Journal of Ambient Intelligence and Smart Environments最新文献_第2页

Erratum to: Energy-efficient multisensor adaptive sampling and aggregation for patient monitoring in edge computing based IoHT networks1 勘误：高能效多传感器自适应采样和聚合，用于基于边缘计算的物联网医院网络中的患者监测1

IF 1.7 4区计算机科学

Journal of Ambient Intelligence and Smart Environments Pub Date : 2023-11-07 DOI: 10.3233/ais-235005

Ali Kadhum Idrees, Duaa Abd Alhussein, Hassan Harb

引用次数: 0

Wavelet-based temporal models of human activity for anomaly detection in smart robot-assisted environments1 基于小波的人类活动时间模型在智能机器人辅助环境中的异常检测[j]

4区计算机科学

Journal of Ambient Intelligence and Smart Environments Pub Date : 2023-11-03 DOI: 10.3233/ais-230144

Manuel Fernandez-Carmona, Sariah Mghames, Nicola Bellotto

{"title":"Wavelet-based temporal models of human activity for anomaly detection in smart robot-assisted environments1","authors":"Manuel Fernandez-Carmona, Sariah Mghames, Nicola Bellotto","doi":"10.3233/ais-230144","DOIUrl":"https://doi.org/10.3233/ais-230144","url":null,"abstract":"Detecting anomalies in patterns of sensor data is important in many practical applications, including domestic activity monitoring for Active Assisted Living (AAL). How to represent and analyse these patterns, however, remains a challenging task, especially when data is relatively scarce and an explicit model is required to be fine-tuned for specific scenarios. This paper, therefore, presents a new approach for temporal modelling of long-term human activities with smart-home sensors, which is used to detect anomalous situations in a robot-assisted environment. The model is based on wavelet transforms and used to forecast smart sensor data, providing a temporal prior to detect unexpected events in human environments. To this end, a new extension of Hybrid Markov Logic Networks has been developed that merges different anomaly indicators, including activities detected by binary sensors, expert logic rules, and wavelet-based temporal models. The latter in particular allows the inference system to discover deviations from long-term activity patterns, which cannot be detected by simpler frequency-based models. Two new publicly available datasets were collected using several smart-sensors to evaluate the approach in office and domestic scenarios. The experimental results demonstrate the effectiveness of the proposed solutions and their successful deployment in complex human environments, showing their potential for future smart-home and robot integrated services.","PeriodicalId":49316,"journal":{"name":"Journal of Ambient Intelligence and Smart Environments","volume":"15 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135868366","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}

引用次数: 0

IoT forensics in ambient intelligence environments: Legal issues, research challenges and future directions 环境智能环境中的物联网取证:法律问题、研究挑战和未来方向

4区计算机科学

Journal of Ambient Intelligence and Smart Environments Pub Date : 2023-10-31 DOI: 10.3233/ais-220511

Pankaj Sharma, Lalit Kumar Awasthi

{"title":"IoT forensics in ambient intelligence environments: Legal issues, research challenges and future directions","authors":"Pankaj Sharma, Lalit Kumar Awasthi","doi":"10.3233/ais-220511","DOIUrl":"https://doi.org/10.3233/ais-220511","url":null,"abstract":"Due to the abundance of the Internet of Things (IoT), smart devices are widely utilized which helps to manage human surroundings and senses inside and outside environments. The huge amount of data generated from the IoT device attracts cyber-criminals in order to gain information from the significant relationship between people and smart devices. Cyber-attacks on IoT pose a severe challenge for forensic experts. Researchers have invented many techniques to solve IoT forensic challenges and to have an in-depth knowledge of all the facts internal as-well-as external architecture of IoT needs to be understood. In this paper, an attempt has been made to understand the relationship between security and forensics incorporating its strengths and weaknesses, which has not been explored till date to the best of our knowledge. An attempt has also been made to classify literature into three categories: physical level, network level, and cloud level. These include evidence sources, areas of IoT forensics, potential forensic information, evidence extraction techniques, investigation procedures, and legal issues. Also, some prominent IoT forensic use cases have been recited along with providing the key requirements for forensic investigation. Finally, possible research problems in IoT forensic have been identified.","PeriodicalId":49316,"journal":{"name":"Journal of Ambient Intelligence and Smart Environments","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135870441","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}

引用次数: 0

Research on human sleep improvement method based on DQN 基于DQN的人类睡眠改善方法研究

4区计算机科学

Journal of Ambient Intelligence and Smart Environments Pub Date : 2023-10-26 DOI: 10.3233/ais-230294

Yunzhi Tian, Qiang Zhou, Wan Li

引用次数: 0

Imbalance-learning road crash assessment under reduced visibility settings: A proactive multicriteria decision-making system 低能见度环境下的不平衡学习道路碰撞评估:一个主动的多标准决策系统

4区计算机科学

Journal of Ambient Intelligence and Smart Environments Pub Date : 2023-10-25 DOI: 10.3233/ais-230127

Zouhair Elamrani Abou Elassad, Dauha Elamrani Abou Elassad, Hajar Mousannif

{"title":"Imbalance-learning road crash assessment under reduced visibility settings: A proactive multicriteria decision-making system","authors":"Zouhair Elamrani Abou Elassad, Dauha Elamrani Abou Elassad, Hajar Mousannif","doi":"10.3233/ais-230127","DOIUrl":"https://doi.org/10.3233/ais-230127","url":null,"abstract":"Road crash prediction is a fundamental key in designing efficient intelligent transportation systems. There has been a pronounced progress in the use of machine learning models for crash events assessment by the transportation safety research community in recent years. However, little attention has been paid so far to evaluating reduced-visibility crash occurrences within a heuristic ensemble system. This study presents a proactive multicriteria decision-making system that can predict crash occurrences based on real-time roadway properties, land zones’ characteristics, vehicle telemetry, driver inputs and weather conditions collected using a desktop driving simulator. A key novelty of this work is implementing a genetic algorithm-based feature selection approach along with ensemble modeling strategies using AdaBoost, XGBoost and RF techniques to establish effective crash predictions. Furthermore, since crash events occur in rare instances tending to be underrepresented in the dataset, an imbalance-learning methodology to overcome the issue was adopted on the basis of several data resampling approaches to increase the predictive performance namely SMOTE, Borderline-SMOTE, SMOTE-Tomek Links and ADASYN strategies. To our knowledge, there has been a limited interest at adopting an ensemble-based imbalance-learning strategy examining the impact of real-time features’ combinations on the prediction of road crash events under reduced visibility settings.","PeriodicalId":49316,"journal":{"name":"Journal of Ambient Intelligence and Smart Environments","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135167096","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}

引用次数: 0

Design and implementation of hybrid low power wide area network architecture for IoT applications 物联网应用的混合低功耗广域网架构设计与实现

4区计算机科学

Journal of Ambient Intelligence and Smart Environments Pub Date : 2023-10-24 DOI: 10.3233/ais-230146

B. Shilpa, Rajesh Kumar Jha, Vaibhav Naware, Anuradha Vattem, Aftab M. Hussain

{"title":"Design and implementation of hybrid low power wide area network architecture for IoT applications","authors":"B. Shilpa, Rajesh Kumar Jha, Vaibhav Naware, Anuradha Vattem, Aftab M. Hussain","doi":"10.3233/ais-230146","DOIUrl":"https://doi.org/10.3233/ais-230146","url":null,"abstract":"The rapid proliferation of Internet of Things (IoT) devices and applications has resulted in an increasing demand for Low Power and Wide Area Network (LPWAN) solutions. The adoption of IoT networks still faces several challenges, despite the rapid advancement of low-power communication technology. Homogenizing this sector requires allowing interoperability between many technologies, which is now one of the largest obstacles. In this article, we present the design and implementation of the hybrid LPWAN architecture that can accomplish wide-area communication coverage and low-power consumption for IoT applications by leveraging two LPWAN technologies, Wireless Smart Ubiquitous Network (Wi-SUN) and Long Range (LoRa). In particular, LoRa is used for long-range communication, and Wi-SUN for a low-latency mesh network. Additionally, we implemented smart street light controlling system as a real-world deployment at the university campus to showcase the efficiency of the hybrid network. Our results demonstrate that the hybrid LPWAN architecture provides a better coverage and capacity while consuming less power than that of the LoRa or Wi-SUN network. The results of this study demonstrate the effectiveness of the proposed hybrid LPWAN architecture as a viable solution for next-generation IoT applications.","PeriodicalId":49316,"journal":{"name":"Journal of Ambient Intelligence and Smart Environments","volume":"4 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135316250","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}

引用次数: 0

Improving resource recycling based on deep learning 改进基于深度学习的资源回收

4区计算机科学

Journal of Ambient Intelligence and Smart Environments Pub Date : 2023-10-24 DOI: 10.3233/ais-230124

Yunjian Xu, Aiyin Guo

引用次数: 0

Applications in integrated intelligent infrastructures 集成智能基础设施的应用

IF 1.7 4区计算机科学

Journal of Ambient Intelligence and Smart Environments Pub Date : 2023-08-30 DOI: 10.3233/ais-235004

Carles Gomez, Brenda Bannan, Anthony Fleury

引用次数: 0

Preface to JAISE 15(3) JAISE 15(3)序言

IF 1.7 4区计算机科学

Journal of Ambient Intelligence and Smart Environments Pub Date : 2023-08-30 DOI: 10.3233/ais-235003

Andrés Muñoz, J. Augusto, H. Aghajan

引用次数: 0

A new long short-term memory based approach for soil moisture prediction 基于长短期记忆的土壤水分预测新方法

IF 1.7 4区计算机科学

Journal of Ambient Intelligence and Smart Environments Pub Date : 2023-08-23 DOI: 10.3233/ais-230035

Bamory Koné, Rima Grati, Bassem Bouaziz, Khouloud Boukadi

{"title":"A new long short-term memory based approach for soil moisture prediction","authors":"Bamory Koné, Rima Grati, Bassem Bouaziz, Khouloud Boukadi","doi":"10.3233/ais-230035","DOIUrl":"https://doi.org/10.3233/ais-230035","url":null,"abstract":"Water scarcity is becoming more severe around the world as a result of suboptimal irrigation practices. Effective irrigation scheduling necessitates an estimation of future soil moisture content. This study presents deep learning models such as CNN-LSTM, a hybrid Deep Learning model that predicts future soil moisture using climate and soil information, including past soil moisture content. The study also investigates the appropriate number of observations and data sampling rate required to predict the next day’s soil moisture value. In terms of MSE, MAE, RMSE, and R 2 , the hybrid CNN-LSTM model is compared to standalone LSTM and Bi-LSTM models. The LSTM model achieved an MSE of 0.2471, MAE of 0.1978, RMSE of 0.4971, and R 2 of 0.9714. The LSTM model outperformed the Bi-LSTM model, which had an MSE of 0.3036, MAE of 0.3248, RMSE of 0.5510, and R 2 of 0.9614. With an MSE of 0.1348, MAE of 0.1868, RMSE of 0.3672, and R 2 of 0.9838, the hybrid CNN-LSTM model outperformed the LSTM. Our findings suggest that deep learning models, particularly the Convolutional LSTM, hold great potential for predicting soil moisture accurately. The Convolutional LSTM model’s superior performance can be attributed to its ability to capture spatial dependencies in soil moisture data. Furthermore, the results show that for better prediction, sub-hourly data samples from the previous three days should be considered.","PeriodicalId":49316,"journal":{"name":"Journal of Ambient Intelligence and Smart Environments","volume":"15 1","pages":"255-268"},"PeriodicalIF":1.7,"publicationDate":"2023-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69735521","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}

引用次数: 1