Aerial base stations (ABSs), i.e., unmanned aerial vehicle-mounted base stations, have emerged as an essential technology to expand the coverage and capacity in next-generation wireless networks. Determining the optim...
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Recent studies have explored the integration of large language models (LLMs) into caregiving robots. The use of LLMs facilitates the generation of human-like natural dialogues and diverse, varied expressions. However,...
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Multi-robot systems (MRS) enable cooperation between multiple robots to achieve common goals or tasks. These systems can enhance efficiency and productivity in various applications, such as transportation, manufacturi...
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The early diagnosis of prostate cancer (PCa) is highly recommended, as the tumor will not spread to other organs of the body and the bones. Moreover, a late diagnosis of PCa could lower the survival rate. The growing ...
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By enabling a highly accurate examination of the chest x-ray, deep learning, for example, is changing the methods of recognizing lung disorders. In order to classify lung diseases, such as bacterial pneumonia, viral p...
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作者：
Petkar, Taniya G.Kumar, PraveenSarate, Kirtiksha U.
Faculty of Engineering and Technology Department of Computer Science & Medical Engineering Maharashtra Sawangi Wardha442001 India
Faculty of Engineering and Technology Department of Computer Science and Design Maharashtra Sawangi Wardha442001 India
By enabling precise, individualized, and effective treatments, the integration of artificial intelligence (AI) and machine learning (ML) into wound and skin healing is revolutionizing healthcare. Artificial intelligen...
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作者：
Warbhe, Mohan K.Bore, Joy JordanChaudari, Shiv Nath
Faculty of Engineering and Technology Department of Computer Science and Design Maharashtra Sawangi Wardha442001 India
Faculty of Engineering and Technology Department of Computer Science and Medical Engineering MaharashtraSawangi Wardha442001 India
The proposed web application for tomato leaf disease detection exemplifies the transformative power of Artificial Intelligence and Computer Vision in modern agriculture. Addressing the critical issue of early and accu...
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Magnesium chips were coated with a high concentration of graphite using a binder and were used as the raw material for injection molding. The microstructure of the magnesium injection-molded product with added graphit...
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Agriculture is changing into a more sustainable and productive sector as a result of the fusion of modern technologies, especially the Internet of Things (Io'T), with traditional farming methods. This shift, dubbe...
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ISBN:
(纸本)9798350379945
Agriculture is changing into a more sustainable and productive sector as a result of the fusion of modern technologies, especially the Internet of Things (Io'T), with traditional farming methods. This shift, dubbed 'Smart Agriculture,' rethinks how farmers conduct cultivation, managing resources, and sustainability by using the power of online access, data analytics, and automation. A network of linked systems and gadgets that gather, transfer, and evaluate real-time data forms the basis of smart agriculture. With previously unheard-of precision and efficiency, farmers may now remotely track and supervise a variety of aspects of their farming activities thanks to this connectivity. The transformative influence of IoT on productivity, sustainability, or precision farming highlights the need for it in agriculture. A crucial element of smart agriculture is precision farming, which entails exact management of resources like pesticides, fertilizers, and water as well as real-time data processing. This study examines the ways in which integrated geospatial technologies, weather forecasting, and IoT -driven automation and actuation support productive and sustainable farming methods. The emphasis on aquaculture monitoring also draws attention to the wide range of uses for IoT in agriculture that go beyond conventional crop growing. The crucial part that IoT plays in meeting the growing need for food production on a worldwide scale while using scarce resources. Precision farming, management of water, and crop monitoring are made possible by Internet of Things technologies including sensors, drones, or automated machinery. These apps support environmental sustainability in agriculture, improve resource efficiency, and enable data-driven decision-making. This research work goes into more detail on the fundamental components of smart agriculture, such as sensor technologies, infrastructure connectivity, automation, data transfer, acquisition, and integration with geospatial tec
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