mobile sensor
Recently Published Documents


TOTAL DOCUMENTS

1734
(FIVE YEARS 231)

H-INDEX

50
(FIVE YEARS 5)

2022 ◽  
Vol 2022 ◽  
pp. 1-13
Author(s):  
Yucong You

With the continuous development of regional economy, the difference of regional economy has also aroused the attention of all walks of life. Due to the limitations of the traditional research methods, the research results are relatively simple and unable to conduct a more comprehensive analysis. The traditional methods include the following: (1) analyze the evolution of regional logistics based on the location Gini coefficient and location quotient of GIS, and reflect the situation of industrial agglomeration from the annual change curve of the location Gini coefficient; (2) use SPSS12.0 software to perform multivariate or event factors, and analyze and calculate the factor score to sum up several principal component factors; and (3) the production function analysis method is used to measure the economies of scale and agglomeration. As an extension, the relationship between the estimated total output and the agglomeration index of the factor input to measure the uniform state of the industrial distribution department is an effective measurement method for the agglomeration economy. In order to promote the sustainable development of regional economy, this paper analyzes the regional economy comprehensively based on the emerging mobile sensor network technology and data mining technology. Firstly, this paper analyzes the location technology of mobile sensor networks based on sequential Monte Carlo, selects the C -means clustering method which is suitable for economic large-sample clustering analysis, and constructs a complete data mining model. Then, the model is used to analyze the economic, social, natural, and educational science and technology indicators of a certain region from 2015 to 2019. The results show that the first principal component weight of economic indicators is the highest proportion of fiscal revenue, which is 0.986. This shows that the role of fiscal revenue in economic indicators is greater. The main index of urban consumption is 72.0, which is the highest. This shows that the population growth rate and the average consumption of urban households in social indicators play a greater role. The first principal component of natural index has the highest weight of pollution emission, which is 0.47, while the second principal component has the highest weight of total energy consumption, which is 0.48. This shows that the pollution emissions and total energy consumption in the natural indicators play a greater role. In the educational science and technology index, the first principal component weight is the highest, which is 0.61. This shows that the education funds play an important role in educational science and technology indicators. Therefore, the data mining model based on mobile sensor network technology can comprehensively and accurately analyze various indicators of regional economy.


Solar Energy ◽  
2022 ◽  
Author(s):  
José M. Aguilar-López ◽  
Ramón A. García ◽  
Adolfo J. Sánchez ◽  
Antonio J. Gallego ◽  
Eduardo F. Camacho

2021 ◽  
Author(s):  
Pritam Goswami ◽  
Sangita Patra ◽  
Buddhadeb Sau

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 7867
Author(s):  
Yanjie Guo ◽  
Zhaoyi Xu ◽  
Joseph Saleh

In this study, a novel collaborative method is developed to optimize hybrid sensor networks (HSN) for environmental monitoring and anomaly search tasks. A weighted Gaussian coverage method hs been designed for static sensor allocation, and the Active Monitoring and Anomaly Search System method is adapted to mobile sensor path planning. To validate the network performance, a simulation environment has been developed for fire search and detection with dynamic temperature field and non-uniform fire probability distribution. The performance metrics adopted are the detection time lag, source localization uncertainty, and state estimation error. Computational experiments are conducted to evaluate the performance of HSNs. The results demonstrate that the optimal collaborative deployment strategy allocates static sensors at high-risk locations and directs mobile sensors to patrol the remaining low-risk areas. The results also identify the conditions under which HSNs significantly outperform either only static or only mobile sensor networks in terms of the monitoring performance metrics.


2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Runping Zhang ◽  
Xue Hong

With the development of signal processing technology and the appearance of small, low-cost, and low-power microprocessors, mobile sensor networks have begun to emerge in large numbers. In view of the different exercise abilities of different body components, mobile network sensor technology is used to monitor various data. Lean body mass is positively correlated with physical strength, aerobic capacity, and maximum oxygen uptake and is the main factor affecting explosive power, speed, and endurance. This article mainly studies the effect of nutritional supplementation in sports on physical strength. The subjects in this article are 10 male physical athletes. Three solid sports drinks with different nutrient composition ratios were selected from the national team’s nutrition centralized procurement product list, and a placebo with sugar-free sweetener and purified water was used as a control group. The test measures the maximum oxygen uptake to determine the exercise intensity during the formal exercise test. Each stage includes exercise test day and washout period. Eat on the test day and provide a one-hour static rest after a unified breakfast, and then, perform a 1-hour power bicycle riding after the rest. During 0, 15, 30, and 45 minutes of exercise, drink the designated solution at 1.8 mL/kg body weight and record it as the corresponding solution group. Within 30 minutes immediately after the end of the cycling exercise, fluids should be refilled at 10 mL/kg of body weight. Experimental data showed that the levels of lactic acid in each group increased significantly after exercise compared to those at rest ( P < 0.05 ), and there was no difference between the groups. There was no significant difference in the duration of the exercise ability test between the sports drink group and the placebo group. The experiment in this article shows that athletes can take appropriate measures to improve athletes’ physical activity level, increase daily energy consumption and a reasonable and balanced diet, which can effectively reduce the athlete’s body fat percentage, improve, and maintain a reasonable body composition. Among all the monitoring actions, the monitoring results indicate that the evaluation value of the action of combat is the highest, reaching 8.7.


2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Wei-Min Zheng ◽  
Ning Liu ◽  
Qing-Wei Chai ◽  
Shu-Chuan Chu

The mobile sensor network can sense and collect the data information of the monitored object in real time in the monitoring area. However, the collected information is meaningful only if the location of the node is known. This paper mainly optimizes the Monte Carlo Localization (MCL) in mobile sensor positioning technology. In recent years, the rapid development of heuristic algorithms has provided solutions to many complex problems. This paper combines the compact strategy into the adaptive particle swarm algorithm and proposes a compact adaptive particle swarm algorithm (cAPSO). The compact strategy replaces the specific position of each particle by the distribution probability of the particle swarm, which greatly reduces the memory usage. The performance of cAPSO is tested on 28 test functions of CEC2013, and compared with some existing heuristic algorithms, it proves that cAPSO has a better performance. At the same time, cAPSO is applied to MCL technology to improve the accuracy of node localization, and compared with other heuristic algorithms in the accuracy of MCL, the results show that cAPSO has a better performance.


Buildings ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 458
Author(s):  
Yanan Zhao ◽  
Zihan Zang ◽  
Weirong Zhang ◽  
Shen Wei ◽  
Yingli Xuan

In practical building control, quickly obtaining detailed indoor temperature distribution is necessary for providing satisfying personal comfort and improving building energy efficiency. The aim of this study is to propose a fast prediction method for indoor temperature distribution without knowing the thermal boundary conditions in practical applications. In this method, the index of contribution ratio of indoor climate (CRI), which represents the independent contribution of each heat source to the temperature distribution, has been combined with the air temperature collected by one mobile sensor at the height of the working area. Based on a typical office model, the effectiveness of using mobile sensors was discussed, and the influence of its acquisition height and acquisition distance on the prediction accuracy was analyzed as well. The results showed that the proposed prediction method was effective. When the sensors fixed on the wall were used to predict the indoor temperature distribution, the maximum average relative error was 27.7%, whereas when the mobile sensor was used to replace the fixed sensors, the maximum average relative error was 4.8%. This indicates that using mobile sensors with flexible acquisition location can help promote both reliability and accuracy of temperature prediction. In the human activity area, data from a set of mobile sensors were used to predict the temperature distribution at four heights. The prediction accuracy was 2.1%, 2.1%, 2.3%, and 2.7%, respectively. However, the influence of acquisition distance of mobile sensors on prediction accuracy cannot be ignored. The distance should be large enough to disperse the distribution of the acquisition points. Due to the influence of airflow, some distance between the acquisition points and the room boundaries should be given.


Sign in / Sign up

Export Citation Format

Share Document