TOWARDS CONTEXT-AWARE REAL-WORLD ENVIRONMENTS: THE CASE OF A REMOTE AUTONOMOUS ENERGY AWARE MONITORING SYSTEM

2011 ◽  
Vol 12 (03) ◽  
pp. 241-260
Author(s):  
NIK BESSIS ◽  
NICHOLAS MCLAUCHLAN ◽  
ELEANA ASIMAKOPOULOU ◽  
ANTONY BROWN ◽  
PETER NORRINGTON

Work is underway on issues associated with the development of tools and services to reduce energy consumption. Current trends suggest that energy consumption is increasing and carbon reserves are decreasing whilst green technologies for energy generation are yet to prove themselves. In industry, there are many legacy installations of equipment capable of transmitting their energy usage via the MODBUS protocol. Here we introduce a means of logging energy usage data and transmitting it to a database. The motivation is that making energy users aware of their consumption can help assist them in taking informed action towards the reduction of wasted energy. Thus, we offer a state-of-the-art of possible networking technologies, which have led to a real-world implementation. We present requirements whilst we mathematically model the compression technique. On the development side, we use GSM/GPRS technology, embedded KJava runtime and a bespoke Java application as the framework to email the usage data to the database.

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4209
Author(s):  
Rita Remeikienė ◽  
Ligita Gasparėnienė ◽  
Aleksandra Fedajev ◽  
Marek Szarucki ◽  
Marija Đekić ◽  
...  

The main goal of setting energy efficiency priorities is to find ways to reduce energy consumption without harming consumers and the environment. The renovation of buildings can be considered one of the main aspects of energy efficiency in the European Union (EU). In the EU, only 5% of the renovation projects have been able to yield energy-saving at the deep renovation level. No other study has thus far ranked the EU member states according to achieved results in terms of increased usage in renewable sources, a decrease in energy usage and import, and reduction in harmful gas emissions due to energy usage. The main purpose of this article is to perform a comparative analysis of EU economies according to selected indicators related to the usage of renewable resources, energy efficiency, and emissions of harmful gasses as a result of energy usage. The methodological contribution of our study is related to developing a complex and robust research method for investment efficiency assessment allowing the study of three groups of indicators related to the usage of renewable energy sources, energy efficiency, and ecological aspects of energy. It was based on the PROMETHEE II method and allows testing it in other time periods, as well as modifying it for research purposes. The EU member states were categorized by such criteria as energy from renewables and biofuels, final energy consumption from renewables and biofuels, gross electricity generation from renewables and biofuels and import dependency, and usage of renewables and biofuels for heating and cooling. The results of energy per unit of Gross Domestic Product (GDP), Greenhouse gasses (GHG) emissions per million inhabitants (ECO2), energy per capita, the share of CO2 emissions from public electricity, and heat production from total CO2 emissions revealed that Latvia, Sweden, Portugal, Croatia, Austria, Lithuania, Romania, Denmark, and Finland are the nine most advanced countries in the area under consideration. In the group of the most advanced countries, energy consumption from renewables and biofuels is higher than the EU average.


Author(s):  
Eva García-Martín ◽  
Niklas Lavesson ◽  
Håkan Grahn ◽  
Emiliano Casalicchio ◽  
Veselka Boeva

AbstractRecently machine learning researchers are designing algorithms that can run in embedded and mobile devices, which introduces additional constraints compared to traditional algorithm design approaches. One of these constraints is energy consumption, which directly translates to battery capacity for these devices. Streaming algorithms, such as the Very Fast Decision Tree (VFDT), are designed to run in such devices due to their high velocity and low memory requirements. However, they have not been designed with an energy efficiency focus. This paper addresses this challenge by presenting the nmin adaptation method, which reduces the energy consumption of the VFDT algorithm with only minor effects on accuracy. nmin adaptation allows the algorithm to grow faster in those branches where there is more confidence to create a split, and delays the split on the less confident branches. This removes unnecessary computations related to checking for splits but maintains similar levels of accuracy. We have conducted extensive experiments on 29 public datasets, showing that the VFDT with nmin adaptation consumes up to 31% less energy than the original VFDT, and up to 96% less energy than the CVFDT (VFDT adapted for concept drift scenarios), trading off up to 1.7 percent of accuracy.


Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1200
Author(s):  
Yong-Joon Jun ◽  
Seung-ho Ahn ◽  
Kyung-Soon Park

The Green Remodeling Project under South Korea’s Green New Deal policy is a government-led project intended to strengthen the performance sector directly correlated with energy performance among various elements of improvement applicable to building remodeling by replacing insulation materials, introducing new and renewable energy, introducing high-efficiency equipment, etc., with public buildings taking the lead in green remodeling in order to induce energy efficiency enhancement in private buildings. However, there is an ongoing policy that involves the application of a fragmentary value judgment criterion, i.e., whether to apply technical elements confined to the enhancement of the energy performance of target buildings and the prediction of improvement effects according thereto, thus resulting in the phenomenon of another important value criterion for green remodeling, i.e., the enhancement of the occupant (user) comfort performance of target buildings as one of its purposes, being neglected instead. In order to accurately grasp the current status of these problems and to promote ‘expansion of the value judgment criteria for green remodeling’ as an alternative, this study collected energy usage data of buildings actually used by public institutions and then conducted a total analysis. After that, the characteristics of energy usage were analyzed for each of the groups of buildings classified by year of completion, thereby carrying out an analysis of the correlation between the non-architectural elements affecting the actual energy usage and the actual energy usage data. The correlation between the improvement performance of each technical element and the actual improvement effect was also analyzed, thereby ascertaining the relationship between the direction of major policy strategies and the actual energy usage. As a result of the relationship analysis, it was confirmed that the actual energy usage is more affected by the operating conditions of the relevant building than the application of individual strategic elements such as the performance of the envelope insulation and the performance of the high-efficiency system. In addition, it was also confirmed that the usage of public buildings does not increase in proportion to their aging. The primary goal of reducing energy usage in target buildings can be achieved if public sector (government)-led green remodeling is pushed ahead with in accordance with biased value judgment criteria, just as in the case of a campaign to refrain from operating cooling facilities in aging public buildings. However, it was possible to grasp through the progress of this study that the remodeling may also result in the deterioration of environmental comfort and stability, such as the numerical value of the indoor thermal environment. The results of this study have the significance of providing basic data for pushing ahead with a green remodeling policy in which the value judgment criteria for aging existing public buildings are more expanded, and it is necessary to continue research in such a direction that the quantitative purpose of green remodeling, which is to reduce energy usage in aging public buildings, and its qualitative purpose, which is to enhance their environmental performance for occupants’ comfort, can be mutually balanced and secured at the same time.


Electronics ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 554
Author(s):  
Suresh Kallam ◽  
Rizwan Patan ◽  
Tathapudi V. Ramana ◽  
Amir H. Gandomi

Data are presently being produced at an increased speed in different formats, which complicates the design, processing, and evaluation of the data. The MapReduce algorithm is a distributed file system that is used for big data parallel processing. Current implementations of MapReduce assist in data locality along with robustness. In this study, a linear weighted regression and energy-aware greedy scheduling (LWR-EGS) method were combined to handle big data. The LWR-EGS method initially selects tasks for an assignment and then selects the best available machine to identify an optimal solution. With this objective, first, the problem was modeled as an integer linear weighted regression program to choose tasks for the assignment. Then, the best available machines were selected to find the optimal solution. In this manner, the optimization of resources is said to have taken place. Then, an energy efficiency-aware greedy scheduling algorithm was presented to select a position for each task to minimize the total energy consumption of the MapReduce job for big data applications in heterogeneous environments without a significant performance loss. To evaluate the performance, the LWR-EGS method was compared with two related approaches via MapReduce. The experimental results showed that the LWR-EGS method effectively reduced the total energy consumption without producing large scheduling overheads. Moreover, the method also reduced the execution time when compared to state-of-the-art methods. The LWR-EGS method reduced the energy consumption, average processing time, and scheduling overhead by 16%, 20%, and 22%, respectively, compared to existing methods.


Author(s):  
John A. Stankovic ◽  
Tian He

This paper presents a holistic view of energy management in sensor networks. We first discuss hardware designs that support the life cycle of energy, namely: (i) energy harvesting, (ii) energy storage and (iii) energy consumption and control. Then, we discuss individual software designs that manage energy consumption in sensor networks. These energy-aware designs include media access control, routing, localization and time-synchronization. At the end of this paper, we present a case study of the VigilNet system to explain how to integrate various types of energy management techniques to achieve collaborative energy savings in a large-scale deployed military surveillance system.


2015 ◽  
Vol 105 (05) ◽  
pp. 313-318
Author(s):  
F. Feder ◽  
K. Erlach ◽  
F. Hosak ◽  
H. Lepple

Die wachsende Volatilität im deutschen Energiesektor bietet jenen Unternehmen zukünftig einen Wettbewerbsvorteil, die ihren Energieverbrauch kontinuierlich senken und flexibel anpassen können. Als Werkzeug dafür wurde die Energiewertstrom-Methode um weitere Energieflüsse aus der Gebäude- und Versorgungstechnik sowie um Aspekte der Energieflexibilität erweitert. Dies erlaubt die Gestaltung eines energiekostenoptimalen Wertstroms.   In the light of the increasing volatility in the German energy sector, companies that are able to constantly reduce and control their energy consumption will gain a competitive advantage. Therefore, the Energy Value Stream Method has been extended by adding further energy flows in building technology as well as aspects of flexible energy usage. This enables the design of a value stream that results in low energy consumption and costs.


2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Aparna Ashok Kamble ◽  
Balaji Madhavrao Patil

Abstract Wireless networks involve spatially extended independent sensor nodes, and it is associated with each other’s to preserve and identify physical and environmental conditions of the particular application. The sensor nodes batteries are equipped with restricted energy for working with an energy source. Consequently, efficient energy consumption is themain important challenge in wireless networks, and it is outfitted witharestricted power storage capacity battery. Therefore, routing protocol with energy efficiency is essential in wireless sensor network (WSN) to offer data transmission and connectivity with less energy consumption. As a result, the routing scheme is the main factor for decreasing energy consumption and the network's lifetime. The energy-aware routing model is mainly devised for WSN with high network performance when transmitting data to a sink node. Hence, in this paper, the effectiveness of energy-aware routing protocols in mobile sink-based WSNs is analyzed and justified. Some energy-aware routing systems in mobile sink-based WSN techniques, such as optimizing low-energy adaptive clustering hierarchy (LEACH) clustering approach, hybrid model using fuzzy logic, and mobile sink. The fuzzy TOPSIS-based cluster head selection (CHS) technique, mobile sink-based energy-efficient CHS model, and hybrid Harris Hawk-Salp Swarm (HH-SS) optimization approach are taken for the simulation process. Additionally, the analytical study is executed using various conditions, like simulation, cluster size, nodes, mobile sink speed, and rounds. Moreover, the performance of existing methods is evaluated using various parameters, namely alive node, residual energy, delay, and packet delivery ratio (PDR).


2018 ◽  
Vol 7 (2.8) ◽  
pp. 550 ◽  
Author(s):  
G Anusha ◽  
P Supraja

Cloud computing is a growing technology now-a-days, which provides various resources to perform complex tasks. These complex tasks can be performed with the help of datacenters. Data centers helps the incoming tasks by providing various resources like CPU, storage, network, bandwidth and memory, which has resulted in the increase of the total number of datacenters in the world. These data centers consume large volume of energy for performing the operations and which leads to high operation costs. Resources are the key cause for the power consumption in data centers along with the air and cooling systems. Energy consumption in data centers is comparative to the resource usage. Excessive amount of energy consumption by datacenters falls out in large power bills. There is a necessity to increase the energy efficiency of such data centers. We have proposed an Energy aware dynamic virtual machine consolidation (EADVMC) model which focuses on pm selection, vm selection, vm placement phases, which results in the reduced energy consumption and the Quality of service (QoS) to a considerable level.


2013 ◽  
Vol 303-306 ◽  
pp. 191-196
Author(s):  
Wei Zhang ◽  
Ling Hua Zhang

Energy aware routing is a critical issue in WSN. Prior work in energy aware routing concerned about transmission energy consumption and residual energy, but often do not consider path hop length, which leads to unnecessary consumption of power at sensor nodes. Improved algorithm adds the control of routing hops. Simulation proof the improved algorithm is feasible, effectively reducing the network delay and the path of energy consumption. Taking into account the WSN is dynamic, in the end we put up dynamic hops control in order to adapt to WSN and select the optimal path.


2019 ◽  
Vol 45 ◽  
pp. 619-627 ◽  
Author(s):  
Triluck Koossalapeerom ◽  
Thaned Satiennam ◽  
Wichuda Satiennam ◽  
Watis Leelapatra ◽  
Atthapol Seedam ◽  
...  

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