Traditional farming procedures are time-consuming and expensive as based on manual labor. Farmers haveno proper knowledge to select which crop is suitable to grow according to the environmental factors and soilcharact...
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Traditional farming procedures are time-consuming and expensive as based on manual labor. Farmers haveno proper knowledge to select which crop is suitable to grow according to the environmental factors and soilcharacteristics. This is the main reason for the low yield of crops and the economic crisis in the agricultural sectorof the different countries. The use of modern technologies such as the Internet of Things (IoT), machine learning,and ensemble learning can facilitate farmers to observe different factors such as soil electrical conductivity (EC),and environmental factors like temperature to improve crop yield. These parameters play a vital role in suggestinga suitable crop to cope the food scarcity. This paper proposes a systemcomprised of twomodules, first module usesstatic data and the second module takes hybrid data collection (IoT-based real-time data and manual data) withmachine learning and ensemble learning algorithms to suggest the suitable crop in the farm to maximize the *** is used to train the model that predicts the crop. This system proposed an intelligent and low-cost solutionfor the farmers to process the data and predict the suitable *** implemented the proposed system in the *** efficiency and accuracy of the proposed system are confirmed by the generated results to predict the crop.
The installation of water distribution networks (WDNs) on farmland is a key facet of agricultural practices in India, particularly for ensuring adequate irrigation of crops, especially in the context of facility agric...
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This research investigates a transformative shift in managing placement related data within the contemporary academic landscape. A dedicated open-source Flask application, Placement-Manager, is examined for its role i...
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Pet owners often face challenges in ensuring their pet's well-being, such as receiving timely advice on health and behavior and managing complex tasks like medication schedules and grooming appointments. The lack ...
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The application of big data analytics to improve energy usage efficiency in smart grids has been prompted by the rising need for power management. Adding to the above, it poses a big data solution for demand predictio...
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The proposed models can design the airfoil by Cuckoo search with Levenberg-Marquardt. The Neural Network framework has impediments due to over-fitting. This paper proposed a modified cuckoo search. here the aerodynami...
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The U.S. National science Foundation (NSF) celebrated the 20th anniversary of its research funding programs in cybersecurity, and more generally, secure and trustworthy computing, with a panel session at its conferenc...
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Breast cancer continues to be a significant global health issue that greatly affects the well-being of people worldwide. Detecting breast cancer early is vital for improving the outcomes of patients. One promising met...
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This survey covers the new trend of privacy-preserving communication frameworks in machine learning in the FL, DP and SMPC for cyber threat detection domains. The specific research performed between the year of 2020 a...
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Handwritten Character Recognition (HCR) is a critical area of research within pattern recognition and artificial intelligence, with applications spanning from document digitization, optical character recognition (OCR)...
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