scholarly journals IoT-based Horticultural Generation Framework

2020 ◽  
Vol 9 (4) ◽  
pp. 1923-1925
Keyword(s):  
Climate Change ◽  
Ecological Data ◽  
Financial Factors ◽  
Data Framework ◽  
It Innovation ◽  
The Difference ◽  
Factual Data

There has been a lot of research and different endeavours to apply new IoT innovation to agrarian zones. In any case, IoT for the agribusiness ought to be considered diversely against similar territories. The proposed system exhibits the IoT-based horticultural generation framework for settling market interest of rural items while building up nature sensors and forecast framework for the development and creation for measure of harvests by social occasion its ecological data. Presently, the interest by utilization of horticultural items could be anticipated quantitatively, nonetheless, the variety of gather and generation by the difference in homestead's developed zone, climate change, illness and bug harm and so forth couldn't be anticipated, with the goal that the organic market of rural items has not been controlled appropriately. The IoT-based rural creation framework through relationship investigation between the yield measurable data and horticultural condition data has improved the capacity of ranchers, analysts, and government authorities to dissect current conditions and anticipate future collect. Furthermore, horticultural items quality can be improved in light of the fact that ranchers watch entire cycle from seeding to selling utilizing this IoT-based choice emotionally supportive network. Strategies for gather anticipating have gotten progressively detailed. Profoundly refined measurable systems in farming are currently being utilized to remove data from past information and to extend forecast estimations of financial factors. To an enormous degree, these advances in the study of reap anticipating have been gained conceivable by ground in IT innovation. Be that as it may, lone measurable strategies don't give immaculate future circumstance. Thusly, it is important to examine associating checking crop conditions with factual data about collect. It is normal that from IoT-based choice emotionally supportive network, this data on factual example of harvest can be gotten. The motivation behind this investigation is to improve the horticultural figure supporting data framework, so constant conjecture will be conceivable. To this end, it will be expected to oversee IoT gadgets and assemble data on them all the more properly

scholarly journals Fabrication of Advanced Agribot Robot

2020 ◽  
Vol 9 (1) ◽  
pp. 1576-1579
Keyword(s):  
Climate Change ◽  
Central Point ◽  
Current Paper ◽  
Wide Scope ◽  
Ecological Data ◽  
Social Affair ◽  
The Earth ◽  
The Difference ◽  
Crop Condition ◽  
High Work

Numerous nations in Asia including India are agrarian economies and the majority of their rustic populaces rely upon horticulture to acquire their business. The utilization of apparatuses and domesticated animals in the rural procedure has decreased the human exertion. Central point that influence agribusiness incorporate less holding territory, deficiency of seeds, manures and work and vulnerability of storm. The motorization of horticulture alludes to the utilization of devices or machines in the rural procedure that conceivably lessens the human exertion. In spite of the fact that it lessens the human exertion in the horticultural procedure, it requires total human collaboration. The mechanization and apply autonomy application in the part of agribusiness is at the blasting stage when contrasted with its wide scope of use in different divisions. Numerous inquires about have been done in this field to robotize the procedure. In the current paper an exertion is made for the plan and advancement of the robot that can perform seeding process with no human intercession. The robot created is equipped for causing a gap in the dirt to up to certain profundity, putting the seed precisely in a similar gap and shutting the mud. The procedure is constrained by a microcontroller. The robot created defeats the disadvantages in the customary technique for seeding which incorporates wastage of seeds, high work wage, lower use of land and so forth. By the utilization of computerization and mechanical technology in the field of farming it is conceivable to build the general proficiency of the agrarian procedure and can alleviate impacts of work lack. This paper likewise presents the IoT-based horticultural creation framework for balancing out organic market of rural items while building up the earth sensors and expectation framework for the development and creation measure of yields by social affair its ecological data. As of now, the interest by utilization of horticultural items could be anticipated quantitatively, be that as it may, the variety of reap and creation by the difference in homestead's developed zone, climate change, infection and bug harm and so on. Couldn't be anticipated, so the market interest of agrarian items has not been controlled appropriately. To beat it, this paper structured the IoT-based checking framework to dissect crop condition, and the technique to improve the effectiveness of dynamic by investigating harvest measurements.

Climate change, global change: What is the difference?

Eos ◽  
1988 ◽  
Vol 69 (25) ◽  
pp. 668
Author(s):  
S.I. Rasool
Keyword(s):  
Climate Change ◽  
Global Change ◽  
The Difference

scholarly journals Towards Sustainable Development: Building’s Retrofitting with PCMs to Enhance the Indoor Thermal Comfort in Tropical Climate, Malaysia

2021 ◽  
Vol 13 (7) ◽  
pp. 3614
Author(s):  
Zeyad Amin Al-Absi ◽  
Mohd Isa Mohd Hafizal ◽  
Mazran Ismail ◽  
Azhar Ghazali
Keyword(s):  
Climate Change ◽  
Sustainable Development ◽  
Thermal Comfort ◽  
Phase Change Materials ◽  
Thermal Environment ◽  
High Energy ◽  
Transition Temperatures ◽  
Indoor Thermal Environment ◽  
Adaptive Thermal Comfort ◽  
The Difference

Building sector is associated with high energy consumption and greenhouse gas emissions, which contribute to climate change. Sustainable development emphasizes any actions to reduce climate change and its effect. In Malaysia, half of the energy utilized in buildings goes towards building cooling. Thermal comfort studies and adaptive thermal comfort models reflect the high comfort temperatures for Malaysians in naturally conditioned buildings, which make it possible to tackle the difference between buildings’ indoor temperature and the required comfort temperature by using proper passive measures. This study investigates the effectiveness of building’s retrofitting with phase change materials (PCMs) as a passive cooling technology to improve the indoor thermal environment for more comfortable conditions. PCM sheets were numerically investigated below the internal finishing of the walls. The investigation involved an optimization study for the PCMs transition temperatures and quantities. The results showed significant improvement in the indoor thermal environment, especially when using lower transition temperatures and higher quantities of PCMs. Therefore, the monthly thermal discomfort time has decreased completely, while the thermal comfort time has increased to as high as 98%. The PCM was effective year-round and the optimum performance for the investigated conditions was achieved when using 18mm layer of PCM27-26.

scholarly journals Analysis of livestock breeders’ perceptions and their adaptation measures to climate change in Morocco‘s arid rangelands

2020 ◽  
Vol 6 (1) ◽  
pp. 1-25
Author(s):  
Wadii Snaibi
Keyword(s):  
Climate Change ◽  
Local Level ◽  
Small Scale ◽  
Climate Data ◽  
Chi Square ◽  
Adaptation Measures ◽  
Significant Difference ◽  
The Difference ◽  
Eastern Morocco ◽  
Climate Analysis

AbstractThe high plateaus of eastern Morocco are already suffering from the adverse impacts of climate change (CC), as the local populations’ livelihoods depend mainly on extensive sheep farming and therefore on natural resources. This research identifies breeders’ perceptions about CC, examines whether they correspond to the recorded climate data and analyses endogenous adaptation practices taking into account the agroecological characteristics of the studied sites and the difference between breeders’ categories based on the size of owned sheep herd. Data on perceptions and adaptation were analyzed using the Chi-square independence and Kruskal-Wallis tests. Climate data were investigated through Mann-Kendall, Pettitt and Buishand tests.Herders’ perceptions are in line with the climate analysis in term of nature and direction of observed climate variations (downward trend in rainfall and upward in temperature). In addition, there is a significant difference in the adoption frequency of adaptive strategies between the studied agroecological sub-zones (χ2 = 14.525, p <.05) due to their contrasting biophysical and socioeconomic conditions, as well as among breeders’ categories (χ2 = 10.568, p < .05) which attributed mainly to the size of sheep flock. Policy options aimed to enhance local-level adaptation should formulate site-specific adaptation programs and prioritise the small-scale herders.

Regional biogeographical model of vegetation zones in doctoral programme Regional Biography in Olomouc (Case study for Norway spruce)

2020 ◽  
Author(s):  
Ivo Machar ◽  
Marián Halás ◽  
Zdeněk Opršal
Keyword(s):  
Climate Change ◽  
Regional Climate ◽  
Climate Change Impacts ◽  
Climate Data ◽  
Ecological Data ◽  
The Czech Republic ◽  
Climate Conditions ◽  
Vegetation Zones ◽  
Landscape Research

Regional climate changes impacts induce vegetation zones shift to higher altitudes in temperate landscape. This paper deals with applying of regional biogeography model of climate conditions for vegetation zones in Czechia to doctoral programme Regional Geography in Palacky University Olomouc. The model is based on general knowledge of landscape vegetation zonation. Climate data for model come from predicted validated climate database under RCP8.5 scenario since 2100. Ecological data are included in the Biogeography Register database (geobiocoenological data related to landscape for cadastral areas of the Czech Republic). Mathematical principles of modelling are based on set of software solutions with GIS. Students use the model in the frame of the course “Special Approaches to Landscape Research” not only for regional scenarios climate change impacts in landscape scale, but also for assessment of climate conditions for growing capability of agricultural crops or forest trees under climate change on regional level.

scholarly journals Cross-validation of bias-corrected climate simulations is misleading

2018 ◽  
Vol 22 (9) ◽  
pp. 4867-4873 ◽  
Author(s):  
Douglas Maraun ◽  
Martin Widmann
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Cross Validation ◽  
Climate Model ◽  
False Negative ◽  
Internal Variability ◽  
Validation Period ◽  
Climate Simulations ◽  
Free Running ◽  
The Difference

Abstract. We demonstrate both analytically and with a modelling example that cross-validation of free-running bias-corrected climate change simulations against observations is misleading. The underlying reasoning is as follows: a cross-validation can have in principle two outcomes. A negative (in the sense of not rejecting a null hypothesis), if the residual bias in the validation period after bias correction vanishes; and a positive, if the residual bias in the validation period after bias correction is large. It can be shown analytically that the residual bias depends solely on the difference between the simulated and observed change between calibration and validation periods. This change, however, depends mainly on the realizations of internal variability in the observations and climate model. As a consequence, the outcome of a cross-validation is also dominated by internal variability, and does not allow for any conclusion about the sensibility of a bias correction. In particular, a sensible bias correction may be rejected (false positive) and a non-sensible bias correction may be accepted (false negative). We therefore propose to avoid cross-validation when evaluating bias correction of free-running bias-corrected climate change simulations against observations. Instead, one should evaluate non-calibrated temporal, spatial and process-based aspects.

scholarly journals Can an Earth System Model simulate better climate change at mid-Holocene than an AOGCM? A comparison study of MIROC-ESM and MIROC3

2013 ◽  
Vol 9 (4) ◽  
pp. 1519-1542 ◽  
Author(s):  
R. Ohgaito ◽  
T. Sueyoshi ◽  
A. Abe-Ouchi ◽  
T. Hajima ◽  
S. Watanabe ◽  
...  
Keyword(s):  
Climate Change ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Earth System Model ◽  
Sea Surface ◽  
System Model ◽  
Earth System ◽  
Intercomparison Project ◽  
The Difference ◽  
Precipitation Enhancement

Abstract. The importance of evaluating models through paleoclimate simulations is becoming more recognized in efforts to improve climate projection. To evaluate an integrated Earth System Model, MIROC-ESM, we performed simulations in time-slice experiments for the mid-Holocene (6000 yr before present, 6 ka) and preindustrial (1850 AD, 0 ka) periods under the protocol of the Coupled Model Intercomparison Project 5/Paleoclimate Modelling Intercomparison Project 3. We first give an overview of the simulated global climates by comparing with simulations using a previous version of the MIROC model (MIROC3), which is an atmosphere–ocean coupled general circulation model. We then comprehensively discuss various aspects of climate change with 6 ka forcing and how the differences in the models can affect the results. We also discuss the representation of the precipitation enhancement at 6 ka over northern Africa. The precipitation enhancement at 6 ka over northern Africa according to MIROC-ESM does not differ greatly from that obtained with MIROC3, which means that newly developed components such as dynamic vegetation and improvements in the atmospheric processes do not have significant impacts on the representation of the 6 ka monsoon change suggested by proxy records. Although there is no drastic difference between the African monsoon representations of the two models, there are small but significant differences in the precipitation enhancement over the Sahara in early summer, which can be related to the representation of the sea surface temperature rather than the vegetation coupling in MIROC-ESM. Because the oceanic parts of the two models are identical, the difference in the sea surface temperature change is ultimately attributed to the difference in the atmospheric and/or land modules, and possibly the difference in the representation of low-level clouds.

scholarly journals Forest fires and climate-induced tree range shifts in the western US

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Avery P. Hill ◽  
Christopher B. Field
Keyword(s):  
Climate Change ◽  
Forest Fires ◽  
Fire Management ◽  
Range Shifts ◽  
Inventory Analysis ◽  
Plant Populations ◽  
Wildfire Occurrence ◽  
Western Us ◽  
The Difference ◽  
Climate Space

AbstractDue to climate change, plant populations experience environmental conditions to which they are not adapted. Our understanding of the next century’s vegetation geography depends on the distance, direction, and rate at which plant distributions shift in response to a changing climate. In this study we test the sensitivity of tree range shifts (measured as the difference between seedling and mature tree ranges in climate space) to wildfire occurrence, using 74,069 Forest Inventory Analysis plots across nine states in the western United States. Wildfire significantly increased the seedling-only range displacement for 2 of the 8 tree species in which seedling-only plots were displaced from tree-plus-seedling plots in the same direction with and without recent fire. The direction of climatic displacement was consistent with that expected for warmer and drier conditions. The greater seedling-only range displacement observed across burned plots suggests that fire can accelerate climate-related range shifts and that fire and fire management will play a role in the rate of vegetation redistribution in response to climate change.

scholarly journals Estimating the Relative Uncertainties Sourced from GCMs and Hydrological Models in Modeling Climate Change Impact on Runoff

2012 ◽  
Vol 13 (1) ◽  
pp. 122-139 ◽  
Author(s):  
Jin Teng ◽  
Jai Vaze ◽  
Francis H. S. Chiew ◽  
Biao Wang ◽  
Jean-Michel Perraud
Keyword(s):  
Climate Change ◽  
Climate Change Impact ◽  
Daily Rainfall ◽  
Low Flow ◽  
Hydrological Models ◽  
Rainfall Runoff ◽  
Runoff Modeling ◽  
Change Impact ◽  
The Difference ◽  
Climate Series

Abstract This paper assesses the relative uncertainties from GCMs and from hydrological models in modeling climate change impact on runoff across southeast Australia. Five lumped conceptual daily rainfall–runoff models are used to model runoff using historical daily climate series and using future climate series obtained by empirically scaling the historical climate series informed by simulations from 15 GCMs. The majority of the GCMs project a drier future for this region, particularly in the southern parts, and this is amplified as a bigger reduction in the runoff. The results indicate that the uncertainty sourced from the GCMs is much larger than the uncertainty in the rainfall–runoff models. The variability in the climate change impact on runoff results for one rainfall–runoff model informed by 15 GCMs (an about 28%–35% difference between the minimum and maximum results for mean annual, mean seasonal, and high runoff) is considerably larger than the variability in the results between the five rainfall–runoff models informed by 1 GCM (a less than 7% difference between the minimum and maximum results). The difference between the rainfall–runoff modeling results is larger in the drier regions for scenarios of big declines in future rainfall and in the low-flow characteristics. The rainfall–runoff modeling here considers only the runoff sensitivity to changes in the input climate data (primarily daily rainfall), and the difference between the hydrological modeling results is likely to be greater if potential changes in the climate–runoff relationship in a warmer and higher CO2 environment are modeled.

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