Enabling Precision Agriculture Through Embedded Sensing With Artificial Intelligence

AbstractIn the recent years, robotic systems became more advanced and more accessible. This has led to their slow, but stable integration and use in different processes and applications, including in the agricultural domain. Nowadays, agricultural robots are developed with the aim to replace the human labour in the otherwise exhausting, time-consuming or dangerous activities. Agricultural robotic systems provide many advantages, which can differ based on the type of the robot and its sensors, actuators and communication systems. This paper presents the design, the construction process, the main characteristics and the evaluation of a prototype of a small-scale agricultural robot that can be used for some of the simplest activities in agricultural enterprises. The robot is designed as an end-user autonomous mobile system, which is capable of self-localization and can map or inspect a specific farming area. The decision-making capabilities of the robot are based on artificial intelligence (AI) algorithms, which allow it to perform specific actions in accordance to the situation and the surrounding environment. The presented prototype is in its early development and evaluation stages and the paper concludes with discussions on the possible further improvements of the platform.

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Performance Evaluation of Artificial Intelligence on Soil Property Detection

SMART MOVES JOURNAL IJOSCIENCE ◽

10.24113/ijoscience.v4i10.166 ◽

2018 ◽

Vol 4 (10) ◽

pp. 5

Author(s):

Smriti Singhatiya ◽

Dr. Shivnath Ghosh

Keyword(s):

Artificial Intelligence ◽

Precision Agriculture ◽

Crop Production ◽

Nutrient Status ◽

Soil Testing ◽

Support Vector ◽

Soil Test ◽

New Era ◽

Agriculture Soil ◽

Historical Role

Now-a-days there is a need to study the nutrient status in lower horizons of the soil. Soil testing has played historical role in evaluating soil fertility maintenance and in sustainable agriculture. Soil testing shall also play its crucial role in precision agriculture. At present there is a need to develop basic inventory as per soil test basis and necessary information has to be built into the system for translating the results of soil test to achieve the crop production goal in new era. To achieve this goal artificial intelligence approach is used for predicting the soil properties. In this paper for analysing these properties support vector regression (SVR), ensembled regression (ER) and neural network (NN) are used. The performance is evaluated with respect to MSE and RMSE and it is observed that ER outperforms better with respect to SVR and NN.

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Applications of Artificial Intelligence for Precision Agriculture

EDIS ◽

10.32473/edis-ae529-2018 ◽

2018 ◽

Vol 2018 (6) ◽

Author(s):

Yiannis Ampatzidis

Keyword(s):

Artificial Intelligence ◽

Machine Learning ◽

Remote Sensing ◽

Computer Vision ◽

Precision Agriculture ◽

Agricultural Systems ◽

Disease Identification ◽

Technological Advances

Technological advances in computer vision, mechatronics, artificial intelligence and machine learning have enabled the development and implementation of remote sensing technologies for plant/weed/pest/disease identification and management. They provide a unique opportunity for developing intelligent agricultural systems for precision applications. Herein, the Artificial Intelligence (AI) and Machine Learning concepts are described, and several examples are presented to demonstrate the application of the AI in agriculture. Available on EDIS at: https://edis.ifas.ufl.edu/ae529

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Agriculture in the Fourth Industrial Revolution

Annals of Bangladesh Agriculture ◽

10.3329/aba.v23i2.50060 ◽

2019 ◽

Vol 23 (2) ◽

pp. 115-122

Author(s):

T Ane ◽

S Yasmin

Keyword(s):

Artificial Intelligence ◽

Precision Agriculture ◽

Industrial Revolution ◽

Insect Pests ◽

Fourth Industrial Revolution ◽

Level Data ◽

Smart Farming ◽

Real Time Information ◽

Time Information ◽

Crop Health

Agriculture and industry are tied up and both are complementary to each other. The fourth industrial revolution is an advanced digital technology, it focuses an opportunity that could change the environment in the way human think and work. The farms and factories must implement smart technology to move very fast and it should be an innovative applications to embrace the fourth industrial revolution robustly for Bangladesh. The fourth industrial revolution concept combines artificial intelligence and big data that have achieved significant attention and popularity in precision farming like in monitoring, diagnosing insect pests, measuring soil moisture, diagnosing harvest time and monitoring crop health status and reducing complicated monitoring by human. Industry that extend precision agriculture using artificial intelligence with robotic technology in fourth industrial revolution and its application is embedding into smart observation that retrieve real-time information from field level data with minor human interference. The fourth industrial revolution builds a smart farming technology which brings advanced and sustainable changes for both production and agroprocessing. The fourth industrial revolution extends farms production and also increase their value. This paper reviewed the past effects of industrial revolution, discussed expanded benefit into smart farming and predicted impacts of fourth industrial revolution in Bangladesh agriculture. Ann. Bangladesh Agric. (2019) 23(2) : 115-122

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Digitalization of Technological Processes of Crop Production in Russia

Agricultural machinery and technologies ◽

10.22314/2073-7599-2018-13-1-14-20 ◽

2019 ◽

Vol 13 (1) ◽

pp. 14-20 ◽

Cited By ~ 2

Author(s):

V. M. Korotchenya ◽

G. I. Lichman ◽

I. G. Smirnov

Keyword(s):

Artificial Intelligence ◽

Internet Of Things ◽

Precision Agriculture ◽

Crop Production ◽

Agricultural Sector ◽

Integral Approach ◽

The Internet ◽

Digital Agriculture ◽

The Internet Of Things ◽

And Robotics

Currently, the influence of program documents on digital agriculture development is rather great in our country. Within the framework of the European Association of Agricultural Mechanical Engineering, a relevant definition of agriculture 4.0 has been elaborated and introduced.Research purpose: offering general recommendations on the digitalization of agriculture in RussiaMaterials and methods. The authors make use of the normative approach: the core of digital agriculture is compared with the current state of the agricultural sector in Russia.Results and discussion. The analysis has found that digital agriculture (agriculture 4.0 and 5.0) is based on developed mechanized technologies (agriculture 2.0), precision agriculture technologies (agriculture 3.0), the use of such digital technologies and technical means as the Internet of things, artificial intelligence, and robotics. The success of introducing digital agriculture depends on the success of all the three levels of the system. However, the problem of the lack of agricultural machinery indicates insufficient development of mechanized technologies; poor implementation of precision agriculture technologies means the lack of experience of using these technologies by the majority of farms in our country; an insufficient number of leading Russian IT companies (such as Amazon, Apple, Google, IBM, Intel, Microsoft etc.) weakens the country’s capacity in making a breakthrough in the development of the Internet of things, artificial intelligence, and robotics.Conclusions.The authors have identified the need to form scientific approaches to the digitization of technological operations used in the cultivation of agricultural crops and classified precision agriculture technologies. They have underlined that the digitization of agricultural production in Russia must be carried out along with intensified mechanization (energy saturation); also, to introduce technologies of precision agriculture and digital agriculture, it is necessary to organize state-funded centers for training farmers in the use of these technologies. Finally, it is necessary to take measures to strengthen the development of the IT sphere, as well as formulate an integral approach to the problem of digitalization.

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Precision Agriculture Technology: A Literature Review

Asian Journal of Advanced Research and Reports ◽

10.9734/ajarr/2020/v14i330335 ◽

2020 ◽

pp. 30-34

Author(s):

C. A. Danbaki ◽

N. C. Onyemachi ◽

D. S. M. Gado ◽

G. S. Mohammed ◽

D. Agbenu ◽

...

Keyword(s):

Artificial Intelligence ◽

Image Processing ◽

Precision Agriculture ◽

State Of The Art ◽

Irrigation Management ◽

Conventional Farming ◽

Livestock Farming ◽

Current State ◽

Art Methods ◽

Increase In Productivity

This study is a survey on state-of-the-art methods based on artificial intelligence and image processing for precision agriculture on Crop Management, Pest and Disease Management, Soil and Irrigation Management, Livestock Farming and the challenges it presents. Precision agriculture (PA) described as applying current technologies into conventional farming methods. These methods have proved to be highly efficient, sustainable and profitable to the farmer hence boosting the economy. This study is a survey on the current state of the art methods applied to precision agriculture. The application of precision agriculture is expected to yield an increase in productivity which ultimately ends in profit to the farmer, to the society increase sustainability and also improve the economy.

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