scholarly journals Development of an IoT-Driven System for High Valued Crop Farming

2020 ◽  
Vol 9 (3S) ◽  
pp. 1-6
Keyword(s):  
Vital Role ◽  
Farming Practices ◽  
Traditional Methods ◽  
Qualitative And Quantitative ◽  
Use Of Technology ◽  
Driven System ◽  
Smart Farming ◽  
Crop Farming ◽  
Smart Agriculture ◽  
Survey Questionnaires

The use of technology in agriculture plays a vital role in revolutionizing traditional methods of farming. The insufficiency of technology and the use of traditional methods of farming results to low yielding of crops. The integration of smart agriculture using Internet of Things is an absolute solution in modernizing the traditional methods of farming. This paper aims to design and develop an IoT-driven system for high valued crop farming which automates farming processes like watering, distribution and application of fertilizer. It provides real-time monitoring and collection of information about the farm conditions like moisture, temperature, fertility of soil and level of water. Qualitative and quantitative data were gathered by means of interview and survey questionnaires which were given to Alfonso Lista, Ifugao farmers and Yaojiaxi Corporation personnel. The majority of the respondents evaluated the functionality of the system as “Fully Functional”, usability as “Very Usable”, efficiency as “Mostly Efficient” and maintainability as “Mostly Agree” based from the result of ISO standard criteria survey questionnaires. The developed prototype realized smart farming which promotes sustainable agriculture involving the integration of IoT technology into existing farming practices that definitely reduces manual work, man power and provides efficiency on the use of farming resources.

scholarly journals IoT-Based Smart Agriculture

2021 ◽  
pp. 63-77
Author(s):  
Kishore Kumar K.
Keyword(s):  
Farming System ◽  
Agricultural Field ◽  
Crop Fields ◽  
Modern Agriculture ◽  
Current State ◽  
Use Of Technology ◽  
Smart Farming ◽  
Potential Population ◽  
Field Information ◽  
Smart Agriculture

Smart farming is an evolving concept since IoT sensors are capable of providing agricultural field information and then acting on the basis of user feedback. The main factor in improving the yield of efficient crops is the control of environmental conditions. There is a small yard, farmland, or a plantation area for most of us. However, our busy timetable does not allow us to manage it well. But we can easily accomplish it with the use of technology. So, the authors make an IoT-based smart farming system that can control soil moisture. As data has become a critical component in modern agriculture to assist producers with critical decisions and make a decision with objective data obtained from sensors, significant advantages emerge. This chapter explores the current state of advanced farm management systems by revisiting each critical phase, from data collection in crop fields to variable rate applications, in order for growers to make informed decisions save money while also protecting the environment and transforming how food is grown to meet potential population growth.

scholarly journals The Effectiveness of Developing Contextual Material For Teaching English at Madrasah Aliyah

2018 ◽  
Vol 2 (2) ◽  
Author(s):  
Mukhaiyar Mukhaiyar ◽  
Z Mawardi Effendi ◽  
Zul Amri
Keyword(s):  
Data Analysis ◽  
Learning Process ◽  
Development Research ◽  
Teaching English ◽  
Quantitative Technique ◽  
Qualitative And Quantitative ◽  
Post Test ◽  
Is Development ◽  
Addie Model ◽  
Survey Questionnaires

One of the aspects that determine the success of the learning process is teaching materials.  This research aimed to develop the effectiveness of contextual material for teaching English at Madrasah Aliyah.  The design of this research is development research by using ADDIE model. The product consists of two books, (teacher's book and students'book) the title is “English For Us”.  Subjects in this research were all students of grade X. Sample were 87 persons and it was selected by using the purposive technique. The instrument used to collect data was a survey, questionnaires, and an interview. Data analysis was used the qualitative and quantitative technique. The practicalities of the teacher’s book were 82.54   and students’ book showed an average  84.63 score. The effectiveness of a product is measured through pre-test is 68,00  and post-test is 75.44.  It can be concluded that the contextual material for teaching English at Madrasah Aliyah was effective

scholarly journals Advanced Leak Detection and Quantification of Methane Emissions Using sUAS

Drones ◽  
2021 ◽  
Vol 5 (4) ◽  
pp. 117
Author(s):  
Derek Hollenbeck ◽  
Demitrius Zulevic ◽  
Yangquan Chen
Keyword(s):  
Oil And Gas ◽  
Near Field ◽  
Oil And Gas Industry ◽  
Leak Detection ◽  
Methane Emissions ◽  
Vital Role ◽  
Unmanned Aircraft ◽  
Natural Ecosystems ◽  
Traditional Methods ◽  
Detection Techniques

Detecting and quantifying methane emissions is gaining an increasingly vital role in mitigating emissions for the oil and gas industry through early detection and repair and will aide our understanding of how emissions in natural ecosystems are playing a role in the global carbon cycle and its impact on the climate. Traditional methods of measuring and quantifying emissions utilize chamber methods, bagging individual equipment, or require the release of a tracer gas. Advanced leak detection techniques have been developed over the past few years, utilizing technologies, such as optical gas imaging, mobile surveyors equipped with sensitive cavity ring down spectroscopy (CRDS), and manned aircraft and satellite approaches. More recently, sUAS-based approaches have been developed to provide, in some ways, cheaper alternatives that also offer sensing advantages to traditional methods, including not being constrained to roadways and being able to access class G airspace (0–400 ft) where manned aviation cannot travel. This work looks at reviewing methods of quantifying methane emissions that can be, or are, carried out using small unmanned aircraft systems (sUAS) as well as traditional methods to provide a clear comparison for future practitioners. This includes the current limitations, capabilities, assumptions, and survey details. The suggested technique for LDAQ depends on the desired accuracy and is a function of the survey time and survey distance. Based on the complexity and precision, the most promising sUAS methods are the near-field Gaussian plume inversion (NGI) and the vertical flux plane (VFP), which have comparable accuracy to those found in conventional state-of-the-art methods.

scholarly journals Smart Agriculture and Smart Farming using IoT Technology

2021 ◽  
Vol 2089 (1) ◽  
pp. 012038
Author(s):  
V Dankan Gowda ◽  
M Sandeep Prabhu ◽  
M Ramesha ◽  
Jayashree M Kudari ◽  
Ansuman Samal
Keyword(s):  
Internet Of Things ◽  
Treatment Optimization ◽  
Agricultural Producers ◽  
Support Tools ◽  
Smart Farming ◽  
Protection Systems ◽  
Smart Agriculture ◽  
Remote Monitoring Systems ◽  
Future Technologies ◽  
The Internet Of Things

Abstract It has become easier to access agriculture data in recent years as a result of a decline in digital breaches between agricultural producers and IoT technologies. These future technologies can be used to boost productivity by cultivating food more sustainably while also preserving the environment, thanks to improved water use and input and treatment optimization. The Internet of Things (IoT) enables the production of agricultural process-supporting systems. Referred to as remote monitoring systems, decision support tools, automated irrigation systems, frost protection systems, and fertilisation systems, respectively. Farmers and researchers must be provided with a detailed understanding of IoT applications in agriculture as a result of the knowledge described above. This study is about using Internet of Things (IoT) technologies and techniques to enhance agriculture. This article is meant to serve as an introduction to IoT-based applications in agriculture by identifying need for such tools and explaining how they support agriculture.

Deep Learning and Computer Vision in Smart Agriculture

2020 ◽  
pp. 66-88
Author(s):  
Shiv Kumar ◽  
Agrima Yadav ◽  
Deepak Kumar Sharma
Keyword(s):  
Computer Vision ◽  
Deep Learning ◽  
Life Cycle ◽  
World Population ◽  
Traditional Methods ◽  
Demand And Supply ◽  
The World ◽  
Increasing Demand ◽  
Smart Agriculture ◽  
The Many

The exponential growth in the world population has led to an ever-increasing demand for food supplies. This has led to the realization that conventional and traditional methods alone might not be able to keep up with this demand. Smart agriculture is being regarded as one of the few realistic ways that, together with the traditional methods, can be used to close the gap between the demand and supply. Smart agriculture integrates the use of different technologies to better monitor, operate, and analyze different activities involved in different phases of the agricultural life cycle. Smart agriculture happens to be one of the many disciplines where deep learning and computer vision are being realized to be of major impact. This chapter gives a detailed explanation of different deep learning methods and tries to provide a basic understanding as to how these techniques are impacting different applications in smart agriculture.

Adult Education With Technology for Transformative Learning

2021 ◽  
pp. 718-734
Author(s):  
Victor Wang ◽  
Uta M. Stelson
Keyword(s):  
Adult Education ◽  
Transformative Learning ◽  
Learning Strategies ◽  
Teaching And Learning ◽  
Vital Role ◽  
Learning Technology ◽  
Learner Engagement ◽  
Web 3.0 ◽  
Use Of Technology ◽  
Technological Skills

Adult learners often fear that employment will be difficult if they lack technological skills. Newspapers, magazines, and advertisements for positions often emphasize the importance of the use of technology in the workplace. Without adequate skills in the use of appropriate technologies, adult workers may face challenges in finding employment. Web technologies can provide powerful teaching and learning strategies, enhance learner engagement, provide a chance to acquire critical technological skills, and promote critical reflection. This chapter addresses technological applications in vocational and adult education advancement from different perspectives. Technology has the potential to support transformative learning. Technology, along with the vital role of adult educators, helps learners grow, change, and develop. Through the discussion of these, and related issues, a model titled, Learners' Seeking Transformation via Web 2.0 and Web 3.0 Technologies, emerged.

Review on Smart Farming and Smart Agriculture for Society: Post-pandemic Era

2021 ◽  
pp. 233-256
Author(s):  
Nagarjuna Telagam ◽  
Nehru Kandasamy ◽  
M. Arun Kumar
Keyword(s):  
Smart Farming ◽  
Smart Agriculture

Smart Farming Using Internet of Things

2021 ◽  
pp. 236-250
Author(s):  
Rishabh Verma ◽  
Latika Kharb
Keyword(s):  
Deep Learning ◽  
Internet Of Things ◽  
Water System ◽  
Field Conditions ◽  
Learning Models ◽  
System Framework ◽  
Smart Farming ◽  
The World ◽  
Crop Types ◽  
Smart Agriculture

Smart farming through IoT technology could empower farmers to upgrade profitability going from the amount of manure to be used to the quantity of water for irrigating their fields and also help them to decrease waste. Through IoT, sensors could be used for assisting farmers in the harvest field to check for light, moistness, temperature, soil dampness, etc., and robotizing the water system framework. Moreover, the farmers can screen the field conditions from anyplace and overcome the burden and fatigue to visit farms to confront problems in the fields. For example, farmers are confronting inconvenience while utilizing right quantity and time to use manures and pesticides in their fields as per the crop types. In this chapter, the authors have introduced a model where farmers can classify damaged crops and healthy crops with the help of different sensors and deep learning models. (i.e., The idea of implementing IoT concepts for the benefit of farmers and moving the world towards smart agriculture is presented.)

Workforce: Goals for Research and Innovation

Inclusion ◽  
2015 ◽  
Vol 3 (4) ◽  
pp. 267-273 ◽  
Author(s):  
Colleen McLaughlin ◽  
Lori Sedlezky ◽  
Harolyn Belcher ◽  
Abby Marquand ◽  
Amy Hewitt
Keyword(s):  
Family Support ◽  
The United States ◽  
Vital Role ◽  
Intellectual And Developmental Disabilities ◽  
Competency Development ◽  
Research And Innovation ◽  
Use Of Technology ◽  
Direct Support ◽  
Direct Support Professionals

Abstract Across the United States, there is growing demand for a competent and stable workforce able to effectively support the health and community lives of individuals with intellectual and developmental disabilities (IDD) throughout the lifespan. This article describes national goals for research and innovation to advance the IDD workforce. The research goals outlined address important workforce topics that include increasing capacity and sustainability, competency development and quality support, the use of technology, family support, and the vital role of direct support professionals in helping people with IDD to become fully included and valued members of their communities.

scholarly journals Sensor Applications in Agrifood Systems: Current Trends and Opportunities for Water Stewardship

Climate ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 44 ◽  
Author(s):  
Naoum Tsolakis ◽  
Eirini Aivazidou ◽  
Jagjit Singh Srai
Keyword(s):  
Precision Agriculture ◽  
Vital Role ◽  
Water Monitoring ◽  
Supply Networks ◽  
Factors Affecting ◽  
Sensor Applications ◽  
Smart Farming ◽  
Production Technologies ◽  
Food Commodities ◽  
Water Scarce

Growing global food demand and security concerns dictate the need for state-of-the-art food production technologies to increase farming efficiency. Concurrently, freshwater overexploitation in agriculture, especially in arid and water-scarce areas, emphasises the vital role of appropriate water-saving irrigations techniques to ensure natural resources sustainability in food supply networks. In line with the development of automated systems, the use of sensors for water monitoring, indicatively in the cases of smart farming or precision agriculture, could further promote the preservation of freshwater resources. To this end, this research first provides a review of sensor applications for improving sustainability in agrifood systems. We then focus on digital technologies applied for monitoring and assessing freshwater utilisation in the food commodities sector based on academic literature and real-world business evidence. A contextual map is developed for capturing the main technical, environmental and economic factors affecting the selection of sensors for water monitoring and stewardship during agricultural production. This first-effort framework, in terms of sensor-based freshwater monitoring, aims at supporting the agrifood system’s decision makers to identify the optimal sensor applications for improving sustainability and water efficiency in agricultural operations.

Sign in / Sign up

Export Citation Format

Share Document