This document discusses the growing role of data and technology in agriculture. It notes that farms are generating huge amounts of data from soils, genetics, machinery sensors, weather, and remote sensing. However, for data to improve farm income, it must impact key factors like yield, price, and costs. Data standards and privacy protections need to be established to allow easy sharing and use of data. Both small and big data can provide insights if used through farm management software, helping farmers make better decisions and collaborate more effectively.
Among the new and emerging technologies in agriculture, Big Data is the one that promises the best improvements. Producers and growers want superior yields, cost savings, and better real-time data; consumers want healthier agricultural products at better prices; agriculture scientists need improved seeds and plants to face climate changes and prevent famine.
Today the use of data is having a very revolutionized effect with
cultivatable land in decline demand for food increasing from
developing countries farmers.
Farmers who use data are capable of turning ordinary harvests into
bumper crops and profits behind.This is the precision agriculture hub connecting the world’s biggest agricultural businesses farmers and suppliers using integrated software solutions.
Better ways of using Analytics in Agriculture in indiaYagnesh Shetty
Received the 1st Prize for this Research Paper presentation on Better Ways of using Analytics in Agriculture in India. Undertook Primary and Secondary Research to understand innovations in the agricultural sector that could transform the productivity levels and yeild/hectare for Indian farms. Did a comparative study of the Global scenario and made recommendations for Indian scope.
Presentation made on the new CGIAR Big Data in agriculture platform, and how big data approaches can contribute to improved productivity through data driven agronomy.
An overview of the CGIAR Platform for Big Data in Agriculture, officially launched in May 2017. The 15 CGIAR Research Centers and 12 Research Programs are partners in the Platform, alongside 70 external partners ranging international institutions, universities to private companies.
More info at: http://bigdata.cgiar.org
SC2 Workshop 1: Big Data challenges and solutions in agricultural and environ...BigData_Europe
“Lightning talk” in the Big Data Europe (BDE) workshop on “Big data for food, agriculture and forestry: opportunities and challenges” taking place on 22.9.2015 in Paris by Rob Lokers and Sander Janssen from Alterra, Wageningen UR
The Netherlands.
Among the new and emerging technologies in agriculture, Big Data is the one that promises the best improvements. Producers and growers want superior yields, cost savings, and better real-time data; consumers want healthier agricultural products at better prices; agriculture scientists need improved seeds and plants to face climate changes and prevent famine.
Today the use of data is having a very revolutionized effect with
cultivatable land in decline demand for food increasing from
developing countries farmers.
Farmers who use data are capable of turning ordinary harvests into
bumper crops and profits behind.This is the precision agriculture hub connecting the world’s biggest agricultural businesses farmers and suppliers using integrated software solutions.
Better ways of using Analytics in Agriculture in indiaYagnesh Shetty
Received the 1st Prize for this Research Paper presentation on Better Ways of using Analytics in Agriculture in India. Undertook Primary and Secondary Research to understand innovations in the agricultural sector that could transform the productivity levels and yeild/hectare for Indian farms. Did a comparative study of the Global scenario and made recommendations for Indian scope.
Presentation made on the new CGIAR Big Data in agriculture platform, and how big data approaches can contribute to improved productivity through data driven agronomy.
An overview of the CGIAR Platform for Big Data in Agriculture, officially launched in May 2017. The 15 CGIAR Research Centers and 12 Research Programs are partners in the Platform, alongside 70 external partners ranging international institutions, universities to private companies.
More info at: http://bigdata.cgiar.org
SC2 Workshop 1: Big Data challenges and solutions in agricultural and environ...BigData_Europe
“Lightning talk” in the Big Data Europe (BDE) workshop on “Big data for food, agriculture and forestry: opportunities and challenges” taking place on 22.9.2015 in Paris by Rob Lokers and Sander Janssen from Alterra, Wageningen UR
The Netherlands.
Big Data in Agriculture, the SemaGrow and agINFRA experienceAndreas Drakos
Presentation of the SemaGrow and agINFRA projects during the EDBT/ICDT 2014 Special Track on Big Data Management Challenges and Solutions in the Context of European Projects, 27th of March 2014
http://www.edbticdt2014.gr/index.php/eu-projects-track
Diverse agro-ecological and Socioeconomic situations create opportunities as well as vulnerabilities for Nepalese farmers. Rapidly changing unpredictable climate and technology innovations increase the need for reliable data/information day by day to make our agriculture more efficient, competitive and sustainable. Our data sources are different and we need to bring them together and make those data complete, secure, user-friendly, and accessible. The government's role needs to be more proactive, coordinating and facilitating to create data platforms working with other actors.
Jeremy Wilson - Return On Investment When Using Technology And DataJohn Blue
Return On Investment When Using Technology And Data - Jeremy Wilson, from the 2018 Conservation Tillage and Technology Conference, March 6 - 7, Ada, OH, USA.
More presentations at https://www.youtube.com/channel/UCZBwPfKdlk4SB63zZy16kyA
Presentation in the CGIAR Science Week in Montpellier 2016 on how Big Data cna change agricultural research and development, and what the CGIAR needs to do.
A confluence of factors have converged to afford the opportunity to apply data science at large scale to agricultural production. The demand for agricultural outputs is growing and there is a need to meet this demand by utilizing increasingly mechanized precision agriculture and enormous data volumes collected to intelligently optimize agriculture outputs. We will consider the machine learning challenges related to optimizing global food production.
Smart Farming is a development that emphasizes the use of information and communication technology in the
cyber-physical farm management cycle. New technologies such as the Internet of Things and Cloud Computing
are expected to leverage this development and introduce more robots and artificial intelligence in farming.
This is encompassed by the phenomenon of Big Data, massive volumes of data with a wide variety that can be
captured, analysed and used for decision-making. This review aims to gain insight into the state-of-the-art of
Big Data applications in Smart Farming and identify the related socio-economic challenges to be addressed. Following
a structured approach, a conceptual framework for analysiswas developed that can also be used for future
studies on this topic. The review shows that the scope of Big Data applications in Smart Farming goes beyond
primary production; it is influencing the entire food supply chain. Big data are being used to provide predictive
insights in farming operations, drive real-time operational decisions, and redesign business processes for
game-changing business models. Several authors therefore suggest that Big Data will cause major shifts in
roles and power relationsamong different players in current food supply chain networks. The landscape of stakeholders
exhibits an interesting gamebetween powerful tech companies, venture capitalists and often small startups
and new entrants. At the same time there are several public institutions that publish open data, under the
condition that the privacy of persons must be guaranteed. The future of Smart Farming may unravel in a continuum
of two extreme scenarios: 1) closed, proprietary systems in which the farmer is part of a highly integrated
food supply chain or 2) open, collaborative systems inwhich the farmer and every other stakeholder in the chain
network is flexible in choosing business partners as well for the technology as for the food production side. The
further development of data and application infrastructures (platforms and standards) and their institutional
embedment will play a crucial role in the battle between these scenarios. From a socio-economic perspective,
the authors propose to give research priority to organizational issues concerning governance issues and suitable
business models for data sharing in different supply chain scenarios.
Puedes ver cómo las Actividades Colectivas Gaudem que te ofrecemos cumplen con tu objetivo principal de entrenamiento. Elige las que más te gusten entre las más eficaces para tu Ruta y te asegurarás resultados sólo con acudir a nuestro gimnasio.
Concert Sponsorship Proposal -Major radio station event attracts thousands of consumers ages 35 to 54. Motivate prospects with:
Backstage “Meet & Greets”
Personal appearances by performers
Free Ticket With (test drive, home tour, minimum purchase,etc.
“Best Seats in The House” Sweepstakes
Discount Ticket Outlet
Perform at the Concert Contest
Custom Sweepstakes
EVEIL-3D : les défis de la réalité virtuelle pour l’apprentissage des langues...roymickael
Diaporama d'une communication présentée à la 2ème journée de formation et d’échanges de pratiques « Les usages du numérique au service des apprentissages », ESPE de l'académie de Strasbourg, Sélestat, 09 avril 2014
Big Data in Agriculture, the SemaGrow and agINFRA experienceAndreas Drakos
Presentation of the SemaGrow and agINFRA projects during the EDBT/ICDT 2014 Special Track on Big Data Management Challenges and Solutions in the Context of European Projects, 27th of March 2014
http://www.edbticdt2014.gr/index.php/eu-projects-track
Diverse agro-ecological and Socioeconomic situations create opportunities as well as vulnerabilities for Nepalese farmers. Rapidly changing unpredictable climate and technology innovations increase the need for reliable data/information day by day to make our agriculture more efficient, competitive and sustainable. Our data sources are different and we need to bring them together and make those data complete, secure, user-friendly, and accessible. The government's role needs to be more proactive, coordinating and facilitating to create data platforms working with other actors.
Jeremy Wilson - Return On Investment When Using Technology And DataJohn Blue
Return On Investment When Using Technology And Data - Jeremy Wilson, from the 2018 Conservation Tillage and Technology Conference, March 6 - 7, Ada, OH, USA.
More presentations at https://www.youtube.com/channel/UCZBwPfKdlk4SB63zZy16kyA
Presentation in the CGIAR Science Week in Montpellier 2016 on how Big Data cna change agricultural research and development, and what the CGIAR needs to do.
A confluence of factors have converged to afford the opportunity to apply data science at large scale to agricultural production. The demand for agricultural outputs is growing and there is a need to meet this demand by utilizing increasingly mechanized precision agriculture and enormous data volumes collected to intelligently optimize agriculture outputs. We will consider the machine learning challenges related to optimizing global food production.
Smart Farming is a development that emphasizes the use of information and communication technology in the
cyber-physical farm management cycle. New technologies such as the Internet of Things and Cloud Computing
are expected to leverage this development and introduce more robots and artificial intelligence in farming.
This is encompassed by the phenomenon of Big Data, massive volumes of data with a wide variety that can be
captured, analysed and used for decision-making. This review aims to gain insight into the state-of-the-art of
Big Data applications in Smart Farming and identify the related socio-economic challenges to be addressed. Following
a structured approach, a conceptual framework for analysiswas developed that can also be used for future
studies on this topic. The review shows that the scope of Big Data applications in Smart Farming goes beyond
primary production; it is influencing the entire food supply chain. Big data are being used to provide predictive
insights in farming operations, drive real-time operational decisions, and redesign business processes for
game-changing business models. Several authors therefore suggest that Big Data will cause major shifts in
roles and power relationsamong different players in current food supply chain networks. The landscape of stakeholders
exhibits an interesting gamebetween powerful tech companies, venture capitalists and often small startups
and new entrants. At the same time there are several public institutions that publish open data, under the
condition that the privacy of persons must be guaranteed. The future of Smart Farming may unravel in a continuum
of two extreme scenarios: 1) closed, proprietary systems in which the farmer is part of a highly integrated
food supply chain or 2) open, collaborative systems inwhich the farmer and every other stakeholder in the chain
network is flexible in choosing business partners as well for the technology as for the food production side. The
further development of data and application infrastructures (platforms and standards) and their institutional
embedment will play a crucial role in the battle between these scenarios. From a socio-economic perspective,
the authors propose to give research priority to organizational issues concerning governance issues and suitable
business models for data sharing in different supply chain scenarios.
Puedes ver cómo las Actividades Colectivas Gaudem que te ofrecemos cumplen con tu objetivo principal de entrenamiento. Elige las que más te gusten entre las más eficaces para tu Ruta y te asegurarás resultados sólo con acudir a nuestro gimnasio.
Concert Sponsorship Proposal -Major radio station event attracts thousands of consumers ages 35 to 54. Motivate prospects with:
Backstage “Meet & Greets”
Personal appearances by performers
Free Ticket With (test drive, home tour, minimum purchase,etc.
“Best Seats in The House” Sweepstakes
Discount Ticket Outlet
Perform at the Concert Contest
Custom Sweepstakes
EVEIL-3D : les défis de la réalité virtuelle pour l’apprentissage des langues...roymickael
Diaporama d'une communication présentée à la 2ème journée de formation et d’échanges de pratiques « Les usages du numérique au service des apprentissages », ESPE de l'académie de Strasbourg, Sélestat, 09 avril 2014
[Webinar recording in last slide or at https://youtu.be/DMg9UI7Ur0M, 26/3/2018]
As part of its work on farmers’ data rights and following up on the face-to-face course on Farmers’ Access to Data organized in Centurion in November 2017, GFAR collaborates with the Global Open Data for Agriculture and Nutrition initiative (GODAN) and the Technical Center for Agricultural and Rural Cooperarion (CTA) on a series of webinars on data-driven agriculture, its opportunities and its challenges.
Overview of webinar #3
This webinar is a continuation of exploring digital agriculture for smallholder farmers. The first webinar provided an overview of digital agriculture, the trends impacting it, and it advantages and challenges for smallholder farmers. The second identified specific data needed by farmers, as well as potential sources.
“Crossing the Donga” will provide smallholder farmers, and those who support them, specific methods for ensuring farmer-centric solutions. The webinar will examine some of the key challenges that are blocking adoption of digital architecture by smallholder farmers. Attendees will learn a process for mapping their data needs, based on their goals and key tasks. Attendees will learn the foundational market model, and how to create value for success.
About the presenter
Dan Berne is a highly regarded professional business growth strategist with over 30 years’ experience. Dan led the effort to create an Ag Irrigation market strategy for the Northwest Energy Efficiency Alliance (NEEA). He also conducted grower experience studies to help identify barriers to grower adoption of energy saving practices. Dan wrote or co-wrote many of the NEEA Ag Irrigation reports. Dan serves as the Project Manager on AgGateway’s Precision Ag Irrigation Language data standards project. He is an affiliate of the Chasm Institute, and a certified practitioner of Innovation Games.
Dan started the “Lagom Ag Initiative” within his company to help accelerate the adoption of precision farming practices and improve the use of digital agricultural methodologies. Lagom is a Swedish word that means “just enough.” It is also used to mean “simply perfect.” It fits our philosophy of helping farmers use just enough water, just enough fertilizers, just enough energy to be profitable while increasing or maintaining yield.
U.S. Department of Agriculture conducts Agricultural Resource Management Survey each year to measure financial well-being of the U.S. farm sector. This presentation outlines several key impact of the results of this survey.
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
StarCompliance is a leading firm specializing in the recovery of stolen cryptocurrency. Our comprehensive services are designed to assist individuals and organizations in navigating the complex process of fraud reporting, investigation, and fund recovery. We combine cutting-edge technology with expert legal support to provide a robust solution for victims of crypto theft.
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Our team of experienced lawyers can initiate lawsuits on your behalf and represent you in various jurisdictions around the world. They work diligently to recover your stolen funds and ensure that justice is served.
At StarCompliance, we understand the urgency and stress involved in dealing with cryptocurrency theft. Our dedicated team works quickly and efficiently to provide you with the support and expertise needed to recover your assets. Trust us to be your partner in navigating the complexities of the crypto world and safeguarding your investments.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
2. • Soils, physiology
sensor data
• Genetics, genomics,
phenotypes, models
• GPS and planter /
sprayer / combine
data
• Weather and climate
data and models
• Image data from
machinery, remote
sensing
GBs - TBs / plant University library
TBs - PBs/ region
GBs / field /yr Pickup bed full of paper
TBs - PBs / region
PBs - EBs / region
All US academic
libraries
Every word ever spoken
by every human being
Data type Size in bytes Size analogy
Geo-Eye1 – about 8 terabytes / day
5. Key stakeholder mindset…
Key Questions
• Should I share my data
with a 3rd party?
• What is the 3rd party
doing with my data?
• Does this make my work
easier
• Will this improve farm
income?
6. Data must impact basic formula
Yield x Price - Costs = Farm Income
• Enabler
• Monitor
• Predictor
7. Foundation needs set
• Data privacy has to be clear
• Data standards need established
• Ease transfer from tractor to cloud
• Pace of larger industry transformation
• All stakeholders need to have a clear path
to profits
12. The Value Chain is
More than Farming
USDA ERS Food Dollar Series, 2013
13. The Value Chain
Approaching the Farm
Farm Assets
• Land and buildings
$2.3T
• Machinery and
equipment
$243B
$42
$76
$29
$17
$12
$16
Selected US Farm Production Expenses
in Billions
Livestock and poultry
purchased or leased
Feed purchased
Fertilizer, lime, and soil
conditioners purchased
Gasoline, fuels, and oils
purchased
Interest expense
Chemicals purchased
Data from USDA Census of Agriculture, 2012
14. Where are the Farm Operations?
Data from USDA Census of Agriculture, 2012
15. Where Are Others Working in the
Value Chain?
About 300,000 in Food
Manufacturing and Ag
Implement Production In
Illinois and Adjacent
Midwestern States Alone
Data from US Department of Labor, 2014
16. Businesses in Food and Ag Make
Important Decisions About
Where to Buy and Sell
Imagine a plant milling 7 Million bushels of corn per
year…
• What if the average bushel of corn trucked to the plant
didn’t have to go as far?
• For every mile saved: about $25,000 per year in truck
freight costs for corn at that mill.*
Imagine this in the context of the US and its use of
12 Billion bushels of corn per year domestically …
* We’ll let the economists sort out how much of this savings is enjoyed by who.
17. Want to continue discussion about
where to buy, sell, or act?
Charles Linville, PhD
Founder and President
linville@ploughman-analytics.com
2021 S. 1st St. Ste. 206D
Champaign, IL 61820
(217) 693-4000
19. Software Will Make Farming a Better Business
1. Easier to get more done…
– Collaboration
– Process improvement
– Take on more scale, complexity
2. Easier to make best decisions…
– $ yield not bushel yield
– Probabilities not recent experience
– Acting faster with confidence
20. It All Starts with Software Adoption
• Until farms run their business in software every day “big
data” will have limited impact
• Using farm management software allows them to…
– Capture their own farm’s data
– Build habit of making and recording decisions in software
– Trust that technology can make good recommendations
21. Farms Need Data of All Sizes
Big Data Industry • How does price/value of land in NE compare
to AK?
• What marketing strategy would have
performed best in my area for last 10 years?
Medium Data Peer farms • What do my peers pay for similar quantities
of DKC60-67?
• What is average contribution margin for 10K
acre farm with my crop mix?
Small Data Single farm • How much risk do I take if I farm 2,000 more
acres with same capacity?
• How does margin of crop rotation A compare
to crop rotation B?
