scholarly journals Detection of Potentially Compromised Computer Nodes and Clusters Connected on a Smart Grid, Using Power Consumption Data

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5075
Author(s):  
Mohammed Almshari ◽  
Georgios Tsaramirsis ◽  
Adil Omar Khadidos ◽  
Seyed Mohammed Buhari ◽  
Fazal Qudus Khan ◽  
...  
Keyword(s):  
Power Consumption ◽  
Smart Grids ◽  
Moving Average ◽  
Descriptive Analysis ◽  
Abnormal Behavior ◽  
Management Tool ◽  
Software Application ◽  
Consumption Data ◽  
Custom Made ◽  
Two Samples

Monitoring what application or type of applications running on a computer or a cluster without violating the privacy of the users can be challenging, especially when we may not have operator access to these devices, or specialized software. Smart grids and Internet of things (IoT) devices can provide power consumption data of connected individual devices or groups. This research will attempt to provide insides on what applications are running based on the power consumption of the machines and clusters. It is therefore assumed that there is a correlation between electric power and what software application is running. Additionally, it is believed that it is possible to create power consumption profiles for various software applications and even normal and abnormal behavior (e.g., a virus). In order to achieve this, an experiment was organized for the purpose of collecting 48 h of continuous real power consumption data from two PCs that were part of a university computer lab. That included collecting data with a one-second sample period, during class as well as idle time from each machine and their cluster. During the second half of the recording period, one of the machines was infected with a custom-made virus, allowing comparison between power consumption data before and after infection. The data were analyzed using different approaches: descriptive analysis, F-Test of two samples of variance, two-way analysis of variance (ANOVA) and autoregressive integrated moving average (ARIMA). The results show that it is possible to detect what type of application is running and if an individual machine or its cluster are infected. Additionally, we can conclude if the lab is used or not, making this research an ideal management tool for administrators.

scholarly journals PUMPNET: a deep learning approach to pump operation detection

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Luyao Ma ◽  
Qingyu Meng ◽  
Shirui Pan ◽  
Ariel Liebman
Keyword(s):  
Time Series ◽  
Deep Learning ◽  
Power Consumption ◽  
Smart Grids ◽  
Sampling Rate ◽  
High Energy ◽  
Series Data ◽  
Pump Operation ◽  
Consumption Data ◽  
Load Monitoring

AbstractNon-urgent high energy-consuming residential appliances, such as pool pumps, may significantly affect the peak to average ratio (PAR) of energy demand in smart grids. Effective load monitoring is an important step to provide efficient demand response (DR) to PAR. In this paper, we focus on pool pump analytics and present a deep learning framework, PUMPNET, to identify the pool pump operation patterns from power consumption data. Different from conventional time-series based Non-intrusive Load Monitoring (NILM) methods, our approach transfers the time-series data into image-like (date-time matrix) data. Then a U-shaped fully convolutional neural network is developed to detect and segment the image-like data in pixel level for operation detection. Our approach identify whether pool pumps operate given thirty-minute interval aggregated active power consumption data in kilowatt-hours only. Furthermore, the PUMPNET algorithm could identify pool pump operation status with high accuracy in the low-frequency sampling scenario for thousands of household, compared to traditional NILM algorithms which process high sampling rate data and can only apply to limited number of households. Experiments on real-world data validate the promising results of the proposed PUMPNET model.

scholarly journals Goals and measures for analyzing power consumption data in manufacturing enterprises

2021 ◽  
Vol 3 (1) ◽  
pp. 65-82
Author(s):  
Sören Henning ◽  
Wilhelm Hasselbring ◽  
Heinz Burmester ◽  
Armin Möbius ◽  
Maik Wojcieszak
Keyword(s):  
Power Consumption ◽  
Real Time ◽  
Manufacturing Industry ◽  
Fog Computing ◽  
Electrical Power ◽  
Time Data ◽  
Manufacturing Enterprises ◽  
Computing Paradigm ◽  
Consumption Data ◽  
Analyzing Power

AbstractThe Internet of Things adoption in the manufacturing industry allows enterprises to monitor their electrical power consumption in real time and at machine level. In this paper, we follow up on such emerging opportunities for data acquisition and show that analyzing power consumption in manufacturing enterprises can serve a variety of purposes. In two industrial pilot cases, we discuss how analyzing power consumption data can serve the goals reporting, optimization, fault detection, and predictive maintenance. Accompanied by a literature review, we propose to implement the measures real-time data processing, multi-level monitoring, temporal aggregation, correlation, anomaly detection, forecasting, visualization, and alerting in software to tackle these goals. In a pilot implementation of a power consumption analytics platform, we show how our proposed measures can be implemented with a microservice-based architecture, stream processing techniques, and the fog computing paradigm. We provide the implementations as open source as well as a public show case allowing to reproduce and extend our research.

scholarly journals INDIKATOR MAKROEKONOMI DAN PEMBANGUNAN KOTA BANDUNG

2019 ◽  
pp. 622
Author(s):  
Teguh Santoso ◽  
Bayu Kharisma
Keyword(s):  
Economic Growth ◽  
Poverty Reduction ◽  
Moving Average ◽  
Descriptive Analysis ◽  
High Rate ◽  
Purchasing Power ◽  
Autoregressive Moving Average Model ◽  
Food Commodities ◽  
The City ◽  
Poverty Levels

The high rate of inflation has the potential to increase poverty because it can reduce people's purchasing power, where if inflation rises significantly it can shift the people who are categorized as not poor, become vulnerable to poverty, almost poor and even poor. The aims of this study are to analyze the development of macroeconomic indicators, namely inflation and economic growth that are associated with poverty levels in the city of Bandung. The methodology used in this study is descriptive analysis and the ARMA (autoregressive moving average) model. The results showed that the high inflation in the city of Bandung compared to national and West Java inflation carries its own burden for the economy of the community, where purchasing power will decrease when inflation rises significantly and will have an impact on people's welfare. Inflation in the city of Bandung is often due to the price of food commodities (volatile food inflation). In addition, the high economic growth in the city of Bandung is not directly proportional to the decline in poverty levels. This shows that the quality of economic growth in the city of Bandung has problems that need attention. Therefore, local government in their efforts to encourage economic growth must prioritize poverty reduction and inequality.

scholarly journals Son los códigos éticos un instrumento de gestión de la responsabilidad social? Un estudio exploratorio en Andalucía

2016 ◽  
Vol 12 (2) ◽  
pp. 462 ◽  
Author(s):  
Mercedes Ruiz-Lozano ◽  
Araceli De los Ríos Berjillos ◽  
Salud Millán Lara
Keyword(s):  
Business Ethics ◽  
Social Responsibility ◽  
Control Systems ◽  
Descriptive Analysis ◽  
Management Control ◽  
Management Tool ◽  
Small Enterprises ◽  
Ethical Codes ◽  
Sustainable Value ◽  
Corporate Social

Purpose: The growing concern for social responsibility and/or business ethics must be reflected in the control systems of organizations. Therefore we are concerned to analyze whether the ethical codes have been introduced as a management tool of social responsibility to build sustainable value-based organizations.Design/methodology/approach: Development of a survey based on the literature review of code types and motivations. We performed a descriptive analysis of the information obtained from companies based in Andalusia under study. Furthermore, it has been implemented a test of mean difference and an analysis of variance to contrast the hypotheses. Findings: The study supports a tendency to use the ethical codes by Andalusian companies analyzed, influenced by firm size. Similarly, the incidence of immediate environment is confirmed. Research limitations/implications: The study is exploratory in the Andalusian area due to restrictions databases and sample size. Practical implications: The results allow an approach to the Andalusian business reality and to the management systems related with social responsibility and business ethics. Social implications: It has highlighted the need for training in this area and that measures to promote ethics and corporate social responsibility are taken from the public sector, distinguishing between needs that may have micro and small enterprises from medium or large companies. Originality/value: This study contributes to knowledge about the importance of integrating instruments that promote responsible and sustainable management based on values in management control systems and about what were the motivations that are influencing both, for and against, in this action. Motivations that should be taken into account by decision-makers and influential in business development agencies.

Research on the Visualization of Living Conditions from the Power Consumption Data using the ECHONET Lite Standard

2021 ◽  
Author(s):  
Takahiro Sakai ◽  
Ryuta Imanishi ◽  
Shouma Yasuda ◽  
Hiroshi Sugimura ◽  
Masao Isshiki
Keyword(s):  
Power Consumption ◽  
Living Conditions ◽  
Consumption Data
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