2022 18th International Conference on Intelligent Environments (IE)最新文献_第2页

PISCO: A smart simulator to deploy energy saving methods in microservices based networks PISCO:一个智能模拟器，用于在基于微服务的网络中部署节能方法

2022 18th International Conference on Intelligent Environments (IE) Pub Date : 2022-06-20 DOI: 10.1109/ie54923.2022.9826775

H. H. Álvarez-Valera, Marc Dalmau, P. Roose, J. Larracoechea, Christina Herzog

{"title":"PISCO: A smart simulator to deploy energy saving methods in microservices based networks","authors":"H. H. Álvarez-Valera, Marc Dalmau, P. Roose, J. Larracoechea, Christina Herzog","doi":"10.1109/ie54923.2022.9826775","DOIUrl":"https://doi.org/10.1109/ie54923.2022.9826775","url":null,"abstract":"Nowadays, many researchers work to identify microservices-based application deployments and scheduling solutions to save energy without decreasing functional QoS. In this work, we present PISCO: A simulator that allows facing this challenge in a simple and efficient way, enabling its users to focus uniquely on microservices deployment/scheduling algorithms and its hardware/software repercussions (load vs. energy consumption) without worrying about low-level network configurations or operating system issues. PISCO is able to deploy and schedule (move, duplicate, start/stop) microservices and their dependencies on various devices with software and hardware heterogeneity (CPU, bandwidth, RAM, Battery, etc.), taking into account various scheduling heuristics algorithms: centralized vs non-centralized. To do this, PISCO allows deploying custom network topologies based on client-server schemes or p2p distributions, where devices can (dis)appear, turn on/off obeying random circumstances or user strategies.Finally, the simulator performs relevant operations such as QoS definition, resource monitoring, calculation of energy saved and consumption tracking (at device and network level). We tested some ideas based on our previous work “Kaligreen” to demonstrate the effectiveness of PISCO.","PeriodicalId":157754,"journal":{"name":"2022 18th International Conference on Intelligent Environments (IE)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130195966","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

Organization, Sponsors and Supports 组织、赞助者和支持者

2022 18th International Conference on Intelligent Environments (IE) Pub Date : 2022-06-20 DOI: 10.1109/ie54923.2022.9826777

引用次数: 0

Intelligent Building Evacuation under Consideration of Temporary Events and Dynamic Fire Propagation 考虑临时事件和火灾动态传播的智能建筑疏散

2022 18th International Conference on Intelligent Environments (IE) Pub Date : 2022-06-20 DOI: 10.1109/ie54923.2022.9826762

Timm Wächter, J. Rexilius, Martin Hoffmann, Matthias König

引用次数: 1

EMO-Learning: Towards an intelligent tutoring system to assess online students’ emotions emoo - learning:面向在线学生情绪评估的智能辅导系统

2022 18th International Conference on Intelligent Environments (IE) Pub Date : 2022-06-20 DOI: 10.1109/ie54923.2022.9826770

Belén López, Francisco Arcas-Túnez, Magdalena Cantabella, Fernando Terroso-Sáenz, M. Curado, Andrés Muñoz

引用次数: 0

Evaluation of time-series libraries for temperature prediction in smart greenhouses 智能温室温度预测的时间序列库评价

2022 18th International Conference on Intelligent Environments (IE) Pub Date : 2022-06-20 DOI: 10.1109/ie54923.2022.9826765

Santiago Ruiz, Juan Morales-García, C. Calafate, Juan-Carlos Cano, P. Manzoni, José M. Cecilia

{"title":"Evaluation of time-series libraries for temperature prediction in smart greenhouses","authors":"Santiago Ruiz, Juan Morales-García, C. Calafate, Juan-Carlos Cano, P. Manzoni, José M. Cecilia","doi":"10.1109/ie54923.2022.9826765","DOIUrl":"https://doi.org/10.1109/ie54923.2022.9826765","url":null,"abstract":"Nowadays, human overpopulation is stressing our ecosystems in different ways, being agriculture a critical example as different predictions point towards food shortages in the near future. In such context, smart farming is becoming key to optimize natural resources so that different crops are grown efficiently, consuming as few resources as possible. In particular, greenhouses have shown to be an effective approach to producing a high volume of vegetables/fruits in a reduced space and within a short time span. Hence, optimizing greenhouse functioning results in less water and nutrient consumption, less energy use, faster growth, and better product quality. In this paper, we take a step in this direction by studying the best approach to forecast greenhouse temperature based on univariate time-series analysis. In particular, several widely used time-series libraries such as Prophet by Facebook, Greykite by LinkedIn and TPOT are studied to figure out which performs better for this particular scenario. Results show that the maximum prediction error ranges from 1.5 to 3 degrees Celsius, and, in general terms, Greykite is found to be the best performing library for this particular environment.","PeriodicalId":157754,"journal":{"name":"2022 18th International Conference on Intelligent Environments (IE)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127396732","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

Optimization of Soft Mobility Localization with Sustainable Policies and Open Data 基于可持续政策和开放数据的软移动出行本地化优化

2022 18th International Conference on Intelligent Environments (IE) Pub Date : 2022-06-20 DOI: 10.1109/ie54923.2022.9826779

Sofia Kleisarchaki, L. Gürgen, Y. Kassa, M. Krystek, Daniel González Vidal

{"title":"Optimization of Soft Mobility Localization with Sustainable Policies and Open Data","authors":"Sofia Kleisarchaki, L. Gürgen, Y. Kassa, M. Krystek, Daniel González Vidal","doi":"10.1109/ie54923.2022.9826779","DOIUrl":"https://doi.org/10.1109/ie54923.2022.9826779","url":null,"abstract":"A quarter of global greenhouse emissions come from transport, with modern cities producing more than 60% of these emissions. To reduce carbon footprint, several solutions on soft mobility (e.g., optimizing electric vehicles locations) have been proposed using IoT resources and AI techniques. However, these solutions either lack replicability since they ignore city’s needs per area and economic restrictions or lack algorithmic fairness since they account no social criteria (e.g., disabled, age, gender). In this work, we developed AI-based methods to automatically detect the different areas (e.g., rural, urban) and propose two heuristics which incorporate social, environmental and economic criteria of the area in their decision making in the form of sustainability policy templates. Our heuristics solve the p-median problem; they minimize the distance of stations to important points constrained by the cost of new stations. We show that our proposed solution is able to disperse the new stations within the city while covering local neighbourhoods. This work is replicated in two big European cities adapted to different open data and demonstrated by a dedicated visual dashboard.","PeriodicalId":157754,"journal":{"name":"2022 18th International Conference on Intelligent Environments (IE)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128563714","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

Doki: A Multi-sensation Interaction Device that Communicates Emotions Doki:一种交流情感的多感觉互动设备

2022 18th International Conference on Intelligent Environments (IE) Pub Date : 2022-06-20 DOI: 10.1109/ie54923.2022.9826782

Yuhe Cui, Zezhi Guo, Yuxin Wang, Xiangzhou Peng, Joon Park, Carlos Aguiar

{"title":"Doki: A Multi-sensation Interaction Device that Communicates Emotions","authors":"Yuhe Cui, Zezhi Guo, Yuxin Wang, Xiangzhou Peng, Joon Park, Carlos Aguiar","doi":"10.1109/ie54923.2022.9826782","DOIUrl":"https://doi.org/10.1109/ie54923.2022.9826782","url":null,"abstract":"During the pandemic, many people have found themselves physically isolated from each other for long periods of time, so online chatting tools have become the main path of communication. However, texts and other chatting tools do not properly transmit the complex emotions hidden behind them. However, texts and other visual information have created an overload of information and made people ignore the complex emotions hidden behind them. Without the stimulation of sensations from face-to-face communications, people, especially lovers, lose their ability to observe their beloved ones’ emotions and feelings effectively.In this work, we propose a device to improve the efficiency of emotional communication - a multi-sensation interaction installation called Doki, which utilizes light, digital display, vibrations, and tactile interaction to transfer emotions. In addition, this device is comfortable to touch and enjoyable to play with. When used in conjunction with its texting applications, this product will help people express emotions over long distances and alleviate feelings of isolation.","PeriodicalId":157754,"journal":{"name":"2022 18th International Conference on Intelligent Environments (IE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133937295","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

Unsupervised Segmentation of Smart Home Logs for Human Habit Discovery 用于人类习惯发现的智能家居日志的无监督分割

2022 18th International Conference on Intelligent Environments (IE) Pub Date : 2022-06-20 DOI: 10.1109/ie54923.2022.9826776

Lucia Esposito, F. Leotta, Massimo Mecella, Silvestro V. Veneruso

引用次数: 3

A machine learning-based approach for smart agriculture via stacking-based ensemble learning and feature selection methods 基于堆叠的集成学习和特征选择方法的智能农业机器学习方法

2022 18th International Conference on Intelligent Environments (IE) Pub Date : 2022-06-20 DOI: 10.1109/ie54923.2022.9826767

Emna Ben Abdallah, Rima Grati, Khouloud Boukadi

{"title":"A machine learning-based approach for smart agriculture via stacking-based ensemble learning and feature selection methods","authors":"Emna Ben Abdallah, Rima Grati, Khouloud Boukadi","doi":"10.1109/ie54923.2022.9826767","DOIUrl":"https://doi.org/10.1109/ie54923.2022.9826767","url":null,"abstract":"Smart irrigation has many advantages in optimizing resource usage (e.g., saving water, reducing energy consumption) and improving crop productivity. In this paper, we contribute to this field by proposing a robust and accurate machine learning-based approach that combines the power of feature selection methods and stacking ensemble method to effectively determine the optimal quantity of water needed for a plant. Random Forest, Recursive Feature Elimination (RFE), and SelectKBest are used to assess the importance of the features. Then, based on the best subset of features, a stacking ensemble model is proposed that combines CART, Gradient Boost Regression (GBR), Random Forest (RF) and XGBoost regressors. The different models involved in this approach are trained and tested using a collected dataset about various crops such as tomatoes, grapes, and lemon and encompasses different features such as meteorological data, soil data, irrigation data, and crop data. The experiments demonstrated the performance of RF in analyzing the feature importance. The findings of feature selection highlight the importance level of the evapotranspiration, the depletion, and the deficit to maximize the model’s accuracy. The results also showed that the proposed stacking model (Stacking_GBR+CART+RF+XGB) with the 10 most essential features outperforms individual models and other stacking models by achieving low error rates (i.e., MSE=0.0026, MAE=0.0279, RMSE=0.0509) and high R2 score (i.e., 0.9927).","PeriodicalId":157754,"journal":{"name":"2022 18th International Conference on Intelligent Environments (IE)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129164675","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: 5

ISEEapp: An Event Explanation Prototype bridging the gap between sensor network and document corpora data ISEEapp:一个事件解释原型，弥合了传感器网络和文档语料库数据之间的差距

2022 18th International Conference on Intelligent Environments (IE) Pub Date : 2022-06-20 DOI: 10.1109/ie54923.2022.9826763

Nabila Guennouni, Sébastien Laborie, C. Sallaberry, R. Chbeir, Elio Mansour

引用次数: 0