Application of computer in agriculture pdf. (PDF) The Use of Computers in Agriculture: A Key to Improved Agricultural Productivity in the 21 st Century: A Review 2022-11-17
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The application of computers in agriculture has revolutionized the way farmers cultivate and harvest crops, manage livestock, and make decisions about their farms. With the help of computers, farmers can now collect and analyze large amounts of data, use precision farming techniques to optimize crop yields, and make more informed decisions about their operations.
One key application of computers in agriculture is precision farming, which involves the use of GPS technology and sensors to gather data about various aspects of the farm, such as soil moisture, nutrient levels, and crop growth. This data can then be used to make precise and accurate decisions about irrigation, fertilization, and pest management. For example, farmers can use precision farming techniques to determine the precise amount of water and nutrients each plant needs, and apply these resources only where they are needed, reducing waste and improving crop yields.
Another important application of computers in agriculture is the use of sensors and monitoring systems to monitor the health and well-being of livestock. These systems can track the movements and vital signs of animals, alerting farmers to any potential health issues, and allowing them to take early preventive action. This can help to reduce the spread of disease, improve animal welfare, and increase the efficiency of livestock production.
Computers are also used to manage and analyze large amounts of data about the farm, including financial records, production data, and market trends. This can help farmers to make better-informed decisions about their operations, and to optimize their use of resources. For example, farmers can use data analytics to identify trends and patterns in their production data, and to identify opportunities for improvement.
In addition to these applications, computers are also used in other areas of agriculture, such as the development of new crop varieties and the design of agricultural machinery. For example, computer-aided design (CAD) software is frequently used to design and optimize the performance of tractors, harvesters, and other farm machinery.
Overall, the application of computers in agriculture has had a profound impact on the way farmers operate and manage their farms. With the help of computers, farmers can make more informed and efficient decisions about their operations, optimize their use of resources, and improve the productivity and sustainability of their farms.
The Best Applications of Computer Vision in Agriculture (2022)
Computer Vision systems monitor animals such as cattle, sheep, pigs, or others with cameras. Technology has changed the concept of farming thus making it more profitable, efficient, safer and simple. Fish Farming With Computer Vision Automatic fish detection with computer vision is an important tool in precision farming for achieving automatic fish detection. We demonstrate different machine learning techniques like Decision Tree Ensemble, Random Forest, Support Vector Machine used in agricultural fields. Internet Forums, Social Networking and Online Knowledge Bases Any business in the world that you can think of, has benefited from the advent and global reach of the Internet and related communication technologies mobile computing, e-commerce etc. Our team is working to provide more information.
In poultry farms, computer vision technology aims to prevent diseases and ensure food security while enhancing overall productivity by lowering costs and providing information to increase product quality. It does not store any personal data. The idea in this area of work is to develop feed formulas for livestock and poultry that meet the nutrient requirements of the animal utilizing available feeds in such a manner that the cost of the final product is a minimum. The computer never forgets these locations. It allows the website owner to implement or change the website's content in real-time.
Application of Computer Vision Technology in Agricultural Field
To improve the efficiency of agriculture and reduce the cost we use the concept of Machine learning. . Our team is working to provide more information. In human operated Weeder, muscle power is required and so it cannot be operated for long time. Also included is a discussion of the computer software and hardware used in agriculture today, hardware and software purchasing strategies for both individuals and institutions, and sources of information on computer applications in agriculture. Our team is working to provide more information. Considered are specific ways microcomputers are changing agriculture, the exact nature of these changes, and how agriculturists are currently adapting microprocessor technology to make agriculture more efficient and viable.
Today, computer vision has been widely used in poultry production systems. This paper explores the potential of the new information and communications technologies to improve the access to agrometeorological information. For instance, a farmer can easily seek out and connect with an agricultural entrepreneur and begin the exchange of ideas or business proposals. From records of this nature, he can select the superior breeding stock to carry on the next generation. This technique can also help in harvesting where it can inform the farmer regarding where each batch of crops in terms of harvesting status which will result in decrease in wastage of resources by constantly monitoring and responding the data to the machine learning algorithm, which in turn will organise the data and inform the farmer regarding the status of the crops. The computer will eventually become as close to every day life as the telephone - a sort of public utility of information. In addition, 85%, 75%, 60%, 55%, and 50% of the respondents have clear understanding of the statistical concepts such as variance, probability, sampling and sampling procedures, ogive curve and normal distributions respectively.
(PDF/Books) Computer Applications In Agriculture Download FULL
The authors define agriculture in the broadest possible terms, including the traditional aspects of farming, the industries supporting agriculture, service bureaus related to agriculture, classroom instruction and youth development, and the rural family and community. It has given new horizons to the fields of science and medicine, changed the techniques of education and improved the efficiency of Government. Featuring 23 peer-reviewed papers, it discusses topics such as the use of metaheuristic for non-deterministic problem solutions, software architectures for supporting e-government initiatives, and the use of electronics in e-learning and industrial environments. Yield Estimation With Fruit or Vegetable Counting Yield estimation is an essential preharvest practice among most large-scale farming companies. The key innovation is to use different machine learning techniques and algorithms to minimize the labour cost, improve quality of crops, increase quantity of crops and maximum profit.
(DOC) STATISTICS AND ITS APPLICATIONS IN AGRICULTURE
This article reviewed the use of computer in agriculture as key to improved agricultural productivity in the 21 st century. The Internet will play an important role in the collection and transfer of information. Procedures on evaluating the impact of agrometeorological information are provided. Modern agriculture is driven by the continuous improvements using the digital tools and data which has increased the processes involved in agriculture. In this system, we are using machine learning techniques which help to suggest the crops according to soil classification or soil series.
(PDF) The Use of Computers in Agriculture: A Key to Improved Agricultural Productivity in the 21 st Century: A Review
There are different soil kinds and each kind has different features for different crops. The facts are relayed to the memory unit via electronic impulses that store the numerically defined fact in several metal rings. The computer receives its information, called input, from magnetic disks, magnetic tapes, punched cards or typewriter-like keyboards that feed the memory unit. Programs of this nature will accelerate the improvement of a breed. The information produced in present-day horticultural tasks is given by a wide range of sensors that empower a superior comprehension of the operational condition an association of dynamic harvest, soil, and climate conditions and the activity itself apparatus information , prompting increasingly precise and quicker basic leadership. The rapidly growing population will lead to gradual reduction in the cultivated land and this will increase the productivity pressures on agriculture.
This type of information brings together in an accurate and clear manner the financial pictures of any type of farm enterprise. If computers have changed the ways of farming, then the Internet has only doubled that pace of change. Automated tractors are probably not far away. These records are forwarded to a computer centre, processed, and a monthly statement is returned to the dairy farmers in three or four days. The book emphasizes the quantitative dynamic relationships between elements and system responses. From reducing production costs with intelligent automation to boosting productivity, computer vision has massive potential to enhance the overall functioning of the agricultural sector. About 90% of the respondents also enjoy solving statistical problems and understood the concept of mean deviation.
They didn't think about the humidity, level of water and especially climate condition which terrible a farmer increasingly. Computers free the research worker from this boredom and allow him time to think and formulate ways of putting the newly found information into practice to the benefit of the agricultural industry. The traditional agricultural methods should now be equipped with the digital technologies and efforts have to made to make the processes involved in the agriculture some simpler and productive. This makes it possible to implement deep face recognition in multiple remote farms. In addition, there are several learning repositories serving as knowledge bases to provide information on a wide variety of agricultural topics. The main objective of the Action is the evaluation of possible impacts arising from climate change and variability on agriculture and the assessment of critical thresholds for various European areas. Information has value when it is disseminated in such a way that the end-users get the maximum benefit in applying its content.