Regression learning assisted efficient energy harvesting method for smart city environment

2021 ◽  
Vol 44 ◽  
pp. 101003
Author(s):  
Osama Alfarraj
Keyword(s):  
Energy Harvesting ◽  
Smart City ◽  
Efficient Energy ◽  
City Environment ◽  
Harvesting Method ◽  
Regression Learning

scholarly journals Enhanced Power Extraction with Sediment Microbial Fuel Cells by Anode Alternation

Fuels ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 168-178
Author(s):  
Marzia Quaglio ◽  
Daniyal Ahmed ◽  
Giulia Massaglia ◽  
Adriano Sacco ◽  
Valentina Margaria ◽  
...  
Keyword(s):  
Fuel Cells ◽  
Energy Harvesting ◽  
Power Density ◽  
Microbial Fuel Cells ◽  
Average Power ◽  
Power Extraction ◽  
Harvesting Technique ◽  
Harvesting Method ◽  
Energy Harvesting Devices ◽  
Efficient Power

Sediment microbial fuel cells (SMFCs) are energy harvesting devices where the anode is buried inside marine sediment, while the cathode stays in an aerobic environment on the surface of the water. To apply this SCMFC as a power source, it is crucial to have an efficient power management system, leading to development of an effective energy harvesting technique suitable for such biological devices. In this work, we demonstrate an effective method to improve power extraction with SMFCs based on anodes alternation. We have altered the setup of a traditional SMFC to include two anodes working with the same cathode. This setup is compared with a traditional setup (control) and a setup that undergoes intermittent energy harvesting, establishing the improvement of energy collection using the anodes alternation technique. Control SMFC produced an average power density of 6.3 mW/m2 and SMFC operating intermittently produced 8.1 mW/m2. On the other hand, SMFC operating using the anodes alternation technique produced an average power density of 23.5 mW/m2. These results indicate the utility of the proposed anodes alternation method over both the control and intermittent energy harvesting techniques. The Anode Alternation can also be viewed as an advancement of the intermittent energy harvesting method.

An all-rubber-based woven nanogenerator with improved triboelectric effect for highly efficient energy harvesting

2021 ◽  
Vol 287 ◽  
pp. 129271
Author(s):  
Shengnan Zhang ◽  
Jianming Xu ◽  
Junbin Yu ◽  
Linlin Song ◽  
Jian He ◽  
...  
Keyword(s):  
Energy Harvesting ◽  
Efficient Energy ◽  
Highly Efficient ◽  
Triboelectric Effect

In-situ liquid cell transmission electron microscopy guiding the design of large-sized cocatalysts coupled with ultra-small photocatalysts for highly efficient energy harvesting

2021 ◽  
Author(s):  
Chunlang Gao ◽  
Chunqiang Zhuang ◽  
Yuanli Li ◽  
Heyang Qi ◽  
Ge Chen ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Transmission Electron Microscopy ◽  
Energy Harvesting ◽  
Design Strategy ◽  
Efficient Energy ◽  
Highly Efficient ◽  
Transmission Electron ◽  
Cell Transmission ◽  
Liquid Cell

In this study, we employed in-situ liquid cell transmission electron microscopy (LC-TEM) to carry out the new design strategy of precisely regulating the microstructure of large-sized cocatalysts for highly efficient...

Significance of Building Information Modeling in Modern Project Management for Sustainable Smart City Applications

2021 ◽  
pp. 2141007
Author(s):  
Mengyi Lian ◽  
Xiaowei Liu
Keyword(s):  
Project Management ◽  
Internet Of Things ◽  
Smart City ◽  
Building Information Modeling ◽  
Information Modeling ◽  
The Internet ◽  
City Environment ◽  
Modern Project ◽  
Building Information ◽  
The Internet Of Things

Building information modeling (BIM) is one of the most exciting recent construction, engineering, and architecture developments. Built environments play a significant role in Smart City worldwide, and they are used to convey useful information to achieve smart city strategic goals. In modern project management, optimizing resources, BIM data integration, and data sharing in a smart city environment is challenging. Hence, in this paper, IoT-based Improved Building Information modeling (IoT-IBIM) has been proposed to overcome the challenges in building information modeling in modern project management for sustainable smart city applications. This paper discusses the efforts to create and integrate built-in environment data with IoT sensors for effective communication. The Internet of Things provides efficient resource control, increased efficiency, and improved human quality of life. As a result, the Internet of Things is a critical enabler of smart societies, including smart homes, smart cities, and smart factories. Building Information Modeling is an advanced asset allocation framework that generates high-quality output, reduces resource use, reduces environmental effects of development, and secures resources and availability for future generations. The experimental results show that the proposed IoT-IBIM method enhances the performance ratio and improves data integration and data sharing in a smart city environment.

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