scholarly journals Energy-Efficient Unmanned Aerial Vehicle (UAV) Surveillance Utilizing Artificial Intelligence (AI)

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Hai T. Do ◽  
Linh H. Truong ◽  
Minh T. Nguyen ◽  
Chen-Fu Chien ◽  
Hoang T. Tran ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Data Processing ◽  
Moving Objects ◽  
High Energy ◽  
Video Data ◽  
Data Streaming ◽  
Huge Data ◽  
Aerial Vehicle ◽  
Data Processing Center ◽  
Save Energy

Recently, unmanned aerial vehicles (UAVs) enhance connectivity and accessibility for civilian and military applications. A group of UAVs with on-board cameras usually monitors or collects information about designated areas. The UAVs can build a distributed network to share/exchange and to process collected sensing data before sending to a data processing center. A huge data transmission among them may cause latency and high-energy consumption. This paper deploys artificial intelligent (AI) techniques to process the video data streaming among the UAVs. Thus, each distributed UAV only needs to send a certain required information to each other. Each UAV processes data utilizing AI and only sends the data that matters to the others. The UAVs, formed as a connected network, communicate within a short communication range and share their own data to each other. Convolution neural network (CNN) technique extracts feature from images automatically that the UAVs only send the moving objects instead of the whole frames. This significantly reduces redundant information for either each UAV or the whole network and saves a huge energy consumption for the network. The UAVs can also save energy for their motion in the sensing field. In addition, a flocking control algorithm is deployed to lead the group of UAVs in the working fields and to avoid obstacles if needed. Simulation and experimental results are provided to verify the proposed algorithms in either AI-based data processing or controlling the UAVs. The results show promising points to save energy for the networks.

scholarly journals Large Scale Hotel Resource Retrieval Algorithm Based on Characteristic Threshold Extraction

2022 ◽  
Vol 16 ◽  
pp. 26-31
Author(s):  
Min Fang
Keyword(s):  
Energy Consumption ◽  
Data Processing ◽  
Large Scale ◽  
High Energy ◽  
Error Component ◽  
Retrieval Algorithm ◽  
Data Detection ◽  
Redundant Data ◽  
Variable Window ◽  
Resource Data

At present, the hotel resource retrieval algorithm has the problem of low retrieval efficiency, low accuracy, low security and high energy consumption, and this study proposes a large scale hotel resource retrieval algorithm based on characteristic threshold extraction. In the large-scale hotel resource data, the mass sequence is decomposed into periodic component, trend component, random error component and burst component. Different components are extracted, the singular point detection is realized by the extraction results, and the abnormal data in the hotel resource data are obtained. Based on the attribute of hotel resource data, the data similarity is processed with variable window, the total similarity of data is obtained, and the abnormal detection of redundant resource data is realized. The abnormal data detection results and redundant data detection results are substituted into the space-time filter, and the data processing is completed. The retrieval problem is identified, and the data processing results are replaced in the hotel resource retrieval based on the characteristic threshold extraction to achieve the normalization of data source and rule knowledge. The characteristic threshold and retrieval strategy are determined, and data fusion reasoning is carried out. After repeated iteration, effective solutions are obtained. The effective solution is fused to get the best retrieval result. Experimental results showed that the algorithm has higher retrieval accuracy, efficiency and security coefficient, and the average search energy consumption is 56n J/bit.

scholarly journals A Novel Reconstruction Approach to Elevator Energy Conservation Based on a DC Micro-Grid in High-Rise Buildings

Energies ◽  
2018 ◽  
Vol 12 (1) ◽  
pp. 33 ◽  
Author(s):  
Yongming Zhang ◽  
Zhe Yan ◽  
Feng Yuan ◽  
Jiawei Yao ◽  
Bao Ding
Keyword(s):  
Energy Consumption ◽  
Energy Conservation ◽  
High Energy ◽  
Energy Storage Devices ◽  
Storage Devices ◽  
High Rise ◽  
Field Data Collection ◽  
Micro Grid ◽  
Save Energy

Elevators were reported to cause an important part of building energy consumption. In general, each elevator has two operation states: The load state and power regeneration state. During operation, it has the potential to save energy by using regeneration power efficiently. In existing research, a set of energy storage devices are installed for every elevator, which is highly costly. In this paper, an energy conservation approach for elevators based on a direct current (DC) micro-grid is proposed, which has better economy. Then, an innovative energy-efficient device for the elevator group is designed based on a supercapacitor with similar characteristics and lifetimes. In a high-rise building case study, the experimental test and field data collection show that the innovative approach could result in a high energy efficiency within 15.87–23.1% and 24.1–54.5%, respectively. It is expected that the proposed method and designed device could be employed practically, saving energy consumption for elevator reconstruction.

Research on Energy Consumption for Improving Light Vehicle Manufacturing Technology of Automotive Industry in China

2012 ◽  
Vol 538-541 ◽  
pp. 2864-2867
Author(s):  
Fang Ma ◽  
Li Hua Chen ◽  
Yi Ping Luo
Keyword(s):  
Energy Consumption ◽  
Statistical Analysis ◽  
Automotive Industry ◽  
High Energy ◽  
Manufacturing Technology ◽  
Iron And Steel ◽  
New Era ◽  
Close Relationship ◽  
Save Energy ◽  
The Times

It has become the theme of the times to save energy and protect environment, since the environment has been deteriorating and energy crisis has been increasingly nervous. The trend is the development of automotive lightweight direction, because of the close relationship among energy consumption and vehicle manufacturing and using cost. In this article, the automotive industry to use the material is still main traditional material of iron and steel high-energy through a statistical analysis of the automotive industry energy consumption. Furthermore, the method was described that the use of lightweight environmentally friendly materials to promote lightweight manufacturing technology in the automotive industry based on the statistical analysis of the automotive industry energy consumption. A new era is coming with automotive materials development. The research and application of lightweight materials on new car will become the focus of future vehicle development.

Research on Measure of Energy-Saving and Environmental Protection in Foundry Industry

2014 ◽  
Vol 522-524 ◽  
pp. 845-848
Author(s):  
Ji Gao Li ◽  
Qian Zhang
Keyword(s):  
Sustainable Development ◽  
Energy Consumption ◽  
Energy Saving ◽  
Environmental Protection ◽  
High Energy ◽  
The Sustainable Development ◽  
Foundry Industry ◽  
Save Energy ◽  
High Energy Consumption

According the high energy consumption and pollution in foundry industry, the reason of high energy consumption and the source of the pollution were analyzed. Based on the analysis, for the sustainable development of foundry industry, some effective measures were suggested: defining the responsibility of all referred parties (governor and enterpriser); trying to save energy and protect environment from the source; reusing the waste scientifically.

EEA

2018 ◽  
Vol 7 (2) ◽  
pp. 19-37 ◽  
Author(s):  
Hassan El Alami ◽  
Abdellah Najid
Keyword(s):  
Energy Consumption ◽  
Clustering Algorithm ◽  
Clustering Algorithms ◽  
Data Communication ◽  
High Energy ◽  
Hierarchical Design ◽  
Communication Task ◽  
Save Energy ◽  
High Energy Consumption ◽  
Communication Path

The data communication task, in wireless sensor networks (WSNs), is a major issue of high energy consumption. A hierarchical design based on a clustering algorithm is one of the approaches to manage the data communication and save energy in WSNs. However, most of the previous approaches based on clustering algorithms have not considered the length of the data communication path, which is a direct relation to energy consumption in WSNs. In this article, a novel scheme of a clustering algorithm has been proposed for reducing the data communication distance in WSNs. Hierarchical routing protocols were implemented for homogeneous and heterogeneous networks. The results show that the proposed scheme is more efficient than other protocols.

scholarly journals Analyzing and Forecasting Energy Consumption in China’s Manufacturing Industry and Its Subindustries

2018 ◽  
Vol 11 (1) ◽  
pp. 99 ◽  
Author(s):  
Wei Sun ◽  
Yufei Hou ◽  
Lanjiang Guo
Keyword(s):  
Energy Consumption ◽  
Manufacturing Industry ◽  
Energy Use ◽  
Manufacturing Sector ◽  
High Energy ◽  
Chinese Government ◽  
Independent Innovation ◽  
Consumption Index ◽  
Save Energy ◽  
Energy Intensive Industries

In the context of new industrialization, the energy problem being experienced by the manufacturing industry has aroused social concerns. This paper focuses on the energy use of 27 subindustries in China’s manufacturing industry and it develops an energy consumption index for 1994–2015. Subsequently, the method of grey relational analysis is used, with the full period divided according to years in which change points occur. The empirical analysis indicates that the energy consumption indexes generally exhibit a declining trend. Using the grey model (GM (1,1)) to forecast the index indicates a continued downward trend up to 2025 for energy-intensive industries, which is a more optimistic scenario than the trend forecast for the whole manufacturing sector. Thus, these energy-intensive industries do not drag down the performance of the whole manufacturing industry in regard to energy intensity. In future, more attention should be paid to energy-saving efforts by nontraditional high-energy-consuming industries. Although the results show that energy efficiency is improving in China, total annual consumption is rising rapidly. Therefore, the industry needs to continue to strengthen independent innovation and improve the efficiency of new energy use. The Chinese government should formulate feasible long-term plans to encourage enterprises to save energy.

scholarly journals Teaching Learning Based Optimization (TLBO) for energy efficiency in Fog Computing

2021 ◽  
Vol 4 (1) ◽  
pp. 248-252
Author(s):  
Amanpreet Kaur ◽  
Heena Wadhwa ◽  
Pardeep Singh ◽  
Harpreet Kaur Toor
Keyword(s):  
Energy Consumption ◽  
Fog Computing ◽  
High Energy ◽  
Teacher Student ◽  
Huge Data ◽  
Teaching Learning Based Optimization ◽  
Teaching Learning ◽  
Least Energy ◽  
Fog Network

Fog Computing is eminent to ensure quality of service in handling huge volume and variety of data and to display output, or for closed loop process control. It comprises of fog devices to manage huge data transmission but results in high energy consumption, end-to end-delay, latency. In this paper, an energy model for fog computing environment has been proposed and implemented based on teacher student learning model called Teaching Learning Based Optimization (TLBO) to improve the responsiveness of the fog network in terms of energy optimization. The results show the effectiveness of TLBO in choosing the shortest path with least energy consumption.

EEA

2020 ◽  
pp. 735-752
Author(s):  
Hassan El Alami ◽  
Abdellah Najid
Keyword(s):  
Energy Consumption ◽  
Clustering Algorithm ◽  
Clustering Algorithms ◽  
Data Communication ◽  
High Energy ◽  
Direct Relation ◽  
Communication Task ◽  
Save Energy ◽  
High Energy Consumption ◽  
Communication Path

The data communication task, in wireless sensor networks (WSNs), is a major issue of high energy consumption. A hierarchical design based on a clustering algorithm is one of the approaches to manage the data communication and save energy in WSNs. However, most of the previous approaches based on clustering algorithms have not considered the length of the data communication path, which is a direct relation to energy consumption in WSNs. In this article, a novel scheme of a clustering algorithm has been proposed for reducing the data communication distance in WSNs. Hierarchical routing protocols were implemented for homogeneous and heterogeneous networks. The results show that the proposed scheme is more efficient than other protocols.

Evaluating the Emission and Energy Impacts of Automated Buses on Urban Expressways

2020 ◽  
Vol 2674 (12) ◽  
pp. 515-529
Author(s):  
Yixin Zhang ◽  
Xumei Chen ◽  
Lei Yu
Keyword(s):  
Energy Consumption ◽  
Autonomous Vehicles ◽  
High Energy ◽  
Environmental Benefits ◽  
Specific Power ◽  
Simulation Platform ◽  
Dynamic Link Library ◽  
Operational Strategies ◽  
Save Energy ◽  
The Impact

In recent years, a series of traffic problems have emerged with continuously increasing traffic. Connected and autonomous vehicles (CAV) technology is considered to be an effective way to relieve these problems. It is believed that buses, trucks, and other special vehicles could be among of the first application areas to promote the development of CAV technology. Because of their features of high emissions of pollutants and high energy consumption, the improvement of environmental benefits for such heavy vehicles as buses is the focus in this research. Therefore, this paper aims to evaluate the impact of automated buses on emissions and energy consumption on urban expressways. To achieve the research objectives in this paper, the established automated buses model is embedded into the simulation platform with VISSIM dynamic link library. Models are developed for emissions and energy consumption calculations based on vehicle-specific power to quantify the environmental impact of automated buses. Two improvement strategies: dedicated managed lane and dedicated bus lane, are designed. Finally, a VISSIM simulation platform based on the Fourth Ring Road in Beijing (Xueyuan Bridge to Haidian Bridge) is built to conduct case studies. The results show that CAV technology in buses can reduce exhaust emissions and save energy. Moreover, the managed lane strategy brings a significant reduction in the emissions and energy consumption of automated buses. These findings can be used for the development of automated bus operational strategies focused on environmental benefits.

scholarly journals Survey on Near-Data Processing: Applications and Architectures

2021 ◽  
Vol 16 (2) ◽  
pp. 1-17
Author(s):  
Paulo Cesar Santos ◽  
Francis Birck Moreira ◽  
Aline Santana Cordeiro ◽  
Sairo Raoní Santos ◽  
Tiago Rodrigo Kepe ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Data Processing ◽  
Data Transfer ◽  
High Energy ◽  
Data Movement ◽  
History Of ◽  
Memory Bottleneck ◽  
High Energy Consumption

One of the main challenges for modern processors is the data transfer between processor and memory. Such data movement implies high latency and high energy consumption. In this context, Near-Data Processing (NDP) proposals have started to gain acceptance as an accelerator device. Such proposals alleviate the memory bottleneck by moving instructions to data whereabouts. The first proposals date back to the 1990s, but it was only in the 2010s that we could observe an increase in papers addressing NDP. It occurred together with the appearance of 3D-stacked chips with logic and memory stacked layers. This survey presents a brief history of these accelerators, focusing on the applications domains migrated to near-data and the proposed architectures. We also introduce a new taxonomy to classify such architectural proposals according to their data distance.

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