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  • Open Access

    ARTICLE

    A Sensitive Wavebands Identification System for Smart Farming

    M. Kavitha*, M. Sujaritha

    Computer Systems Science and Engineering, Vol.43, No.1, pp. 245-257, 2022, DOI:10.32604/csse.2022.023320

    Abstract Sensing the content of macronutrients in the agricultural soil is an essential task in precision agriculture. It helps the farmers in the optimal use of fertilizers. It reduces the cost of food production and also the negative environmental impacts on atmosphere and water bodies due to indiscriminate dosage of fertilizers. The traditional chemical-based laboratory soil analysis methods do not serve the purpose as they are hardly suitable for site specific soil management. Moreover, the spectral range used in the chemical-based laboratory soil analysis may be of 350–2500 nm, which leads to redundancy and confusion. Developing sensors… More >

  • Open Access

    ARTICLE

    Design of Machine Learning Based Smart Irrigation System for Precision Agriculture

    Khalil Ibrahim Mohammad Abuzanouneh1, Fahd N. Al-Wesabi2, Amani Abdulrahman Albraikan3, Mesfer Al Duhayyim4, M. Al-Shabi5, Anwer Mustafa Hilal6, Manar Ahmed Hamza6,*, Abu Sarwar Zamani6, K. Muthulakshmi7

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 109-124, 2022, DOI:10.32604/cmc.2022.022648

    Abstract Agriculture 4.0, as the future of farming technology, comprises numerous key enabling technologies towards sustainable agriculture. The use of state-of-the-art technologies, such as the Internet of Things, transform traditional cultivation practices, like irrigation, to modern solutions of precision agriculture. To achieve effective water resource usage and automated irrigation in precision agriculture, recent technologies like machine learning (ML) can be employed. With this motivation, this paper design an IoT and ML enabled smart irrigation system (IoTML-SIS) for precision agriculture. The proposed IoTML-SIS technique allows to sense the parameters of the farmland and make appropriate decisions for… More >

  • Open Access

    ARTICLE

    An Optimal Classification Model for Rice Plant Disease Detection

    R. Sowmyalakshmi1, T. Jayasankar1,*, V. Ayyem Pillai2, Kamalraj Subramaniyan3, Irina V. Pustokhina4, Denis A. Pustokhin5, K. Shankar6

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1751-1767, 2021, DOI:10.32604/cmc.2021.016825

    Abstract Internet of Things (IoT) paves a new direction in the domain of smart farming and precision agriculture. Smart farming is an upgraded version of agriculture which is aimed at improving the cultivation practices and yield to a certain extent. In smart farming, IoT devices are linked among one another with new technologies to improve the agricultural practices. Smart farming makes use of IoT devices and contributes in effective decision making. Rice is the major food source in most of the countries. So, it becomes inevitable to detect rice plant diseases during early stages with the… More >

  • Open Access

    ARTICLE

    A Method for Planning the Routes of Harvesting Equipment using Unmanned Aerial Vehicles

    Vitaliy Mezhuyev1,*, Yurii Gunchenko2, Sergey Shvorov3, Dmitry Chyrchenko3

    Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 121-132, 2020, DOI:10.31209/2019.100000133

    Abstract The widespread distribution of precision farming systems necessitates improvements in the methods for the control of unmanned harvesting equipment (UHE). While unmanned aerial vehicles (UAVs) provide an effective solution to this problem, there are many challenges in the implementation of technology. This paper considers the problem of identifying optimal routes of UHE movement as a multicriteria evaluation problem, which can be solved by a nonlinear scheme of compromises. The proposed method uses machine learning algorithms and statistical processing of the spectral characteristics obtained from UAV digital images. Developed method minimizes the resources needed for a More >

  • Open Access

    ARTICLE

    Biofilter efficiency of Eichhornia crassipes in wastewater treatment of fish farming in Amazonia

    Rubim MAL1, PR Isolino Sampaio1, P Parolin2,3

    Phyton-International Journal of Experimental Botany, Vol.84, No.1, pp. 244-251, 2015, DOI:10.32604/phyton.2015.84.244

    Abstract Fish is a very important part of the human diet in Amazonia. Near the growing cities, fish populations and individual size have decreased over the past decades. Alternatives to traditional and industrial fishing arise, including fish farming. Strategies to minimize the impact of fish farms on the environment are needed to have a regular and healthy fish supply. This is to avoid a reduction of biodiversity, a depletion of natural resources, and/or the induction of significant changes in the structure and functioning of adjacent ecosystems. Very little research has been performed on management of effluents… More >

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