Jianming Zhang, Zhuofan Zheng, Xianding Xie, Yan Gui, Gwang-Jun Kim
Traffic sign detection is a challenging task. Although existing deep learning techniques have made great progress in detecting traffic signs, there are still many unsolved challenges. We propose a novel traffic sign detection network named ReYOLO that learns rich contextual information and senses scale variations to efficiently detect small and ambiguous traffic signs in the wild. Specifically, we first replace the conventional convolutional block with modules that are built by structural reparameterization methods and are embedded into bigger structures, thus decoupling the training structures and the inference structures using parameter transformation, and allowing the model to learn more effective features. We then design a novel weighting mechanism which can be embedded into a feature pyramid to exploit foreground features at different scales to narrow the semantic gap between multiple scales. To fully evaluate the proposed method, we conduct experiments on a traditional traffic sign dataset GTSDB as well as two new traffic sign datasets TT100K and CCTSDB2021, achieving 97.2%, 68.3% and 83.9% mAP (Mean Average Precision) for the three-class detection challenge in these three datasets.
交通标志检测是一项具有挑战性的任务。尽管现有的深度学习技术在检测交通标志方面取得了很大进展，但仍有许多未解决的挑战。我们提出了一种新的交通标志检测网络ReYOLO，它可以学习丰富的上下文信息并感知尺度变化，从而有效地检测出小型和模糊的交通标志。具体来说，我们首先用结构重参数化方法构建的模块取代传统的卷积块，并嵌入到更大的结构中，从而使用参数变换将训练结构和推理结构解耦，并允许模型学习更有效的特征。然后，我们设计了一种新的加权机制，该机制可以嵌入到特征金字塔中，以利用不同尺度的前景特征来缩小多尺度之间的语义差距。为了充分评估所提出的方法，我们在传统的交通标志数据集GTSDB以及两个新的交通标志数据集TT100K和CCTSDB2021上进行了实验，对这三个数据集的三类检测挑战实现了97.2%，68.3%和83.9%的mAP (Mean Average Precision)。
{"title":"ReYOLO: A traffic sign detector based on network reparameterization and features adaptive weighting","authors":"Jianming Zhang, Zhuofan Zheng, Xianding Xie, Yan Gui, Gwang-Jun Kim","doi":"10.3233/ais-220038","DOIUrl":"https://doi.org/10.3233/ais-220038","url":null,"abstract":"Traffic sign detection is a challenging task. Although existing deep learning techniques have made great progress in detecting traffic signs, there are still many unsolved challenges. We propose a novel traffic sign detection network named ReYOLO that learns rich contextual information and senses scale variations to efficiently detect small and ambiguous traffic signs in the wild. Specifically, we first replace the conventional convolutional block with modules that are built by structural reparameterization methods and are embedded into bigger structures, thus decoupling the training structures and the inference structures using parameter transformation, and allowing the model to learn more effective features. We then design a novel weighting mechanism which can be embedded into a feature pyramid to exploit foreground features at different scales to narrow the semantic gap between multiple scales. To fully evaluate the proposed method, we conduct experiments on a traditional traffic sign dataset GTSDB as well as two new traffic sign datasets TT100K and CCTSDB2021, achieving 97.2%, 68.3% and 83.9% mAP (Mean Average Precision) for the three-class detection challenge in these three datasets.","PeriodicalId":49316,"journal":{"name":"Journal of Ambient Intelligence and Smart Environments","volume":"19 7 1","pages":"317-334"},"PeriodicalIF":1.7,"publicationDate":"2022-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81265570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the commencement of new technologies like IoT and the Cloud, the sources of data generation have increased exponentially. The use and processing of this generated data have motivated and given birth to many other domains. The concept of a smart city has also evolved from making use of this data in decision-making in the various aspects of daily life and also improvement in the traditional systems. In smart cities, various technologies work collaboratively; they include devices used for data collection, processing, storing, retrieval, analysis, and decision making. Big data storage, retrieval, and analysis play a vital role in smart city applications. Traditional data processing approaches face many challenges when dealing with such voluminous and high-speed generated data, such as semi-structured or unstructured data, data privacy, security, real-time responses, and so on. Probabilistic Data Structures (PDS) has been evolved as a potential solution for many applications in smart cities to complete this tedious task of handling big data with real-time response. PDS has been used in many smart city domains, including healthcare, transportation, the environment, energy, and industry. The goal of this paper is to provide a comprehensive review of PDS and its applications in the domains of smart cities. The prominent domain of the smart city has been explored in detail; origin, current research status, challenges, and existing application of PDS along with research gaps and future directions. The foremost aim of this paper is to provide a detailed survey of PDS in smart cities; for readers and researchers who want to explore this field; along with the research opportunities in the domains.
{"title":"Probabilistic data structures in smart city: Survey, applications, challenges, and research directions","authors":"Mandeep Kumar, Amritpal Singh","doi":"10.3233/ais-220101","DOIUrl":"https://doi.org/10.3233/ais-220101","url":null,"abstract":"With the commencement of new technologies like IoT and the Cloud, the sources of data generation have increased exponentially. The use and processing of this generated data have motivated and given birth to many other domains. The concept of a smart city has also evolved from making use of this data in decision-making in the various aspects of daily life and also improvement in the traditional systems. In smart cities, various technologies work collaboratively; they include devices used for data collection, processing, storing, retrieval, analysis, and decision making. Big data storage, retrieval, and analysis play a vital role in smart city applications. Traditional data processing approaches face many challenges when dealing with such voluminous and high-speed generated data, such as semi-structured or unstructured data, data privacy, security, real-time responses, and so on. Probabilistic Data Structures (PDS) has been evolved as a potential solution for many applications in smart cities to complete this tedious task of handling big data with real-time response. PDS has been used in many smart city domains, including healthcare, transportation, the environment, energy, and industry. The goal of this paper is to provide a comprehensive review of PDS and its applications in the domains of smart cities. The prominent domain of the smart city has been explored in detail; origin, current research status, challenges, and existing application of PDS along with research gaps and future directions. The foremost aim of this paper is to provide a detailed survey of PDS in smart cities; for readers and researchers who want to explore this field; along with the research opportunities in the domains.","PeriodicalId":49316,"journal":{"name":"Journal of Ambient Intelligence and Smart Environments","volume":"124 1","pages":"229-284"},"PeriodicalIF":1.7,"publicationDate":"2022-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80433475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The main aim of this work is to implement a progressive path-planning algorithm with a proposed hybrid network based CNC-C (Cooperative Network Coded–Communication) architecture for a smart evacuation system. An algorithm ALCDTS (Health based Age–Length–Capacity–Distance–Trustiness–Speed) is proposed to generate possible progressive routes by considering the building conditions, hazard estimation, path capacity along with the occupant’s age, speed and health status. The investigation of ALCDTS is carried out by using the path finder simulator. The comparative study between the conventional evacuation algorithm and ALCDTS algorithm has been performed and the results are obtained. A four-storied shopping mall is taken as a building model where the performance of test cases for abnormal event is analysed.
{"title":"Smart building evacuation system with hybrid network based CNC-C architecture","authors":"P. Raja, C. Arunachalaperumal, M. Divya","doi":"10.3233/ais-210427","DOIUrl":"https://doi.org/10.3233/ais-210427","url":null,"abstract":"The main aim of this work is to implement a progressive path-planning algorithm with a proposed hybrid network based CNC-C (Cooperative Network Coded–Communication) architecture for a smart evacuation system. An algorithm ALCDTS (Health based Age–Length–Capacity–Distance–Trustiness–Speed) is proposed to generate possible progressive routes by considering the building conditions, hazard estimation, path capacity along with the occupant’s age, speed and health status. The investigation of ALCDTS is carried out by using the path finder simulator. The comparative study between the conventional evacuation algorithm and ALCDTS algorithm has been performed and the results are obtained. A four-storied shopping mall is taken as a building model where the performance of test cases for abnormal event is analysed.","PeriodicalId":49316,"journal":{"name":"Journal of Ambient Intelligence and Smart Environments","volume":"1 1","pages":"335-347"},"PeriodicalIF":1.7,"publicationDate":"2022-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77225611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Several computing paradigms have emerged along the years integrated with the Internet of Things (IoT) as the base to realize the complex hyperspace associated to the ubiquitous Cyber-Physical-Social-Thinking hyperspace that society expects. An overlap of the principles that define those paradigms exists and, despite of previous efforts, a unified and appropriate definition of each of them is still a challenge. Therefore, the purpose of this work is to survey the existing literature about IoT and their related paradigms to obtain a model that provides a definition usable to guide in the selection of that paradigm that fits better the requirements of the system-to-be. For this aim, a rigorous and systematic Thematic Synthesis has been conducted to analyze the most relevant studies of the selected paradigms and specify a model that integrates their definitions, their relations and differences. Furthermore, Cyber-Physical-Social Systems (CPSS) has been identified as the paradigm focusing on social and human factors that better realizes the complex hyperspace of the smart world since it entails relevant and convenient aspects from other paradigms.
多年来出现了几种与物联网(IoT)相结合的计算范式，作为实现与社会所期望的无处不在的网络-物理-社会-思维超空间相关的复杂超空间的基础。定义这些范例的原则存在重叠，尽管以前作出了努力，但对每一个范例进行统一和适当的定义仍然是一项挑战。因此，这项工作的目的是调查现有的关于物联网及其相关范式的文献，以获得一个模型，该模型提供了一个可用于指导选择更适合系统需求的范式的定义。为此，本文进行了严格而系统的主题综合，分析了所选范式中最相关的研究，并提出了一个整合它们的定义、关系和差异的模型。此外，Cyber-Physical-Social Systems (CPSS)被认为是关注社会和人为因素的范式，因为它需要其他范式的相关和便利方面，因此可以更好地实现智能世界的复杂超空间。
{"title":"Paradigms for the conceptualization of Cyber-Physical-Social-Thinking hyperspace: A Thematic Synthesis","authors":"Aurora Macías, Elena Navarro","doi":"10.3233/ais-210492","DOIUrl":"https://doi.org/10.3233/ais-210492","url":null,"abstract":"Several computing paradigms have emerged along the years integrated with the Internet of Things (IoT) as the base to realize the complex hyperspace associated to the ubiquitous Cyber-Physical-Social-Thinking hyperspace that society expects. An overlap of the principles that define those paradigms exists and, despite of previous efforts, a unified and appropriate definition of each of them is still a challenge. Therefore, the purpose of this work is to survey the existing literature about IoT and their related paradigms to obtain a model that provides a definition usable to guide in the selection of that paradigm that fits better the requirements of the system-to-be. For this aim, a rigorous and systematic Thematic Synthesis has been conducted to analyze the most relevant studies of the selected paradigms and specify a model that integrates their definitions, their relations and differences. Furthermore, Cyber-Physical-Social Systems (CPSS) has been identified as the paradigm focusing on social and human factors that better realizes the complex hyperspace of the smart world since it entails relevant and convenient aspects from other paradigms.","PeriodicalId":49316,"journal":{"name":"Journal of Ambient Intelligence and Smart Environments","volume":"70 1","pages":"285-316"},"PeriodicalIF":1.7,"publicationDate":"2022-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82862755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, Virtual Assistive Smart Eyes (VASE) is described which introduces a new advanced smart glass technology for the visually impaired. Smart glasses in general, have come up as the most calculative device in the modern age to amalgamate humans and machines with the help of machine learning and information technology. These devices are frequently used in industries like medicine and gaming, but their exploration in the field of assistive technology, specifically for the visually impaired is very limited. Majority of these devices are focusing on only a fraction of the features required. It is unfair to leave the average person no choice but to invest in products that are expensive and are not covering all aspects of the problems faced, that they would need to be autonomous in their every-day lives. The proposed VASE is a cost-effective pair of smart glasses which includes many features such as obstruction detection and object recognition. VASE would immensely benefit the visually impaired people in doing their daily tasks and lead an independent life. It will impact the society enormously, as it aids in the prevention of accidents and any other unfortunate incidents, bringing about a major technological advancement benefiting the whole world.
{"title":"VASE: Smart glasses for the visually impaired","authors":"Seemu Sharma, Nidhi Kalra, Lavanya Gupta, Neha Varma, Srishti Agrawal, Vipasha Verma","doi":"10.3233/ais-210491","DOIUrl":"https://doi.org/10.3233/ais-210491","url":null,"abstract":"In this paper, Virtual Assistive Smart Eyes (VASE) is described which introduces a new advanced smart glass technology for the visually impaired. Smart glasses in general, have come up as the most calculative device in the modern age to amalgamate humans and machines with the help of machine learning and information technology. These devices are frequently used in industries like medicine and gaming, but their exploration in the field of assistive technology, specifically for the visually impaired is very limited. Majority of these devices are focusing on only a fraction of the features required. It is unfair to leave the average person no choice but to invest in products that are expensive and are not covering all aspects of the problems faced, that they would need to be autonomous in their every-day lives. The proposed VASE is a cost-effective pair of smart glasses which includes many features such as obstruction detection and object recognition. VASE would immensely benefit the visually impaired people in doing their daily tasks and lead an independent life. It will impact the society enormously, as it aids in the prevention of accidents and any other unfortunate incidents, bringing about a major technological advancement benefiting the whole world.","PeriodicalId":49316,"journal":{"name":"Journal of Ambient Intelligence and Smart Environments","volume":"8 1","pages":"213-226"},"PeriodicalIF":1.7,"publicationDate":"2022-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89705876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. R. Domínguez, Carlos Lino Ramírez, David Asael Gutiérrez Hernández, Héctor José Puga Soberanes, V. Zamudio
An intelligent system intended to provide assistance to an elderly user in their home is presented. This multi-agent system is designed to monitor the interaction between the user and other agents, and regulate itself based on the estimated level of mental engagement of the user in order to contribute to help them maintain adequate levels of awareness and interaction with their home environment. The agents are devices programmed to preserve the security, comfort and health of the user, who is also conceptualized as one of the agents in the system. The user engagement level is estimated through fuzzy inference, that is, by means of a set of fuzzy membership functions and rules applied over the interaction of the user with different categories of agents. The system incorporates several dozen agents and is tested using two different datasets of real interactions between users and devices in their home environments. A uniform parameter configuration yielded very positive results for diverse scenarios and subsequently the parameters of the system were automatically optimized to show that improved performance, in the form of a more efficient system regulation and increased certainty in adjustment estimation, is obtained.
{"title":"Fuzzy multi-agent assistance system for elderly care based on user engagement","authors":"A. R. Domínguez, Carlos Lino Ramírez, David Asael Gutiérrez Hernández, Héctor José Puga Soberanes, V. Zamudio","doi":"10.3233/ais-210312","DOIUrl":"https://doi.org/10.3233/ais-210312","url":null,"abstract":"An intelligent system intended to provide assistance to an elderly user in their home is presented. This multi-agent system is designed to monitor the interaction between the user and other agents, and regulate itself based on the estimated level of mental engagement of the user in order to contribute to help them maintain adequate levels of awareness and interaction with their home environment. The agents are devices programmed to preserve the security, comfort and health of the user, who is also conceptualized as one of the agents in the system. The user engagement level is estimated through fuzzy inference, that is, by means of a set of fuzzy membership functions and rules applied over the interaction of the user with different categories of agents. The system incorporates several dozen agents and is tested using two different datasets of real interactions between users and devices in their home environments. A uniform parameter configuration yielded very positive results for diverse scenarios and subsequently the parameters of the system were automatically optimized to show that improved performance, in the form of a more efficient system regulation and increased certainty in adjustment estimation, is obtained.","PeriodicalId":49316,"journal":{"name":"Journal of Ambient Intelligence and Smart Environments","volume":"11 1","pages":"173-194"},"PeriodicalIF":1.7,"publicationDate":"2022-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88747566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alexandre Beaulieu, Florentin Thullier, K. Bouchard, Julien Maître, S. Gaboury
The world population is aging in the last few years and this trend is expected to increase in the future. The number of persons requiring assistance in their everyday life is also expected to rise. Luckily, smart homes are becoming a more and more compelling alternative to direct human supervision. Smart homes are equipped with sensors that, coupled with Artificial Intelligence (AI), can support their occupants whenever needed. At the heart of the problem is the recognition of activities. Human activity recognition is a complex problem due to the variety of sensors available, their impact on privacy, the high number of possible activities, and the several ways even a simple activity can be performed. This paper proposes a deep learning model combining LSTM and a tuned version of the EfficientNet model using transfer learning, data fusion, minimalist pre-processing as well as training for both activity and movement recognition using data from three ultra-wideband (UWB) radars. As regards activity recognition, experiments were conducted in a real and furnished apartment where 15 different activities were performed by 10 participants. Results showed an improvement of 18.63% over previous work on the same dataset with 65.59% in Top-1 accuracy using Leave-One-Subject-Out cross validation. Furthermore, the experiments that address movement recognition were conducted under the same conditions where a single participant was asked to perform four distinct arm movements with the three UWB radars positioned at two different heights. With an overall accuracy of 73% in Top-1, the detailed analysis of the results obtained showed that the proposed model was capable of recognizing accurately large and fine-grained movements. However, the medium-sized movements demonstrated a significant impact on the movement recognition due to an insufficient degree of variation between the four proposed movements.
{"title":"Ultra-wideband data as input of a combined EfficientNet and LSTM architecture for human activity recognition","authors":"Alexandre Beaulieu, Florentin Thullier, K. Bouchard, Julien Maître, S. Gaboury","doi":"10.3233/ais-210462","DOIUrl":"https://doi.org/10.3233/ais-210462","url":null,"abstract":"The world population is aging in the last few years and this trend is expected to increase in the future. The number of persons requiring assistance in their everyday life is also expected to rise. Luckily, smart homes are becoming a more and more compelling alternative to direct human supervision. Smart homes are equipped with sensors that, coupled with Artificial Intelligence (AI), can support their occupants whenever needed. At the heart of the problem is the recognition of activities. Human activity recognition is a complex problem due to the variety of sensors available, their impact on privacy, the high number of possible activities, and the several ways even a simple activity can be performed. This paper proposes a deep learning model combining LSTM and a tuned version of the EfficientNet model using transfer learning, data fusion, minimalist pre-processing as well as training for both activity and movement recognition using data from three ultra-wideband (UWB) radars. As regards activity recognition, experiments were conducted in a real and furnished apartment where 15 different activities were performed by 10 participants. Results showed an improvement of 18.63% over previous work on the same dataset with 65.59% in Top-1 accuracy using Leave-One-Subject-Out cross validation. Furthermore, the experiments that address movement recognition were conducted under the same conditions where a single participant was asked to perform four distinct arm movements with the three UWB radars positioned at two different heights. With an overall accuracy of 73% in Top-1, the detailed analysis of the results obtained showed that the proposed model was capable of recognizing accurately large and fine-grained movements. However, the medium-sized movements demonstrated a significant impact on the movement recognition due to an insufficient degree of variation between the four proposed movements.","PeriodicalId":49316,"journal":{"name":"Journal of Ambient Intelligence and Smart Environments","volume":"1 1","pages":"157-172"},"PeriodicalIF":1.7,"publicationDate":"2022-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83910800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Arthur Desuert, Stéphanie Chollet, Laurent Pion, D. Hély
Connected devices are deployed at a rapid rate and in broad domains like home automation or industry, forming the Internet of Things. Those devices need to be secure and trusted to prevent malicious use. However some connected devices are low-cost, memory constrained, power constrained, etc.. This greatly limits the deployment of usual security solutions. As the absence of security is not acceptable, it is necessary to search for lightweight security solutions adapted to such devices. Physical Unclonable Function (PUF) technology can support new lightweight security mechanisms and several lightweight security protocols using this technology have been proposed over the years. Those protocols look promising, however there are still some unaddressed challenges which have slowed down a large scale adoption. This article presents the design of a new authentication protocol for constrained devices which takes into account those challenges. This protocol is implemented on a hardware platform used for connected devices development, which is then used to evaluate the security level and performances of the protocol in a realistic scenario. This evaluation shows that the protocol is secure and can meet industrial time constraints.
{"title":"Refillable PUF authentication protocol for constrained devices","authors":"Arthur Desuert, Stéphanie Chollet, Laurent Pion, D. Hély","doi":"10.3233/ais-210325","DOIUrl":"https://doi.org/10.3233/ais-210325","url":null,"abstract":"Connected devices are deployed at a rapid rate and in broad domains like home automation or industry, forming the Internet of Things. Those devices need to be secure and trusted to prevent malicious use. However some connected devices are low-cost, memory constrained, power constrained, etc.. This greatly limits the deployment of usual security solutions. As the absence of security is not acceptable, it is necessary to search for lightweight security solutions adapted to such devices. Physical Unclonable Function (PUF) technology can support new lightweight security mechanisms and several lightweight security protocols using this technology have been proposed over the years. Those protocols look promising, however there are still some unaddressed challenges which have slowed down a large scale adoption. This article presents the design of a new authentication protocol for constrained devices which takes into account those challenges. This protocol is implemented on a hardware platform used for connected devices development, which is then used to evaluate the security level and performances of the protocol in a realistic scenario. This evaluation shows that the protocol is secure and can meet industrial time constraints.","PeriodicalId":49316,"journal":{"name":"Journal of Ambient Intelligence and Smart Environments","volume":"153 1","pages":"195-212"},"PeriodicalIF":1.7,"publicationDate":"2022-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78193017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Indoor Air Quality Assessment for Smart Environments","authors":"","doi":"10.3233/aise30","DOIUrl":"https://doi.org/10.3233/aise30","url":null,"abstract":"","PeriodicalId":49316,"journal":{"name":"Journal of Ambient Intelligence and Smart Environments","volume":"31 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2022-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89978747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Preface to JAISE 14(2)","authors":"Hamid Aghajan,Juan Carlos Augusto,Andrés Muñoz","doi":"10.3233/ais-220622","DOIUrl":"https://doi.org/10.3233/ais-220622","url":null,"abstract":"","PeriodicalId":49316,"journal":{"name":"Journal of Ambient Intelligence and Smart Environments","volume":"93 1-2","pages":"77-78"},"PeriodicalIF":1.7,"publicationDate":"2022-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138525290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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