessional. Nevertheless, as the major state holidays in Sweden are tied to Lutheran Christian traditions, and according to the curriculum preschool educators, are given the task to pass on a cultural heritage, defined in terms of values, traditions, history, language, and knowledge, it is the preschool teams or individual preschool teachers who determine whether and to what extent religious considerations are/ought to be seen as part of the cultural heritage the preschool passes on. The data consists of ten video taped observations from two preschools. The video data was transcribed and the transcripts were thereafter analysed through content analysis. In the analysis, we draw on the concept of banal religiosity that has helped us to draw attention to the workings of religious considerations that are so familiar that they rarely are noticed as religious and on Ninian Smart’s theory on the dimensions of religion. The analysis shows that what the adults actually do with religion fulfils six of seven dimensions common to religious traditions as outlined by Smart. At the same time, Christmas is performed as a lived tradition within which the commercial and religious rituals intersect and result in a banal, national religiosity.

Keywords: secular advent, banal religiosity, dimensions of religion, rites

Procedia PDF Downloads 175