An increase in the number of power consumers leads to scale up a power supply grids, and the introduction of Smart Grid (SG) for connecting components and subsystems of distributed generation, increases the complexity...
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This design describes in detail the design and implementation process of the intelligent environment detection system based on WiFi technology. Firstly, the present situation of environmentalmonitoring system is intr...
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The paper considers the importance of expanding the possibilities of environmentalmonitoring of environmental air parameters in the event of man-made emergencies. Software and hardware solutions have been developed f...
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A severe and pervasive environmental problem that affects the entire planet is Air Pollution (AP). Numerous researchers have focused on these issues while keeping human health in mind. One of the best methods to educa...
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This paper presents an improved intelligentcontrol model for greenhouse environments, integrating environmentalmonitoring data with a deep learning approach combining multilayer CNN and LSTM networks with model pred...
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ISBN:
(数字)9798331534622
ISBN:
(纸本)9798331534639
This paper presents an improved intelligentcontrol model for greenhouse environments, integrating environmentalmonitoring data with a deep learning approach combining multilayer CNN and LSTM networks with model predictive control (MPC). By optimizing model parameters and utilizing data fusion techniques, the system’s prediction accuracy and response speed are enhanced. Experimental results from a real greenhouse monitoring system show that the improved model significantly outperforms traditional models and other machine learning algorithms, with a mean absolute error (MAE) of 2.342, mean square error (MSE) of 6.749, and a coefficient of determination (R 2 ) of 0.931, demonstrating its efficiency and reliability in controlling key environmental indicators like temperature, humidity, and CO 2 concentration.
To address the issues of the "Black and White Hole Effect," inadequate lighting brightness, poor air quality, and high lighting energy consumption in highway tunnels, this paper proposes the design of a tunn...
To address the issues of the "Black and White Hole Effect," inadequate lighting brightness, poor air quality, and high lighting energy consumption in highway tunnels, this paper proposes the design of a tunnel measurement and control system that utilizes photovoltaic power generation, environmental sensing, and intelligentcontrol technology. The system is based on the STM32 microcontroller and primarily consists of a photovoltaic power generation subsystem, a tunnel environmentalmonitoring subsystem, an intelligent lighting control subsystem, and a notice and alarm subsystem. The photovoltaic power generation subsystem provides power for the control system. The environmentalmonitoring subsystem and the intelligent lighting control subsystem adjust the lighting brightness and color temperature inside the tunnel to overcome the "Black and White Hole Effect." The environmentalmonitoring subsystem and the notice and alarm subsystem monitor the environmental parameters inside the tunnel and provide tunnel controlmonitoring and fire alarm functions. Experimental results show that this system can improve the safety and comfort of tunnel traffic while reducing energy consumption and environmental pollution, and has good application prospects.
Agriculture is affected by many factors such as environmental changes, natural disasters, soil erosion, water irrigation, and pesticide control. All these factors will affect the yield of the crop. The Internet of Thi...
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control algorithms are crucial for protection of civil engineering structures that are subjected to significant levels of the seismic or wind-induced vibration. intelligent adaptive control algorithms as data-driven m...
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This article used OpenCV (Open Source computer Vision Library) to preprocess images, and then used positioning methods and horizontal and vertical projection methods to accurately locate the key information to be reco...
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ISBN:
(数字)9798350305463
ISBN:
(纸本)9798350305470
This article used OpenCV (Open Source computer Vision Library) to preprocess images, and then used positioning methods and horizontal and vertical projection methods to accurately locate the key information to be recognized. Then, convolutional neural networks were utilized to recognize and analyze the segmented images. Based on the characteristics of the layout and dynamic environmentalmonitoring of the computer room, the computer room equipment safety monitoring system designed in this article includes an environmentalmonitoring module, a power monitoring module, a security access controlmonitoring module, and an abnormal alarm module. The average current intensity in the sleep state was 2μA, 10 mA in the wake state, 110 mA in the send state, and 15 mA in the receive state. The computer room equipment safety monitoring system has increased the efficiency and quality of computer room operation and maintenance, improved the intelligence level of power communication room monitoring, and provided a reference for technical solutions for real-time monitoring of other power communication rooms.
This study examines how machine learning and artificial intelligence (AI) may be used to solve urgent worldwide issues with waste and energy management. It presents a thorough framework for employing AI technology to ...
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