scholarly journals A Novel of Data Gathering Method for User Activity Characterisation in an Office Environment to Improve Energy Efficiency

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Xiaofei Xing ◽  
Dongqing Xie ◽  
Guojun Wang

Compressed sensing (CS) is an emerging sampling technique by which the data sampling and aggregating can be done simultaneously, which can be applied to many fields, including data processing in wireless sensor networks (WSNs). In WSNs, data aggregating can reduce data transmission cost and improve energy efficiency. Existing CS-based data gathering work in WSNs utilizes the centralized method to process the data by a sink node, which causes the load imbalance and “coverage hole” problems, and so forth. In this paper, we propose an energy-balanced data gathering and aggregating (EDGA) scheme that integrates a clustering hierarchical structure with the CS to optimize and balance the amount of data transmitted. We also design a data reconstruction algorithm to perform data recovery tasks by utilizing the orthogonal matching pursuit theory, which helps to reconstruct the original data accurately and effectively at sink node. The advantages of the proposed scheme compared with other state-of-the-art related methods are measured on the metrics of data recovery ratio and energy efficiency. We implement our scheme on a simulation platform using a real dataset from Intel lab. Simulation results demonstrate that the proposed data gathering and aggregating scheme guarantees accurate data reconstruction performance and obtains energy efficiency significantly compared to existing methods.


Author(s):  
Jait Purohit

Energy efficiency (EE) has become an important benchmark in manufacturing industry due the increasing concerns about climate change and tightening of environmental regulations. However, most manufacturing and production industries today are only able to monitor aggregated energy consumption and lack the real-time visibility of EE on the shop floors. The ability to access energy information and effectively analyse such real-time data to extract key indicators is a crucial factor for successful energy management. While enabling real-time online monitoring of Energy Efficiency, it also applies data gathering analysis to detect abnormal energy consumption patterns and quantify energy efficiency gaps. Through a case study of a microfluidic device manufacturing line, we demonstrate how the application can assist energy managers in embedding best energy management practices in their day-to-day operations and improve Energy Efficiency by eliminating possible energy wastages on manufacturing shop floors.


Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2654 ◽  
Author(s):  
Yuan Rao ◽  
Gang Zhao ◽  
Wen Wang ◽  
Jingyao Zhang ◽  
Zhaohui Jiang ◽  
...  

Due to the limited energy budget, great efforts have been made to improve energy efficiency for wireless sensor networks. The advantage of compressed sensing is that it saves energy because of its sparse sampling; however, it suffers inherent shortcomings in relation to timely data acquisition. In contrast, prediction-based approaches are able to offer timely data acquisition, but the overhead of frequent model synchronization and data sampling weakens the gain in the data reduction. The integration of compressed sensing and prediction-based approaches is one promising data acquisition scheme for the suppression of data transmission, as well as timely collection of critical data, but it is challenging to adaptively and effectively conduct appropriate switching between the two aforementioned data gathering modes. Taking into account the characteristics of data gathering modes and monitored data, this research focuses on several key issues, such as integration framework, adaptive deviation tolerance, and adaptive switching mechanism of data gathering modes. In particular, the adaptive deviation tolerance is proposed for improving the flexibility of data acquisition scheme. The adaptive switching mechanism aims at overcoming the drawbacks in the traditional method that fails to effectively react to the phenomena change unless the sampling frequency is sufficiently high. Through experiments, it is demonstrated that the proposed scheme has good flexibility and scalability, and is capable of simultaneously achieving good energy efficiency and high-quality sensing of critical events.


2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Soobin Lee ◽  
Howon Lee

Improving energy efficiency is the most important challenge in wireless sensor networks. Because sensing information is correlated in many sensor network applications, some previous works have proposed ideas that reduce the energy consumption of the network by exploiting the spatial correlation between sensed information. In this paper, we propose a distributed data compression framework that exploits the broadcasting characteristic of the wireless medium to improve energy efficiency. We analyze the performance of the proposed framework numerically and compare it with the performance of previous works using simulation. The proposed scheme performs better when the sensing information is correlated.


2021 ◽  
Vol 13 (3) ◽  
pp. 1584
Author(s):  
Roberto Araya ◽  
Pedro Collanqui

Education is critical for improving energy efficiency and reducing CO2 concentration, but collaboration between countries is also critical. It is a global problem in which we cannot isolate ourselves. Our students must learn to collaborate in seeking solutions together with others from other countries. Thus, the research question of this study is whether interactive cross-border science classes with energy experiments are feasible and can increase awareness of energy efficiency among middle school students. We designed and tested an interactive cross-border class between Chilean and Peruvian eighth-grade classes. The classes were synchronously connected and all students did experiments and answered open-ended questions on an online platform. Some of the questions were designed to check conceptual understanding whereas others asked for suggestions of how to develop their economies while keeping CO2 air concentration at acceptable levels. In real time, the teacher reviewed the students’ written answers and the concept maps that were automatically generated based on their responses. Students peer-reviewed their classmates’ suggestions. This is part of an Asia-Pacific Economic Cooperation (APEC) Science Technology Engineering Mathematics (STEM) education project on energy efficiency using APEC databases. We found high levels of student engagement, where students discussed not only the cross-cutting nature of energy, but also its relation to socioeconomic development and CO2 emissions, and the need to work together to improve energy efficiency. In conclusion, interactive cross-border science classes are a feasible educational alternative, with potential as a scalable public policy strategy for improving awareness of energy efficiency among the population.


2016 ◽  
Vol 2016 ◽  
pp. 1-13
Author(s):  
Fan Yang ◽  
Kotaro Tadano ◽  
Gangyan Li ◽  
Toshiharu Kagawa

Factories are increasingly reducing their air supply pressures in order to save energy. Hence, there is a growing demand for pneumatic booster valves to overcome the local pressure deficits in modern pneumatic systems. To further improve energy efficiency, a new type of booster valve with energy recovery (BVER) is proposed. The BVER principle is presented in detail, and a dimensionless mathematical model is established based on flow rate, gas state, and energy conservation. The mathematics model was transformed into a dimensionless model by accurately selecting the reference values. Subsequently the dimensionless characteristics of BVER were found. BVER energy efficiency is calculated based on air power. The boost ratio is found to be mainly affected by the operational parameters. Among the structural ones, the recovery/boost chamber area ratio and the sonic conductance of the chambers are the most influential. The boost ratio improves by 15%–25% compared to that of a booster valve without an energy recovery chamber. The efficiency increases by 5%–10% depending on the supply pressure. A mathematical model is validated by experiment, and this research provides a reference for booster valve optimisation and energy saving.


2021 ◽  
Vol 13 (7) ◽  
pp. 3810
Author(s):  
Alessandra Cantini ◽  
Leonardo Leoni ◽  
Filippo De Carlo ◽  
Marcello Salvio ◽  
Chiara Martini ◽  
...  

The cement industry is highly energy-intensive, consuming approximately 7% of global industrial energy consumption each year. Improving production technology is a good strategy to reduce the energy needs of a cement plant. The market offers a wide variety of alternative solutions; besides, the literature already provides reviews of opportunities to improve energy efficiency in a cement plant. However, the technology is constantly developing, so the available alternatives may change within a few years. To keep the knowledge updated, investigating the current attractiveness of each solution is pivotal to analyze real companies. This article aims at describing the recent application in the Italian cement industry and the future perspectives of technologies. A sample of plant was investigated through the analysis of mandatory energy audit considering the type of interventions they have recently implemented, or they intend to implement. The outcome is a descriptive analysis, useful for companies willing to improve their sustainability. Results prove that solutions to reduce the energy consumption of auxiliary systems such as compressors, engines, and pumps are currently the most attractive opportunities. Moreover, the results prove that consulting sector experts enables the collection of updated ideas for improving technologies, thus giving valuable inputs to the scientific research.


Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 537
Author(s):  
Mohammad Baniata ◽  
Haftu Tasew Reda ◽  
Naveen Chilamkurti ◽  
Alsharif Abuadbba

One of the major concerns in wireless sensor networks (WSNs) is most of the sensor nodes are powered through limited lifetime of energy-constrained batteries, which majorly affects the performance, quality, and lifetime of the network. Therefore, diverse clustering methods are proposed to improve energy efficiency of the WSNs. In the meantime, fifth-generation (5G) communications require that several Internet of Things (IoT) applications need to adopt the use of multiple-input multiple-output (MIMO) antenna systems to provide an improved capacity over multi-path channel environment. In this paper, we study a clustering technique for MIMO-based IoT communication systems to achieve energy efficiency. In particular, a novel MIMO-based energy-efficient unequal hybrid clustering (MIMO-HC) protocol is proposed for applications on the IoT in the 5G environment and beyond. Experimental analysis is conducted to assess the effectiveness of the suggested MIMO-HC protocol and compared with existing state-of-the-art research. The proposed MIMO-HC scheme achieves less energy consumption and better network lifetime compared to existing techniques. Specifically, the proposed MIMO-HC improves the network lifetime by approximately 3× as long as the first node and the final node dies as compared with the existing protocol. Moreover, the energy that cluster heads consume on the proposed MIMO-HC is 40% less than that expended in the existing protocol.


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