scholarly journals Construction Method of Swimming Pool Intelligent Assisted Drowning Detection Model Based on Computer Feature Pyramid Networks

2021 ◽  
Vol 2137 (1) ◽  
pp. 012065
Author(s):  
Keshi Li
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Construction Method ◽  
Swimming Pool ◽  
Important Research ◽  
Accuracy Rate ◽  
Intelligent Monitoring ◽  
Detection Model ◽  
Underwater Environment ◽  
Feature Pyramid

Abstract Swimming pool intelligent assisted drowning detection is an important research content in the field of drowning rescue. A large number of scholars track drowning targets in real time through underwater intelligent monitoring system, and use it to build a reliable swimming pool intelligent assisted drowning detection model to reduce the risk of drowning. For the complex underwater environment of the swimming pool, the previous detection model has been difficult to adapt to the practical demand. In this regard, based on the summary of the previous swimming pool intelligent assisted drowning detection models and the computer feature pyramid networks, the feature stratification of the swimming pool intelligent assisted drowning detection image is completed, and then the final swimming pool intelligent assisted drowning detection results are obtained through the YOLO principle. After analysis, it is confirmed that the accuracy rate of swimming pool intelligent assisted drowning detection of this method is significantly improved, which can provide effective data theoretical guidance for swimming pool intelligent assisted drowning rescue and has significant practical advantages.

scholarly journals The Development of an Intelligent Monitoring System for Agricultural Inputs Basing on DBN-SOFTMAX

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Ling Yang ◽  
V. Sarath Babu ◽  
Juan Zou ◽  
Xu Can Cai ◽  
Ting Wu ◽  
...  
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Physicochemical Parameters ◽  
Classification Model ◽  
Long Distance ◽  
Intelligent Monitoring ◽  
Softmax Classifier ◽  
Traceability System ◽  
Communication Problems ◽  
Time Acquisition

To solve the problem of unreliability of traceability information in the traceability system, we developed an intelligent monitoring system to realize the real-time online acquisition of physicochemical parameters of the agricultural inputs and to predict the varieties of input products accurately. Firstly, self-developed monitoring equipment was used to realize real-time acquisition, format conversion and pretreatment of the physicochemical parameters of inputs, and real-time communication with the cloud platform server. In this process, LoRa technology was adopted to solve the wireless communication problems between long-distance, low-power, and multinode environments. Secondly, a deep belief network (DBN) model was used to learn unsupervised physicochemical parameters of input products and extract the input features. Finally, these input features were utilized on the softmax classifier to establish the classification model, which could accurately predict the varieties of agricultural inputs. The results showed that when six kinds of pesticides, chemical fertilizers, and other agricultural inputs were predicted through the system, the prediction accuracy could reach 98.5%. Therefore, the system can be used to monitor the varieties of agrarian inputs effectively and use in real-time to ensure the authenticity and accuracy of the traceability information.

scholarly journals Design of Intelligent Monitoring System of Chicken House Environment Based on Single-chip Microcomputer

2018 ◽  
Vol 227 ◽  
pp. 02008
Author(s):  
Qing Du ◽  
Yanhua Miao ◽  
Yunhui Zhang
Keyword(s):  
Carbon Dioxide ◽  
Light Intensity ◽  
Real Time ◽  
Monitoring System ◽  
Carbon Dioxide Concentration ◽  
Environmental Parameters ◽  
Single Chip ◽  
Single Chip Microcomputer ◽  
Intelligent Monitoring ◽  
Chicken House

In view of the problem that some chicken farms are susceptible to various bacteria and viruses due to poor breeding environment, this paper designs a chicken house environmental intelligent monitoring system based on single-chip microcomputer application to improve the chicken house environment. The system adopts STC89C52 single-chip microcomputer as the main control chip. The sensor collects information on the light intensity, temperature and humidity, and carbon dioxide concentration, and controls the exhaust fan and the illumination lamp, and the environmental parameters can be displayed on the display in real time.

Highway Toll Free Release Queue Length Quantitative Algorithm Based on 3G/4G Intelligent Monitoring System

2014 ◽  
Vol 513-517 ◽  
pp. 3699-3702
Author(s):  
Hui Min Guo ◽  
Hui Lin Su
Keyword(s):  
Computer Simulation ◽  
Real Time ◽  
Monitoring System ◽  
Queue Length ◽  
Queuing Theory ◽  
Intelligent Monitoring ◽  
Congestion Problems

In this paper, on the basis of queuing theory, a quantitative algorithm of highway toll free release length using 3G/4G intelligent monitoring system is proposed in view of congestion problems of the domestic highway toll. In the algorithm, the severity of real-time congestion is divided into three levels, each level corresponds to different queue length thresholds; The central server of monitoring system can determine the congestion level at present and give the dynamic free release queue length instructions using the algorithm; Computer simulation shows that the algorithm has certain practical guiding significance.

scholarly journals Research and Application of Intelligent Monitoring System Platform for Safety Risk and Risk Investigation in Urban Rail Transit Engineering Construction

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yong Wu ◽  
Liang-Yun Zhao ◽  
Ye-Xiang Jiang ◽  
Wei Li ◽  
Ye-Sheng Wang ◽  
...  
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Dual Control ◽  
Intelligent Monitoring ◽  
Safety Risk ◽  
Engineering Construction ◽  
The Real ◽  
Urban Rail

In recent years, the construction scale of urban rail transit project is still in a high growth stage. In addition, the geology and surrounding environment of crossing lines are complex, and all kinds of safety accidents are still in a high incidence stage. Based on the investigation and summary of safety risk events and their causes in urban rail transit engineering construction at home and abroad, this paper fully combines the current national security management policies, introduces the “dual control” concept of safety risk classification and hidden danger investigation, and develops the intelligent monitoring system platform for urban rail transit engineering construction based on advanced technologies such as intelligent Internet of Things, 3D visualization, and artificial intelligence. It realizes the intelligent collection and analysis of engineering field monitoring data, the dynamic early warning management of engineering risk sources, the process embedding “dual control” mechanism of safety risk and hidden danger investigation, the real-time supervision of large equipment operations such as shield and hoisting, and the real-time control of high-risk operation sections such as contact channels. At the same time, the traceability and assessment management of the safety supervision process are strengthened. The parties involved in the project can realize the synchronous sharing of information through the platform and improve the efficiency of on-site safety and quality control.

scholarly journals Efficient Object Detection Model for Real-time UAV Application

2021 ◽  
Vol 14 (1) ◽  
pp. 45
Author(s):  
Subrahmanyam Vaddi ◽  
Dongyoun Kim ◽  
Chandan Kumar ◽  
Shafqat Shad ◽  
Ali Jannesari
Keyword(s):  
Object Detection ◽  
Real Time ◽  
High Performance ◽  
Class Imbalance ◽  
Detection Techniques ◽  
Detection Model ◽  
Deep Feature ◽  
Proposed Model ◽  
Negative Effect ◽  
Feature Pyramid

Unmanned Aerial Vehicles (UAVs) equipped with vision capabilities have become popular in recent years. Many applications have especially been employed object detection techniques extracted from the information captured by an onboard camera. However, object detection on UAVs requires high performance, which has a negative effect on the result. In this article, we propose a deep feature pyramid architecture with a modified focal loss function, which enables it to reduce the class imbalance. Moreover, the proposed method employed an end to end object detection model running on the UAV platform for real-time application. To evaluate the proposed architecture, we combined our model with Resnet and MobileNet as a backend network, and we compared it with RetinaNet and HAL-RetinaNet. Our model produced a performance of 30.6 mAP with an inference time of 14 fps. This result shows that our proposed model outperformed RetinaNet by 6.2 mAP.

Study on the Intelligent Monitoring System for the Industrialized Producing Environment of Edible Fungus Based on the Internet of Things

2013 ◽  
Vol 427-429 ◽  
pp. 1028-1031
Author(s):  
Ling Yun Zhang ◽  
Hua Zhang ◽  
Peng Fei Zhang ◽  
Qiu Hong Yuan
Keyword(s):  
Environmental Factors ◽  
Internet Of Things ◽  
Real Time ◽  
Monitoring System ◽  
Text Messages ◽  
Added Value ◽  
The Internet ◽  
Intelligent Monitoring ◽  
Edible Fungus ◽  
The Internet Of Things

The edible fungus industry has relatively high output rate and high added value. In the production of edible fungus, the environmental factors have great impacts. This paper studies the intelligent monitoring system for producing environment of the factory-farmed edible fungus based on the internet of things and aiming at online real-time management. The monitoring system can realize real-time surveillance and visual operation during production by dynamically regulating the environmental factors needed for growing edible fungus and early warning of the environmental parameters fluctuation with traceable history records at any time. When parameters like temperature and humidity are beyond reasonable range, warning will be sent via text messages and equipments such as air conditioners and warming devices will be automatically adjusted for on and off so as to raise management level, increase the output, improve the quality and lower the risks.

Intelligent Monitoring System of Battery Based on CAN Bus

2011 ◽  
Vol 130-134 ◽  
pp. 2568-2572
Author(s):  
Yi Song Guo
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Can Bus ◽  
Bottom Layer ◽  
Measuring System ◽  
Intelligent Monitoring ◽  
The Core ◽  
On Line ◽  
Comprehensive Judgment

The intelligent monitoring system of battery with CAN bus is introduced, which is composed of two layer net, the C8051F045 controller is the core of measuring system, the bottom layer is measuring board based on intelligent battery monitor DS2438 fixed on each battery, it measures the battery parameter such as voltage, current and temperature on line, exchanges dates with C8051F045 by the single bus. The top layer is the CAN bus, by which connected the super monitoring compute and C8051F045 controllers. The system can real-time measure battery parameters remotely, forecast accurately the invalid battery according to the comprehensive judgment, and can improve the reliability of the serial battery.

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