scholarly journals Growing Trends in Indian Farming using Internet of Things (IoT)

2019 ◽  
Vol 9 (2) ◽  
pp. 4360-4364 ◽  
Keyword(s):  
Energy Management ◽  
Soil Structure ◽  
Low Cost ◽  
Weather Condition ◽  
Weather Forecast ◽  
Weather Conditions ◽  
Model Solution ◽  
Indian Agriculture ◽  
Solar Plant ◽  
Day By Day

India is a land of different weather conditions and versatile soils. Every year Indian farmers are facing problem of sudden rain in their areas without any correct weather forecast which leads to damage of the already grown crops. The second major problem pertaining to Indian farmers is the lack of sufficient knowledge about their soil. The soil forecasting of how the soil structure is changing day by day due to different weather condition and other external factors, and which crop will be optimally suited to be grown in such soil are some of the problems common to the farmers. This paper makes an attempt to assess and propose model solution along with developing a prototype of device using IoT for use by farmers in Indian agriculture practice. The solution proposed will have a centralized data server to analyze the data and report to the farmer the precautionary steps to be taken in advance for safety of the crops. The solution proposed have eco-friendly energy management through solar plant and wind energy which makes IoT device more portable and low cost, along with making it implementable in Indian rural sectors..

scholarly journals Classification of Active Fires and Weather Conditions in the Lower Amur River Basin

2020 ◽  
Vol 12 (19) ◽  
pp. 3204
Author(s):  
Hiroshi Hayasaka ◽  
Galina V. Sokolova ◽  
Andrey Ostroukhov ◽  
Daisuke Naito
Keyword(s):  
River Basin ◽  
Boreal Forests ◽  
Weather Condition ◽  
Weather Forecast ◽  
Weather Conditions ◽  
Amur River Basin ◽  
Fire Weather ◽  
Strong Wind ◽  
Amur River ◽  
Active Fire

Most wildland fires in boreal forests occur during summer, but major fires in the lower Amur River Basin of the southern Khabarovsk Krai (SKK) mainly occur in spring. To reduce active fires in the SKK, we carried out daily analysis of MODIS (Moderate Resolution Imaging Spectroradiometer) hotspot (HS) data and various weather charts. HS data of 17 years from 2003 were used to identify the average seasonal fire occurrence. Active fire-periods were extracted by considering the number of daily HSs and their continuity. Weather charts, temperature maps, and wind maps during the top 12 active fire-periods were examined to clarify each fire weather condition. Analysis results showed that there were four active fire-periods that occurred in April, May, July, and October. Weather charts during the top active fire-periods showed active fires in April and October occurred under strong wind conditions (these wind velocities were over 30 km h−1) related to low-pressure systems. The very active summer fire at the end of June 2012 occurred related to warm air mass advection promoted by large westerly meandering. We showed clear fire weather conditions in the SKK from March to October. If a proper fire weather forecast is developed based on our results, more efficient and timely firefighting can be carried out.

scholarly journals Renewable Source Automatic Switching System Apprised on IOT

2021 ◽  
pp. 49-55
Author(s):  
Tarakeshwari V ◽  
Hema C ◽  
Hemalatha P N ◽  
Madhushree ◽  
Syeda Saniya Mehdi
Keyword(s):  
Renewable Energy ◽  
Energy Management ◽  
Management System ◽  
Weather Conditions ◽  
Energy Management System ◽  
Combined System ◽  
Renewable Sources ◽  
Solar Plant ◽  
Bad Weather ◽  
The Individual

Now a days non pollution power production is popular because of less pollution and eco-friendly. This paper presents a new system configuration of the front-end rectifier stage for automatic energy management system of renewable energy source. In today’s technology driven world electricity is one of the foremost things for our day-to-day life activities. As we all are oblivious of the fact that the renewable sources of energy are depleting at a lightning-fast rate. So, it’s time for us to shift the focus from conventional to non-conventional sources of energy to produce electricity. The output of the electricity produced by non-conventional sources is less than their counterparts. Renewable sources do not have any detrimental effect on the environment. Solar- wind and main automatic energy management system of renewable energy is basically an integration of solar plant and a wind energy plant. It will help in providing the uninterrupted power supply. As during bad weather conditions, the production can be shifted from one source to other with the help of a microcontroller. A microcontroller ensures the optimum utilization of resources and it also increases the efficiency of the combined system as compared to the individual mode of generation. It helps in decreasing the dependence on one single source and makes the system more reliable. The system can be used for both industrial and domestic applications. This configuration allows the two or more sources to supply the load depending on the availability of the energy sources and priority.

scholarly journals Low Cost Iot Enable Weather Station for Precision Agriculture

2019 ◽  
Vol 8 (4) ◽  
pp. 3183-3186
Keyword(s):  
Wind Speed ◽  
Wind Direction ◽  
Precision Agriculture ◽  
Low Cost ◽  
Local Level ◽  
Weather Condition ◽  
Weather Conditions ◽  
Mobile App ◽  
Weather Station ◽  
Atmospheric Conditions

Agrometeorology plays an important role in Precision Agriculture for resource management and effects both the quality and quantity of agriculture products. The existing solutions for monitoring weather parameters in agrometeorology are highly global and costly. These solutions are most of the time are inaccessible to the common man or farmers and require frequent physical visits to the field for obtaining information. But in agriculture monitoring highly localized weather condition is required because the weather conditions applicable farm land of one city may not be as such for a farmer of small rural. Weather conditions such as wind speed, wind direction, rainfall, solar radiation, atmospheric pressure, air particle level humidity and temperature measurement plays an important role in different fields like Agriculture, Science, Engineering and Technology. The proposed work provides an optimal solution for monitoring the weather conditions at extremely local level with low cost, compact Internet of Things (IoT) based system. In this paper the design of the system is presented with the use of NodeMCU for realizing the low-cost solution. This low-cost weather station is a product equipped with sensors to measure atmospheric conditions like temperature, humidity, wind speed, wind direction which has predominant effect in agriculture. With embedded IoT connectivity, the proposed weather station is capable to upload the information to IoT cloud ad can be used for further analysis.The user can access the information uploaded by the system anywhere from the world with the help on mobile app or web link on laptop/desktop. The “Low cost Compact IoT enabled Weather Station” does not have any display which make the proposed system more power efficient with overall current rating of about only 80mA to 90mA.

scholarly journals An investigation of the effects of environmental and ecologic factors on cutaneous leishmaniasis in the old world: a systematic review study

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Abolfazl Mohammadbeigi ◽  
Salman Khazaei ◽  
Hamidreza Heidari ◽  
Azadeh Asgarian ◽  
Shahram Arsangjang ◽  
...  
Keyword(s):  
Systematic Review ◽  
Environmental Factors ◽  
Land Cover ◽  
Cutaneous Leishmaniasis ◽  
Weather Condition ◽  
Weather Conditions ◽  
Eligibility Criteria ◽  
Screening Process ◽  
Old World ◽  
Review Study

AbstractObjectivesLeishmaniasis is a neglected and widespread parasitic disease that can lead to serious health problems. The current review study aimed to synthesize the relationship between ecologic and environmental factors (e.g., weather conditions, climatology, temperature and topology) and the incidence of cutaneous leishmaniasis (CL) in the Old World.ContentA systematic review was conducted based on English, and Persian articles published from 2015 to 2020 in PubMed/Medline, Science Direct, Web of Science and Google Scholar. Keywords used to search articles were leishmaniasis, environmental factors, weather condition, soil, temperature, land cover, ecologic* and topogr*. All articles were selected and assessed for eligibility according to the titles or abstracts. The quality screening process of articles was carried out by two independent authors. The selected articles were checked according to the inclusion and exclusion criteria.Summary and outlookA total of 827 relevant records in 2015–2020 were searched and after evaluating the articles, 23 articles met the eligibility criteria; finally, 14 full-text articles were included in the systematic review. Two different categories of ecologic/environmental factors (weather conditions, temperature, rainfall/precipitation and humidity) and land characteristics (land cover, slope, elevation and altitude, earthquake and cattle sheds) were the most important factors associated with CL incidence.ConclusionsTemperature and rainfall play an important role in the seasonal cycle of CL as many CL cases occurred in arid and semiarid areas in the Old World. Moreover, given the findings of this study regarding the effect of weather conditions on CL, it can be concluded that designing an early warning system is necessary to predict the incidence of CL based on different weather conditions.

scholarly journals It’s the Weather: Quantifying the Impact of Weather on Retail Sales

2021 ◽  
Author(s):  
Natalie Rose ◽  
Les Dolega
Keyword(s):  
Weather Condition ◽  
Weather Conditions ◽  
Influential Factor ◽  
Retail Sector ◽  
Retail Sales ◽  
Weather Impact ◽  
High Street ◽  
Sector Decision ◽  
The Impact ◽  
The Relationship

AbstractThe weather is considered as an influential factor on consumer purchasing behaviours and plays a significant role in many aspects of retail sector decision making. As a result, better understanding of the magnitude and nature of the influence of variable UK weather conditions can be beneficial to many retailers and other stakeholders. This study addresses the dearth of research in this area by quantifying the relationship between different weather conditions and trading outcomes. By employing comprehensive daily sales data for a major high street retailer with over 2000 stores across England and adopting a random forest methodology, the study quantifies the influence of various weather conditions on daily retail sales. Results indicate that weather impact is greatest in the summer and spring months and that wind is consistently found to be the most influential weather condition. The top five most weather-dependent categories cover a range of different product types, with health foods emerging as the most susceptible to the weather. Also, sales from out-of-town stores show a far more complex relationship with the weather than those from traditional high street stores with the regions London and the South East experiencing the greatest levels of influence. Various implications of these findings for retail stakeholders are discussed and the scope for further research outlined.

scholarly journals Turning Base Transceiver Stations into Scalable and Controllable DC Microgrids Based on a Smart Sensing Strategy

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1202
Author(s):  
Miguel Tradacete ◽  
Carlos Santos ◽  
José A. Jiménez ◽  
Fco Javier Rodríguez ◽  
Pedro Martín ◽  
...  
Keyword(s):  
Electricity Market ◽  
Low Cost ◽  
Storage System ◽  
Environmental Parameters ◽  
Weather Conditions ◽  
Energy Storage System ◽  
Electricity Grid ◽  
Dc Microgrids ◽  
Smart Sensing ◽  
Battery Energy

This paper describes a practical approach to the transformation of Base Transceiver Stations (BTSs) into scalable and controllable DC Microgrids in which an energy management system (EMS) is developed to maximize the economic benefit. The EMS strategy focuses on efficiently managing a Battery Energy Storage System (BESS) along with photovoltaic (PV) energy generation, and non-critical load-shedding. The EMS collects data such as real-time energy consumption and generation, and environmental parameters such as temperature, wind speed and irradiance, using a smart sensing strategy whereby measurements can be recorded and computing can be performed both locally and in the cloud. Within the Spanish electricity market and applying a two-tariff pricing, annual savings per installed battery power of 16.8 euros/kW are achieved. The system has the advantage that it can be applied to both new and existing installations, providing a two-way connection to the electricity grid, PV generation, smart measurement systems and the necessary management software. All these functions are integrated in a flexible and low cost HW/SW architecture. Finally, the whole system is validated through real tests carried out on a pilot plant and under different weather conditions.

scholarly journals How Can Existing Ground-Based Profiling Instruments Improve European Weather Forecasts?

2019 ◽  
Vol 100 (4) ◽  
pp. 605-619 ◽  
Author(s):  
A. J. Illingworth ◽  
D. Cimini ◽  
A. Haefele ◽  
M. Haeffelin ◽  
M. Hervo ◽  
...  
Keyword(s):  
Real Time ◽  
Traffic Control ◽  
Positive Impact ◽  
Weather Forecast ◽  
Weather Conditions ◽  
Time Data ◽  
Weather Forecasts ◽  
Forecast Models ◽  
Wind Lidar ◽  
Microwave Radiometers

Abstract To realize the promise of improved predictions of hazardous weather such as flash floods, wind storms, fog, and poor air quality from high-resolution mesoscale models, the forecast models must be initialized with an accurate representation of the current state of the atmosphere, but the lowest few kilometers are hardly accessible by satellite, especially in dynamically active conditions. We report on recent European developments in the exploitation of existing ground-based profiling instruments so that they are networked and able to send data in real time to forecast centers. The three classes of instruments are i) automatic lidars and ceilometers providing backscatter profiles of clouds, aerosols, dust, fog, and volcanic ash, the last two being especially important for air traffic control; ii) Doppler wind lidars deriving profiles of wind, turbulence, wind shear, wind gusts, and low-level jets; and iii) microwave radiometers estimating profiles of temperature and humidity in nearly all weather conditions. The project includes collaboration from 22 European countries and 15 European national weather services, which involves the implementation of common operating procedures, instrument calibrations, data formats, and retrieval algorithms. Currently, data from 265 ceilometers in 19 countries are being distributed in near–real time to national weather forecast centers; this should soon rise to many hundreds. One wind lidar is currently delivering real time data rising to 5 by the end of 2019, and the plan is to incorporate radiometers in 2020. Initial data assimilation tests indicate a positive impact of the new data.

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