scholarly journals Eco-Environmental Civilization Construction System in Remote Areas Based on Multiple Data Collection and the Internet of Things

2022 ◽  
Vol 2022 ◽  
pp. 1-9
Author(s):  
Xinyi Du ◽  
Haijun Ma
Keyword(s):  
Data Collection ◽  
Information Transmission ◽  
Development Strategy ◽  
Large Scale ◽  
Edge Computing ◽  
Evaluation Index System ◽  
Ecological Environment ◽  
Ecological Civilization ◽  
Remote Areas ◽  
Multiple Data

For a long time, the development strategy of remote areas is basically resource-oriented. Large-scale exploitation of resources not only damages the corresponding balance of resource reserves but also causes serious damage to the ecological environment. To this end, this paper has carried out research on the construction of ecological environment civilization in remote areas based on multidata collection and edge computing. Based on the understanding of the connotation, composition, and characteristics of ecological civilization, this paper selects representative indicators to reflect the specific requirements of ecological civilization, constructs an evaluation index system for the construction of ecological civilization in remote areas, and uses the evaluation indicators analysis and sorting. Second, edge computing and sensor technologies are applied to the process of data collection and information transmission and providing solutions for data collection and transmission in remote areas. This paper also presents the security method to protect the information transmission. Through testing, the program has shown good adaptability and can provide ideas for the construction of ecological environment in remote areas.

scholarly journals Development Strategy of National Food Sovereignty To Encounter Radicalism Threat

2019 ◽  
Vol 8 (11) ◽  
pp. 544-553
Keyword(s):  
Development Strategy ◽  
Qualitative Method ◽  
Large Scale ◽  
Food Sovereignty ◽  
Small Scale ◽  
Economic Management ◽  
Site Specific ◽  
Remote Areas ◽  
The Government ◽  
Specific Management

Higher demand for broader and possible growth of the problem of state instability. Nothing more than a problem triggers social conflict on a small scale to a large scale. This study aims to identify and study various reasons in Indonesia and also formulate conceptions to increase the responsibility of communities in remote areas. The qualitative method in this study was carried out descriptively based on literature studies. The approach used in this study is integral to the national paradigm and applicable regulations. The results of the study show that the concepts that are following the conditions of the community, increase competitiveness among the environment that can be accessed by the government and facilitate people to manage the natural resources of the region, conduct and implement site-specific management and develop economic management to produce superior products.

scholarly journals Edge Computing-Enabled Wireless Sensor Networks for Multiple Data Collection Tasks in Smart Agriculture

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Xiaomin Li ◽  
Lixue Zhu ◽  
Xuan Chu ◽  
Han Fu
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Collection ◽  
Edge Computing ◽  
Wireless Sensor ◽  
Quality Of Data ◽  
Traditional Methods ◽  
Multiple Data ◽  
Smart Agriculture

At present, precision agriculture and smart agriculture are the hot topics, which are based on the efficient data collection by using wireless sensor networks (WSNs). However, agricultural WSNs are still facing many challenges such as multitasks, data quality, and latency. In this paper, we propose an efficient solution for multiple data collection tasks exploiting edge computing-enabled wireless sensor networks in smart agriculture. First, a novel data collection framework is presented by merging WSN and edge computing. Second, the data collection process is modeled, including a plurality of sensors and tasks. Next, according to each specific task and correlation between task and sensors, on the edge computing server, a double selecting strategy is established to determine the best node and sensor network that fulfills quality of data and data collection time constraints of tasks. Furthermore, a data collection algorithm is designed, based on set values for quality of data. Finally, a simulation environment is constructed where the proposed strategy is applied, and results are analyzed and compared to the traditional methods. According to the comparison results, the proposal outperforms the traditional methods in metrics.

scholarly journals EVALUATION OF THE INFLUENCE OF RAILWAY TRANSPORT IN SIBERIA IN THE STRATEGY OF THE FAR EASTERN VECTOR OF THE COUNTRY'S ECONOMY

2019 ◽  
Vol 3 (1) ◽  
pp. 177-183
Author(s):  
Boris Melent’ev
Keyword(s):  
Economic Policy ◽  
Development Strategy ◽  
Large Scale ◽  
Far East ◽  
Railway Transport ◽  
Remote Areas ◽  
The Far East ◽  
Time Period ◽  
Far Eastern ◽  
The Impact

The paper presents the results of calculations based on inter-sectoral interregional tools to assess the impact of rail transport in the Siberian regions in the implementation of the Eastern development strategy. With the increasing connectivity of the districts, this policy has an impact on both neighboring and remote areas from the Far East. In General, the calculations show a comprehensive assessment of large-scale economic policy options while ensuring systemic conditions. The instrumental base allows to give quantitative values of consequences of change of options of economic policy with indication of branches and areas and on time period dynamics.

Integration of statistical and administrative agricultural data from Namibia

2021 ◽  
pp. 1-22
Author(s):  
Emily Berg ◽  
Johgho Im ◽  
Zhengyuan Zhu ◽  
Colin Lewis-Beck ◽  
Jie Li
Keyword(s):  
Measurement Error ◽  
Data Collection ◽  
Administrative Data ◽  
Statistical Data ◽  
Data Sources ◽  
Extension Programs ◽  
Multiple Data ◽  
Administrative Agencies ◽  
Crop Area ◽  
Using Data

Statistical and administrative agencies often collect information on related parameters. Discrepancies between estimates from distinct data sources can arise due to differences in definitions, reference periods, and data collection protocols. Integrating statistical data with administrative data is appealing for saving data collection costs, reducing respondent burden, and improving the coherence of estimates produced by statistical and administrative agencies. Model based techniques, such as small area estimation and measurement error models, for combining multiple data sources have benefits of transparency, reproducibility, and the ability to provide an estimated uncertainty. Issues associated with integrating statistical data with administrative data are discussed in the context of data from Namibia. The national statistical agency in Namibia produces estimates of crop area using data from probability samples. Simultaneously, the Namibia Ministry of Agriculture, Water, and Forestry obtains crop area estimates through extension programs. We illustrate the use of a structural measurement error model for the purpose of synthesizing the administrative and survey data to form a unified estimate of crop area. Limitations on the available data preclude us from conducting a genuine, thorough application. Nonetheless, our illustration of methodology holds potential use for a general practitioner.

scholarly journals Joint optimization of network selection and task offloading for vehicular edge computing

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Lujie Tang ◽  
Bing Tang ◽  
Li Zhang ◽  
Feiyan Guo ◽  
Haiwu He
Keyword(s):  
Large Scale ◽  
Vehicular Networks ◽  
Access Point ◽  
Edge Computing ◽  
Network Selection ◽  
Network Access ◽  
Task Execution ◽  
Point Selection ◽  
Vehicle Movement ◽  
Task Offloading

AbstractTaking the mobile edge computing paradigm as an effective supplement to the vehicular networks can enable vehicles to obtain network resources and computing capability nearby, and meet the current large-scale increase in vehicular service requirements. However, the congestion of wireless networks and insufficient computing resources of edge servers caused by the strong mobility of vehicles and the offloading of a large number of tasks make it difficult to provide users with good quality of service. In existing work, the influence of network access point selection on task execution latency was often not considered. In this paper, a pre-allocation algorithm for vehicle tasks is proposed to solve the problem of service interruption caused by vehicle movement and the limited edge coverage. Then, a system model is utilized to comprehensively consider the vehicle movement characteristics, access point resource utilization, and edge server workloads, so as to characterize the overall latency of vehicle task offloading execution. Furthermore, an adaptive task offloading strategy for automatic and efficient network selection, task offloading decisions in vehicular edge computing is implemented. Experimental results show that the proposed method significantly improves the overall task execution performance and reduces the time overhead of task offloading.

scholarly journals Construction of a Landscape Ecological Network for a Large-Scale Energy and Chemical Industrial Base: A Case Study of Ningdong, China

Land ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 344
Author(s):  
Haochen Yu ◽  
Jiu Huang ◽  
Chuning Ji ◽  
Zi’ao Li
Keyword(s):  
Ecological Restoration ◽  
Large Scale ◽  
Ecological Environment ◽  
Ecological Network ◽  
High Importance ◽  
Fractional Coverage ◽  
Industrial Base ◽  
Ecological Corridors ◽  
Vegetation Fractional Coverage

A large-scale energy and chemical industry base is an important step in the promotion of the integrated and coordinated development of coal and its downstream coal-based industry. A number of large-scale energy and chemical industrial bases have been built in the Yellow River Basin that rely on its rich coal resources. However, the ecological environment is fragile in this region. Once the eco-environment is destroyed, the wildlife would lose its habitat. Therefore, this area has attracted wide attention regarding the development of the coal-based industry while also protecting the ecological environment. An ecological network could improve landscape connectivity and provide ideas for ecological restoration. This study took the Ningdong Energy and Chemical Industrial Base as a case study. Morphological spatial pattern analysis was applied to extract core patches. The connectivity of the core patches was evaluated, and then the ecological source patches were recognized. The minimum cumulative resistance model, hydrologic analysis and circuit theory were used to simulate the ecological network. Then, ecological corridors and ecological nodes were classified. The results were as follows: (1) The vegetation fractional coverage has recently been significantly improved. The area of core patches was 22,433.30 ha. In addition, 18 patches were extracted as source patches, with a total area of 9455.88 ha; (2) Fifty-eight potential ecological corridors were simulated. In addition, it was difficult to form a natural ecological corridor because of the area’s great resistance. Moreover, the connectivity was poor between the east and west; (3) A total of 52 potential ecological nodes were simulated and classified. The high-importance nodes were concentrated in the western grassland and Gobi Desert. This analysis indicated that restoration would be conducive to the ecological landscape in this area. Furthermore, five nodes with high importance but low vegetation fractional coverage should be given priority in later construction. In summary, optimizing the ecological network to achieve ecological restoration was suggested in the study area. The severe eco-environmental challenges urgently need more appropriate policy guidance in the large energy and chemical bases. Thus, the ecological restoration and ecological network construction should be combined, the effectiveness of ecological restoration could be effectively achieved, and the cost could also be reduced.

scholarly journals Selecting Optimal Combination of Data Channels for Semantic Segmentation in City Information Modelling (CIM)

2021 ◽  
Vol 13 (7) ◽  
pp. 1367
Author(s):  
Yuanzhi Cai ◽  
Hong Huang ◽  
Kaiyang Wang ◽  
Cheng Zhang ◽  
Lei Fan ◽  
...  
Keyword(s):  
Large Scale ◽  
Semantic Segmentation ◽  
Optimal Combination ◽  
Reconstruction Technique ◽  
Process Data ◽  
Redundant Data ◽  
Multiple Data ◽  
Information Models ◽  
Efficient Data

Over the last decade, a 3D reconstruction technique has been developed to present the latest as-is information for various objects and build the city information models. Meanwhile, deep learning based approaches are employed to add semantic information to the models. Studies have proved that the accuracy of the model could be improved by combining multiple data channels (e.g., XYZ, Intensity, D, and RGB). Nevertheless, the redundant data channels in large-scale datasets may cause high computation cost and time during data processing. Few researchers have addressed the question of which combination of channels is optimal in terms of overall accuracy (OA) and mean intersection over union (mIoU). Therefore, a framework is proposed to explore an efficient data fusion approach for semantic segmentation by selecting an optimal combination of data channels. In the framework, a total of 13 channel combinations are investigated to pre-process data and the encoder-to-decoder structure is utilized for network permutations. A case study is carried out to investigate the efficiency of the proposed approach by adopting a city-level benchmark dataset and applying nine networks. It is found that the combination of IRGB channels provide the best OA performance, while IRGBD channels provide the best mIoU performance.

scholarly journals A Proximal Algorithm for Fork-Choice in Distributed Ledger Technology for Context-Based Clustering on Edge Computing

2020 ◽  
Vol 2 (1) ◽  
pp. 92
Author(s):  
Rahim Rahmani ◽  
Ramin Firouzi ◽  
Sachiko Lim ◽  
Mahbub Alam
Keyword(s):  
Large Scale ◽  
Cluster Head ◽  
Edge Computing ◽  
Computing Technology ◽  
Proximal Algorithm ◽  
Data Intensive ◽  
Distributed Ledger ◽  
Smart Contract ◽  
Distributed Ledger Technology ◽  
Iot Devices

The major challenges of operating data-intensive of Distributed Ledger Technology (DLT) are (1) to reach consensus on the main chain as a set of validators cast public votes to decide on which blocks to finalize and (2) scalability on how to increase the number of chains which will be running in parallel. In this paper, we introduce a new proximal algorithm that scales DLT in a large-scale Internet of Things (IoT) devices network. We discuss how the algorithm benefits the integrating DLT in IoT by using edge computing technology, taking the scalability and heterogeneous capability of IoT devices into consideration. IoT devices are clustered dynamically into groups based on proximity context information. A cluster head is used to bridge the IoT devices with the DLT network where a smart contract is deployed. In this way, the security of the IoT is improved and the scalability and latency are solved. We elaborate on our mechanism and discuss issues that should be considered and implemented when using the proposed algorithm, we even show how it behaves with varying parameters like latency or when clustering.

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