2021 12th International Conference on Information, Intelligence, Systems & Applications (IISA)最新文献_第2页

Innovative Personalised Applications to Motivate and Support Behavioural Energy Efficiency 创新的个性化应用程序，以激励和支持行为能源效率

2021 12th International Conference on Information, Intelligence, Systems & Applications (IISA) Pub Date : 2021-07-12 DOI: 10.1109/IISA52424.2021.9555498

K. Koasidis, J. Psarras

{"title":"Innovative Personalised Applications to Motivate and Support Behavioural Energy Efficiency","authors":"K. Koasidis, J. Psarras","doi":"10.1109/IISA52424.2021.9555498","DOIUrl":"https://doi.org/10.1109/IISA52424.2021.9555498","url":null,"abstract":"Under the Energy Efficiency Directive (2012/27/EU) energy companies have to achieve yearly energy savings up to 1.5% of annual sales to final consumers. Although buildings’ occupants and energy end-users seem to be gaining greater awareness of the value and need for sustainable energy practices, they do not behave in a more energy-conscious way. Existing solutions tend to be complicated, excluding buildings’ occupants from the process of understanding how the building works in terms of energy efficiency. This study presents a suite of user-centered applications, which will empower energy end-users to engage in achieving energy efficiency, using an open, secure, privacy-respectful, configurable, scalable cloud based big data infrastructure. This multi-disciplinary big data environment will integrate heterogeneous types of data, combined with emerging machine learning algorithms, distributed ledgers, blockchain technologies and a digital reward scheme through an alternative currency. These tools provide a “user – centric” framework for energy companies, local and regional authorities and third parties to empower energy end-users to take an active attitude in their energy usage. The proposed framework aims at transforming the social environment in a building to make people aware of the value of energy, and the importance of their collaboration, unlocking a potential for 12TWh energy saved in Europe.","PeriodicalId":437496,"journal":{"name":"2021 12th International Conference on Information, Intelligence, Systems & Applications (IISA)","volume":"216 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115515785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

A Data-Driven Decision Support Tool at the service of Energy suppliers and Utilities for Tackling Energy Poverty: A case study in Greece 数据驱动的决策支持工具为能源供应商和公用事业公司解决能源贫困提供服务:以希腊为例

2021 12th International Conference on Information, Intelligence, Systems & Applications (IISA) Pub Date : 2021-07-12 DOI: 10.1109/IISA52424.2021.9555540

A. Arsenopoulos, Elissaios Sarmas, A. Stavrakaki, I. Giannouli, J. Psarras

{"title":"A Data-Driven Decision Support Tool at the service of Energy suppliers and Utilities for Tackling Energy Poverty: A case study in Greece","authors":"A. Arsenopoulos, Elissaios Sarmas, A. Stavrakaki, I. Giannouli, J. Psarras","doi":"10.1109/IISA52424.2021.9555540","DOIUrl":"https://doi.org/10.1109/IISA52424.2021.9555540","url":null,"abstract":"Energy poverty is mainly understood as the inability of households to maintain adequate levels of affordable energy services, within countries of developed economic context, and there is a diverse set of indicators to measure it, with arrears on utility bills being one of them. This has stimulated the interest of utilities and energy suppliers, especially those that are also obliged (through a ringfence) or incentivised (through administrative uplifts in savings) to implement a share of energy efficiency measures to vulnerable and energy poor households, under Article 7 of the Energy Efficiency Directive (2012/27/EU). As a result, a considerable number of energy companies are designing, adopting and implementing measures that help end consumers, and in particular energy poor and vulnerable consumers, improve the energy efficiency of their dwellings. In this context, the aim of this paper is to present a decision support tool to help utilities and energy suppliers effectively evaluate different energy poverty schemes in terms of cost, risk and energy savings and select the optimal one(s) to consider. The final combination of schemes (i.e., portfolios) meet a set of context-specific targets and constraints, and are elicited in the scope of minimising both cost and risk on the utilities’ end. The tool is established upon the basic principles of Multi-objective Programming and it is implemented in Python 3.0 programming language. In this way, the proposed tool sets the groundwork for utilities and energy suppliers to fulfil energy efficiency obligations, as well as tackle energy poverty.","PeriodicalId":437496,"journal":{"name":"2021 12th International Conference on Information, Intelligence, Systems & Applications (IISA)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114711510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

In the Fog: Application Deployment for the Cloud Continuum 迷雾中:云连续体的应用程序部署

2021 12th International Conference on Information, Intelligence, Systems & Applications (IISA) Pub Date : 2021-07-12 DOI: 10.1109/IISA52424.2021.9555532

Dimitris Apostolou, Giannis Verginadis, G. Mentzas

引用次数: 1

Semantic Scene Segmentation for Robotics Applications 机器人应用的语义场景分割

2021 12th International Conference on Information, Intelligence, Systems & Applications (IISA) Pub Date : 2021-07-12 DOI: 10.1109/IISA52424.2021.9555526

Maria Tzelepi, A. Tefas

引用次数: 4

Optimization of motion and energy consumption of an industrial automated ground vehicle 工业自动化地面车辆运动与能耗优化

2021 12th International Conference on Information, Intelligence, Systems & Applications (IISA) Pub Date : 2021-07-12 DOI: 10.1109/IISA52424.2021.9555554

Theodora Liangou, A. J. Dentsoras

{"title":"Optimization of motion and energy consumption of an industrial automated ground vehicle","authors":"Theodora Liangou, A. J. Dentsoras","doi":"10.1109/IISA52424.2021.9555554","DOIUrl":"https://doi.org/10.1109/IISA52424.2021.9555554","url":null,"abstract":"Automated ground vehicles (AGVs) are means for performing a wide spectrum of tasks in the modern industries. The present paper addresses the problem of optimization of motion and energy consumption of such vehicles when they operate in a workspace with a warehouse and multiple workstations. A short description of the main attributes of AGVs is provided, followed by some references to their use as transport means for the distribution of resources in industrial environments. Next, their operation is considered by studying the energy consumption with respect to the load being carried and the resistances caused by their motion. Based on that study, a cost function is introduced, and an algorithm is also presented that considers the allocation tasks for the workstations and computes the least start load for the AGV. The heuristic search algorithm A* is used for the determination of optimal (least distance) paths for each combination of workstations’ pair. Then, a Genetic Algorithm (GA) locates optimal – in terms of distance and energy consumption – combinations/paths among workstations. The GA is supplied with two (2) different versions of fitness function that distinguish between multiple and unique pass of the AGV through workspace subspaces. The code has been implemented in Python and two case studies are presented and discussed. The proposed approach is innovative, presents low computational cost and may act as a tool that solves optimally the problem of motion and energy consumption for the AGVs by using efficiently artificial intelligence methods.","PeriodicalId":437496,"journal":{"name":"2021 12th International Conference on Information, Intelligence, Systems & Applications (IISA)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133802617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Expert Intelligence Tools for Proactive Energy Management in Buildings 楼宇能源主动管理的专家智能工具

2021 12th International Conference on Information, Intelligence, Systems & Applications (IISA) Pub Date : 2021-07-12 DOI: 10.1109/IISA52424.2021.9555547

Stefanos Michos, Dimitris Tsipianitis, P. Groumpos

引用次数: 0

PV Array Soiling Detection using Machine Learning 基于机器学习的光伏阵列污染检测

2021 12th International Conference on Information, Intelligence, Systems & Applications (IISA) Pub Date : 2021-07-12 DOI: 10.1109/IISA52424.2021.9555535

Joshua Martin, Kristen Jaskie, Yiannis Tofis, A. Spanias

{"title":"PV Array Soiling Detection using Machine Learning","authors":"Joshua Martin, Kristen Jaskie, Yiannis Tofis, A. Spanias","doi":"10.1109/IISA52424.2021.9555535","DOIUrl":"https://doi.org/10.1109/IISA52424.2021.9555535","url":null,"abstract":"Solar panel soiling detection is an important problem as soiled panels produce substantially reduced energy. This paper describes a collaborative project between Arizona State University and the University of Cyprus on fault detection. The project is part of an NSF program called International Research Experiences for Students on using machine learning for energy applications. In this study, we focus specifically on two methods for identifying soiling in residential solar installations. The first method aims to calculate a daily energy-lost-due-to-soiling value by comparing two calculated power curves: the expected best case scenario curve and a weather corrected curve, which estimates what the day’s power curve would be in the absence of cloud cover. The second method compares the performance of sites in the same weather region using a multi-level k-means clustering strategy. Initial results with ground truth feedback suggest that this second method is effective. The key take-away from this study is that these methods do not require feature rich datasets, which are often unavailable, rather they operate solely on time-series power values.","PeriodicalId":437496,"journal":{"name":"2021 12th International Conference on Information, Intelligence, Systems & Applications (IISA)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115628015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Formative Evaluation for Intelligence Quality Management in an Education Program. Case Study. 教育项目智力质量管理的形成性评价。案例研究。

2021 12th International Conference on Information, Intelligence, Systems & Applications (IISA) Pub Date : 2021-07-12 DOI: 10.1109/IISA52424.2021.9555576

Dimitris Tsipianitis, Ifigeneia Roumelioti

引用次数: 1

Transforming procedures to web applications using IFML: The new Greek Citizenship Test 使用IFML将程序转换为web应用程序:新的希腊公民考试

2021 12th International Conference on Information, Intelligence, Systems & Applications (IISA) Pub Date : 2021-07-12 DOI: 10.1109/IISA52424.2021.9555545

Stavros Piotopoulos, E. Sakkopoulos

引用次数: 1

Differentially Private Synthetic Mixed-Type Data Generation For Unsupervised Learning 基于非监督学习的差分私有合成混合类型数据生成

2021 12th International Conference on Information, Intelligence, Systems & Applications (IISA) Pub Date : 2021-07-12 DOI: 10.1109/IISA52424.2021.9555521

U. Tantipongpipat, Chris Waites, Digvijay Boob, Amaresh Ankit Siva, Rachel Cummings

引用次数: 15