Smart Agriculture

The agricultural information system provides its users and researches to get online information about, the crop, statistical details and new tendencies. The trends of the crops act so that these will be pretty important to the users who access these via the Internet. The main features of the

Project Title

Smart Agriculture

Project Area of Specialization

Artificial Intelligence

Project Summary

The agricultural information system provides its users and researches to get

online information about, the crop, statistical details and new tendencies. The trends of the crops act so that these will be pretty important to the users who access these via the Internet. The main features of the information system includes information retrieval facilities for users from anywhere in the form of obtaining statistical information about fertilizer, research institutes and researches, land availability, diseases, suitable soil concentration for the corresponding crops, statistical information about exports and etc. In addition this provides individual information about Intercrops related to main crops. The system allows the retrieving facilities but also the updating facilities to the authorized persons in the corresponding institutes.

New agricultural technologies are generated by research institutes, universities, private companies, and by the farmers themselves. Agricultural information and knowledge delivery services (including extension, consultancy, business development and agricultural information services) are expected to disseminate new technologies amongst their clients (people who are involving in agriculture). The role of research and advisory services is to give highly accurate, specific and unbiased technical and management information and advice in direct response to the needs of their clients. Due to poor linkages between research and advisory services, the adoption of new agricultural technologies by farmers is often very slow and research is not focusing on the actual needs of farmers.

The study is to emphasize the importance of agricultural information systems for agricultural development and to identify the strength and weaknesses of the current systems and led to recommendations for improving their performance. This review paper presents initially the definitions and models related for agricultural information system. Then it describes the analysis of agricultural information systems. Thirdly, the findings of the related previous studies are reviewed. Finally, the general conclusions about agricultural information systems are emphasized and implications for better agriculture information systems are suggested.

In addition, recent experiences show that, the human components of the system such as researchers, educators, extension and farmers are not connected together in information flow. However, there have been limited studies about the agricultural information systems. Thus, there is a need for substantial information about these issues, including the mechanisms of the information systems, interactions between components in the system, and their activity.

Project Objectives

Main objective of smart agriculture is  to increasing control over production

anomalies in crop growth or livestock health, for instance, helps eliminate the

 risk of losing yields. Additionally, automation boosts efficiency.

It aims to tackle three main objectives: sustainably increasing agricultural productivity and incomes; adapting and building resilience to climate change; and reducing and/or removing greenhouse gas emissions, where possible.

IoT solutions are focused on helping farmers close the supply demand gap,

by ensuring high yields, profitability, and protection of the environment. The approach of using IoT technology to ensure optimum application of

resources to achieve high crop yields and reduce operational costs is called precision agriculture.

Study established that the main objectives of farmers' groups were to:

 generate income, improve agricultural development and adopt modern technologies, address social welfare activities, reduce poverty and to access markets and good prices.

Project Implementation Method

Smart farming solutions is a system that is built for monitoring the crop field

with the help of sensors (light, humidity, temperature, soil moisture, crop

health, etc.) and automating the irrigation system. The farmers can monitor

the field conditions from anywhere.

AI systems are helping to improve the overall harvest quality and accuracy – known as precision agriculture. AI technology helps in detecting disease in plants, pests and poor nutrition of farms. AI sensors can detect and target

weeds and then decide which herbicide to apply within the region.

Prototype for a real-time crop recommendation algorithm in Python using Machine Learning and Data Analytics. The business logic in Python uses Machine Learning techniques in order to predict the most profitable crop in

the forecasted weather and soil conditions at a specified location.

The proposed system will integrate the data obtained from soil, crop

repository, weather department and by applying machine learning algorithm: Multiple Linear Regression, a prediction of most suitable crops according to current environmental conditions is made. This provides a farmer with variety

of options of crops that can be cultivated.

Agriculture implements IoT through use of robots, drones, sensors and

computer imaging integrated with analytical tools for getting insights and

monitor the farms. Placement of physical equipment on the farms monitors

and records data which is used to get insights.

IoT smart farming solutions is a system that is built for monitoring the crop

field with the help of sensors (light, humidity, temperature,

soil moisture, crop health, etc.) and automating the irrigation system.

The farmers can monitor the field conditions from anywhere.

The main area of application of robots in agriculture today is at the harvesting stage. Emerging applications of robots or drones in agriculture include weed control, cloud seeding, planting seeds, harvesting, environmental monitoring

and soil analysis.

Implemented for performing various operations on the field. This proposed wireless robot is equipped with various sensors for measuring different environmental parameters. It also includes Raspberry Pi 2 model B hardware

for executing the whole process. The main features of this novel intelligent wireless robot is that it can execute tasks such as moisture sensing, scaring birds and animals, spraying pesticides, moving forward or backward and switching ON/OFF electric motor. The robot is fitted with a wireless camera to monitor the activities in real time. The proposed wireless mobile robot has

been tested in the fields, readings have been monitored and satisfactory

results have been observed, which indicate that this system is very much

useful for smart agricultural systems.

Benefits of the Project

Smart farming systems reduce waste, improve productivity and enable management of a greater number of resources through remote sensing.

In traditional farming methods, it was a mainstay for the farmer to be out in the field, constantly monitoring the land and condition of crops. But with larger and larger farms, it has become more challenging for farmers to monitor everything everywhere. This is especially true with micro-farming, where many remote plots of land may be farmed for different crops, requiring different conditions and precise control of soil and water.

The types of precision farming systems implemented depend on the use of software for management of the business. Control systems manage sensor input, delivering remote information for supply and decision support, as well as automation of machines and equipment for taking action in response to emerging issues and production support. This is not notably different than any other "smart" business model's success criteria; a standardized approach sets forth the right use of resources for production in real time on the supply side and for meeting stringent constraints coming from the demand side. Thus, in a smart farming system, it's about managing the supply of land and, based on its condition, setting it forth in the right growing parameters -- for example, moisture, fertilizer or material content -- to provide production for the right crop that is in demand.

During production, it's about managing one's resources to improve the growing process. For example, precision farming systems concern precision seeding using automated tractors to reduce possible loss of seed and optimize spacing of plants to create the highest possible yield per acre. Another example is water, through the use of precision water delivery, such as trickle or subsurface methods, to reduce evaporation and to improve soil moisture content, delivering water only when it is needed through the use of sensors and automation.

Overall, the entire process from farm to table is software-managed and sensor-monitored, reducing overall costs, improving overall yield and quality of the supply, and ultimately the experience for the consumer.

So, Benefits include Higher crop productivity. Decreased use of water, fertilizer, and pesticides, which in turn keeps food prices down. Reduced impact on natural ecosystems.

The term smart agriculture refers to the usage of technologies like Internet of Things, sensors, location systems, robots and artificial intelligence on your farm. The ultimate goal is increasing the quality and quantity of the crops while optimizing the human labor used.

Agriculture plays a chiefly role in economy as well as it is considered to be the backbone of economic system for developing countries. For decades, agriculture has been related with the production of vital food crops. The Present era of farming contains dairy, fruit, forestry, poultry beekeeping and arbitrary.

Technical Details of Final Deliverable

Smart farming is an emerging concept that refers to managing farms using technologies like IoT, robotics, drones and AI to increase the quantity and quality of products while optimizing the human labor required by production.

The Internet of Things (IoT) has provided ways to improve nearly every industry imaginable. In agriculture, IoT has not only provided solutions to often time-consuming and tedious tasks but is totally changing the way we think about agriculture.

Smart farming refers to managing farms using modern Information and communication technologies to increase the quantity and quality of products while optimizing the human labor required.

Among the technologies available for present-day farmers are:

• Sensors: soil, water, light, humidity, temperature management
• Software: Specialized software solutions that target specific farm types or applications agnostic IoT platform
• Connectivity: cellular,LoRa
• Location: GPS, Satellite
• Robotics: Autonomous tractors, processing facilities
• Data analytics: standalone analytics solutions, data pipelines for downstream solutions
• Agriculture Drones: Agriculture is one of the major verticals to incorporate both ground-based and aerial drones for crop health assessment.

Some agriculture technologies are:

•           Soil and Water Sensors

•           Weather Tracking

•           Satellite Imaging

•           Pervasive Automation

•           Minichromosomal Technology

•           RFID Technology

•           Vertical Farming

•           Final Thoughts

Final Deliverable of the Project

HW/SW integrated system

Core Industry

Agriculture

Other Industries

Food , Energy , Health

Core Technology

Internet of Things (IoT)

Other Technologies

Artificial Intelligence(AI), Robotics

Sustainable Development Goals

Good Health and Well-Being for People, Decent Work and Economic Growth

Required Resources

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