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.
Internet of Things ( IOT) in AgricultureAmey Khebade
Application of IOT in Agriculture
Monitoring soil moisture and temperature
Controlled irrigation
Efficient usage of input like water, fertilizers, pesticides, etc
Reduced cost of production
Connected greenhouses and stables
Livestock monitoring
Download PPT for better design and animation
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.
Farmers, growers, and agricultural companies are increasingly adopting digital technologies to transform a traditional industry. In the past, farmers and growers made decisions based on their personal experience, combined with interpreting local conditions.
But digital technologies, from the internet of things to blockchain, are rapidly turning the industry into a high-tech sector. Smart, connected devices can now provide the insight to enable farms to improve every aspect of their operations.
- What is the digital agriculture revolution?
- How digital technologies are transforming the industry – including the impact of the internet of things and blockchain.
- What are the unique challenges that the sector faces in adopting digital technology?
- The future of agriculture
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.
Internet of Things ( IOT) in AgricultureAmey Khebade
Application of IOT in Agriculture
Monitoring soil moisture and temperature
Controlled irrigation
Efficient usage of input like water, fertilizers, pesticides, etc
Reduced cost of production
Connected greenhouses and stables
Livestock monitoring
Download PPT for better design and animation
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.
Farmers, growers, and agricultural companies are increasingly adopting digital technologies to transform a traditional industry. In the past, farmers and growers made decisions based on their personal experience, combined with interpreting local conditions.
But digital technologies, from the internet of things to blockchain, are rapidly turning the industry into a high-tech sector. Smart, connected devices can now provide the insight to enable farms to improve every aspect of their operations.
- What is the digital agriculture revolution?
- How digital technologies are transforming the industry – including the impact of the internet of things and blockchain.
- What are the unique challenges that the sector faces in adopting digital technology?
- The future of agriculture
Why apply IoT in agriculture? Special aspects to consider for
IoT in agriculture. IoT application in this field.
More information on our website: http://aggregate.tibbo.com/industries/agriculture.html
The presentation is on Digital Agriculture and Its Application in Agriculture. The presentation went through problems of Agriculture, potential ways to cater those problems and how use of technology and their uses sustain the life of agriculture for our future generations with few case studies. I hope this is useful to student community. For PPT mail me at #pavankalyan6898@gmail.com , thank You
Using IoT as well as GSM, a whole new concept of farming using networks is introduced reducing labor, updating farmers about the live conditions of farms on mobile devices, and presenting its graphical values.
It makes the process handy with the click of a button.
India, whose GDP depends on the agriculture is not a developed nation in terms of modernization in agriculture. The high cost of labor, uncertainty in the production of crops, lack of knowledge about new methods, continuing with the same orthodox and traditional means to go about agriculture, the inefficient use of proper irrigational facilities results in low productivity. Due to this uncertainty in the irrigation process the crops may also dry up. About 14.7% of India’s growth depends on the agricultural sector, so it’s a huge cause of concern.
With this project, the current problems related to farming are solved and practically implemented solutions are provided. Using IOT as well as GSM, a whole new concept of farming using networks is introduced reducing labor, updating farmer about the live conditions of farm on the mobile devices and presenting its graphical value using thing speak. It makes the process handy with the click a button reformation.
We evaluate the performance of our method in a simple temperature sensing application. In terms of reducing human efforts and ease of irrigation, our approach has been observed to outperform the existing conventional approach. We bring out the advantages and disadvantages followed by their applications. The paper concludes the work open for research.
IoT for Smart Agriculture and Villages Vinay Solanki
Leverage IoT and M2M to make our villages and farming sector smarter and more efficient and productive. I talk about how we can use connected solutions to help rural population to become more efficient and productive
Internet of Things & Its application in Smart AgricultureMohammad Zakriya
As we know Agriculture plays vital role in the development of agricultural country. In India about 70% of population depends upon farming and one third of the nation’s capital comes from farming. Issues concerning agriculture have been always hindering the development of the country. The only solution to this problem is smart agriculture by modernizing the current traditional methods of agriculture. Hence the project aims at making agriculture smart using automation and IoT technologies.
By applying IoT to agriculture it is easy to observe and interact with physical world. Synergizing Internet of Things and Cloud Computing can help the farmers to share useful information regarding cultivation on social networks, and also helps in ensuring global food and farming security
Indian agriculture: Mechanization to DigitizationICRISAT
India is characterized by small farm holdings. More than 80% of the land holdings are less than 2 ha (5 acres). About 55% of India’s population is engaged in Agriculture with 40% farm mechanization. Due to non-remunerative nature of farming, more than 50% farmers in India are in debt. This situation has constrained farmers from investing in mechanization and other technologies.
-> ICRISAT Director General Dr David Bergvinson's presentation at the CII Agri business and Mechanization Summit held in New Delhi, India on 01 Sep 2015.
How can Big Data, the Internet of Things and sensors support agricultural innovation? How open data and hackathons are helping to fulfill the potential of data and technology for food and agriculture, building new business models and revenue streams..
Why apply IoT in agriculture? Special aspects to consider for
IoT in agriculture. IoT application in this field.
More information on our website: http://aggregate.tibbo.com/industries/agriculture.html
The presentation is on Digital Agriculture and Its Application in Agriculture. The presentation went through problems of Agriculture, potential ways to cater those problems and how use of technology and their uses sustain the life of agriculture for our future generations with few case studies. I hope this is useful to student community. For PPT mail me at #pavankalyan6898@gmail.com , thank You
Using IoT as well as GSM, a whole new concept of farming using networks is introduced reducing labor, updating farmers about the live conditions of farms on mobile devices, and presenting its graphical values.
It makes the process handy with the click of a button.
India, whose GDP depends on the agriculture is not a developed nation in terms of modernization in agriculture. The high cost of labor, uncertainty in the production of crops, lack of knowledge about new methods, continuing with the same orthodox and traditional means to go about agriculture, the inefficient use of proper irrigational facilities results in low productivity. Due to this uncertainty in the irrigation process the crops may also dry up. About 14.7% of India’s growth depends on the agricultural sector, so it’s a huge cause of concern.
With this project, the current problems related to farming are solved and practically implemented solutions are provided. Using IOT as well as GSM, a whole new concept of farming using networks is introduced reducing labor, updating farmer about the live conditions of farm on the mobile devices and presenting its graphical value using thing speak. It makes the process handy with the click a button reformation.
We evaluate the performance of our method in a simple temperature sensing application. In terms of reducing human efforts and ease of irrigation, our approach has been observed to outperform the existing conventional approach. We bring out the advantages and disadvantages followed by their applications. The paper concludes the work open for research.
IoT for Smart Agriculture and Villages Vinay Solanki
Leverage IoT and M2M to make our villages and farming sector smarter and more efficient and productive. I talk about how we can use connected solutions to help rural population to become more efficient and productive
Internet of Things & Its application in Smart AgricultureMohammad Zakriya
As we know Agriculture plays vital role in the development of agricultural country. In India about 70% of population depends upon farming and one third of the nation’s capital comes from farming. Issues concerning agriculture have been always hindering the development of the country. The only solution to this problem is smart agriculture by modernizing the current traditional methods of agriculture. Hence the project aims at making agriculture smart using automation and IoT technologies.
By applying IoT to agriculture it is easy to observe and interact with physical world. Synergizing Internet of Things and Cloud Computing can help the farmers to share useful information regarding cultivation on social networks, and also helps in ensuring global food and farming security
Indian agriculture: Mechanization to DigitizationICRISAT
India is characterized by small farm holdings. More than 80% of the land holdings are less than 2 ha (5 acres). About 55% of India’s population is engaged in Agriculture with 40% farm mechanization. Due to non-remunerative nature of farming, more than 50% farmers in India are in debt. This situation has constrained farmers from investing in mechanization and other technologies.
-> ICRISAT Director General Dr David Bergvinson's presentation at the CII Agri business and Mechanization Summit held in New Delhi, India on 01 Sep 2015.
How can Big Data, the Internet of Things and sensors support agricultural innovation? How open data and hackathons are helping to fulfill the potential of data and technology for food and agriculture, building new business models and revenue streams..
Contains information about use of different ICT tools in Indian agriculture. Also contains information about challenges in application of ICT in Agriculture sector and way forward to resolve the issues
Presentation by Sander Muilerman, International Institute of Tropical Agriculture
Session: TechTalk for Agriculture
on 7 Nov 2013
ICT4Ag, Kigali, Rwanda
APPLICATION OF INFORMATION AND COMMUNICATION TOOLS (ICTs) IN MODERN AGRICULTURESREENIVASAREDDY KADAPA
ICT can deliver fast, reliable, and accurate information in a user-friendly manner for practical utilization by the end-user. ICT includes any communication device or application encompassing radio, television, cellular phones, computer and network hardware and software, satellite systems, and as well as the various services and applications associated with them, such as videoconferencing and digital learning.
[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.
Using Big Data Analytics in the Field of Agriculture A Surveyijtsrd
Big data science plays a major role in the current generation deals with the betterment of agriculture field mainly because of the population growth and climate change importance of big data is increased. Big data include the advanced analytical tools. Big data include the advanced analytical chain. Farming is undergoing a digital revolution. Smart farming is depending by the phenomenon of big data. In the field where the cereals and crop seedling growth as well as status and trends of their growth is estimated. Big data is essentially used a global crop growth monitoring system based on remote sensing is dependent on big data science. Big data analytical is a data driven technology useful in generating significant productivity improvement in various industries by collecting, storing, managing, processing, and analysing various kind of structure and unstructured data. The role of big data in agriculture provide an opportunity to increase economic gain of the formers. Gagana H. S | Arpitha H. M | Gouthami H. S "Using Big Data Analytics in the Field of Agriculture: A Survey" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-4 , June 2020, URL: https://www.ijtsrd.com/papers/ijtsrd31015.pdf Paper Url :https://www.ijtsrd.com/computer-science/other/31015/using-big-data-analytics-in-the-field-of-agriculture-a-survey/gagana-h-s
The Internet of Things for Food - An integrated socio-economic and technologi...Sjaak Wolfert
The domain of agri-food is increasingly being digitized through the introduction of all kind of smart devices and software: the Internet of Things (IoT). I distinguish 4 application areas in which IoT and the digital transformation is expected to bring big changes and where data will play an increasingly larger role:
1. Digital data is becoming more important for decision-making for actors at any level of the agri-food supply chain: from farmers, through logistic providers to consumers.
2. The same data is essential for food integrity, providing assurance to consumers and other stakeholders about safety, authenticity and quality of food.
3. Public decision-making for societal challenges such as food security, climate change, healthy food and nutrition could also tap into these data instead of using separate censuses and statistics which are usually lagging behind.
4. Finally, this digitization is driven by fast developments in science and technology (S&T), such as Artificial Intelligence, Internet of Things, Blockchain, etc. At the same time, advancements in data science also heavily rely on the data that is being generated by the application of data-driven research; simply put: no big data analytics without big data.
Now it could be expected that this is purely a technological development. However, I will show how the organisational development is equally important, coining an integrated, multi-disciplinary approach. The heart of this approach is formed by use cases in which digital solutions are designed, tested & implemented and evaluated in a real-life environment, following a cyclic, iterative development path. It is supported by (i) data science and information management, (ii) business modelling, governance & ethics and (iii) ecosystem development. The approach will be demonstrated by an existing example from the wine sector.
key note on Big Data in Horticulture, for Vineland Research and Innovation, November, Ontario Canada. (overlaps considerably with the earlier presentation for USDA NIFA in Chicago)
Menceritakan problematika syiar Islam di dunia digital. Pembuatan https://bandongan.co untuk pembelajaran terstruktur ala MOOC (coursera, udemy, dll).
Aplikasi fatwa digital https://tanyakiai.id dan juga media analisis https://xplore.pustakadata.id
Menempuh studi lanjut dan macam beasiswa yang bisa digunakan. Baik berasal dari dalam dan LN.
Disampaikan dalam workshop madrasah aliyah Ali Maksum, Yogyakarta
Generative AI : Disrupsi dan Antisipasi di Perguruan TinggiWidy Widyawan
Memaparkan sejarah AI dan NLP. Aplikasi generative AI di bidang bahasa, contohnya ChatGPT dan Bard.
Peluang dan tantangan (bias, inaccuracy, plagiarism dll) dan bagaimana PT menyikapinya.
Kecerdasan Buatan: Dampak Positif dan Antisipasi PenyalahgunaanWidy Widyawan
Menerangkan ttg kecerdasaan buatan, sejarah, jenis2 AI. Termasuk generatif AI dan AGI.
Manfaat dan potensi penyalah gunaan. Apakah AI itu seperti tools/teknologi lainnya (contoh: pisau, mobil) yang sering dipandang sebagai netral.
Disampaikan dalam forum smart city di Gunung Kidul, Yogyakarta
Regsosek, registrasi sosial ekonomi, merupan sensus penduduk Indonesia, berbasis rumah tangga, untuk mengetahui kondisi sosial ekonomi. Digunakan untuk pemetaan tingkat kemiskinan dan juga basis bagi program bantuan
Explore possibilities of using big data in Indonesian Parliament, especially in legislation.
Regulation that need to be crated in order to endorse more data transparency between gov. agency and parliament, as well as public
Pendekatan untuk riset big data di bidang sosial dan politik:
1. Data governance dan privacy
2. Media Analysis
3. Social Network Analysis
4. Complex System Analysis
Sosial media, disinformasi dan polarisasiWidy Widyawan
Menjelaskan fenomena sosial media di Indonesia. Aspek positif: network economy, memfasilitasi pergerakan sosial dll. Aspek negatif: disinformasi (fake news/hoax) dan polarisasi.
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
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
5. Background
• From precession agriculture to smart farming
• Smart farming important to answer productivity, environmental
impact, food security and sustainability
• Complex, multivariate and unpredictable agricultural ecosystem need
to be better understand and analysed
• Need large-scale collection, pre-processing, modelling
6.
7.
8. Big Data source
Data Source Availability Veracity
Sensor Closed Medium - High
Administrative Database Closed Medium - High
App Database Closed Medium - High
Social Media Open Low - Medium
Online news Open Medium
• Sensor: Agriculture sensor, GPS, Cellular Network, CCTV, WiFi, IoT
• Admin/Transactional Database: Gov. Enterprise System, Marketplace, etc
• App Database: TaniHub, Desa App, etc
• Social Media: Twitter, Facebook, IG, etc
• Online news: detik.com, kompas.com, cnn.com, etc
10. current analytic technology
data decision action
descriptive
what happened?
diagnostic
why did it happen?
predictive
What will happen?
prescriptive
what should I do?
machine human human still doing
most of the process
Analyze
• Descriptive
• Predictive
• Prescriptive
11. descriptive analytics is still the most successful
http://meetings2.informs.org/analytics2013/execforum.html
15. Farmer Decision Making
• an assessment framework that empowers brands, retailers, suppliers and
farmers at every stage in their sustainability journey, to measure the
environmental impacts of commodity crop production and identify
opportunities for continuous improvement.
The Fieldprint® Platform https://fieldtomarket.org/
20. Mobile Phone Data for population movement between
regions
Mobile Data for Tourism, Migration, Population and Transport in Korea, 6th International Conference on Big Data for Official Statistics, 31 August-2 Sept, 2020