In the case of frequent extreme weather, in order to improve the accuracy of winter wheat yield forecasts. Based on the data from the internet of things, this paper takes Henan Province as the research area and calcul...
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In recent years, new energy and power businesses and new business formats have developed rapidly, and the energy and power industry is changing from traditional competition to competition among ecosystems. However, th...
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With the advent of the internet of things technology, the smart home has been redefined by the concept of "digital home". Especially under the circumstances of global epidemic, the internet of things technol...
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The quality of sleep has become a matter of concern to modern people. The medical field usually uses Electroencephalogram to detect the quality of sleep. The method in machinelearning can figure out people's slee...
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After implementing the Jaminan Kesehatan Nasional (JKN) in Indonesia, health system inequity, payment non-compliance and additional expenditure still exists. To better deal with the problems in their healthcare system...
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In order to facilitate the early detection of potential failure in fire pumps, a fire pump failure prediction system has been designed which incorporates internet of things (IoT) and machinelearning techniques. The s...
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ISBN:
(纸本)9798400710353
In order to facilitate the early detection of potential failure in fire pumps, a fire pump failure prediction system has been designed which incorporates internet of things (IoT) and machinelearning techniques. The system employs an STM32F103RCT6 microcontroller to acquire data from temperature, pressure and water flow sensors. The data is then transmitted to the internet of things (IoT) cloud platform via a Wi-Fi module, allowing for real-time monitoring of the fire pump environment. The data from the IoT cloud platform is also subjected to analysis and learning through the application of machinelearning algorithms. Three machinelearning algorithms, namely k-nearest neighbour, logistic regression and extreme gradient boosting, were employed for the purposes of modelling, training and prediction. It was determined that the accuracy, Kappa coefficient and AUC value of the XGBoost algorithm were superior to those of the other algorithms, and that it demonstrated an excellent capacity for predicting the occurrence of fire pump failure. The system is capable of meeting the real-time monitoring of fire pumps, as well as fault prediction, and of enhancing the reliability of fire pumps.
People's daily lives are getting more and more entangled with the internet as technology advances and the level of living rises. The diversity of mobile internet applications has also attracted some unscrupulous e...
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In order to improve the automation and intelligence level of monitoring systems, an algorithm optimization method based on deep learning was analyzed. The results indicate that the comprehensive application of video p...
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ISBN:
(纸本)9798400710353
In order to improve the automation and intelligence level of monitoring systems, an algorithm optimization method based on deep learning was analyzed. The results indicate that the comprehensive application of video preprocessing, object detection, object tracking, and anomaly event detection can effectively improve monitoring accuracy and response speed, demonstrating good adaptability and robustness. This provides practical guidance and broad application prospects for the development of intelligent monitoring technology.
With the gradual formation of a national digital sharing economy and the growing international concern about environmental issues in developing countries, the emergence of a new "smart environmental protection&qu...
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This paper proposes a design solution for a distributed machinelearning platform based on Apache Spark and expounds on its advantages in specific application scenarios. Through Spark's distributed computing frame...
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