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Low-cost IoT-enabled indoor air quality monitoring systems: A systematic review J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2024-02-01 João Peixe, Gonçalo Marques
Indoor air quality (IAQ) is a critical challenge much less controlled in comparison with outdoor air quality. Bad IAQ is related to significant health complications such as respiratory problems, heart disease, and cancer. Many people spend most of their days inside buildings and don’t have air quality monitoring systems. Therefore, the occupants don’t know when the space has a higher quantity of pollutants
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Systematic review of motion capture in virtual reality: Enhancing the precision of sports training J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2024-01-22 Xiaohui Li, Dongfang Fan, Junjie Feng, Yu Lei, Chao Cheng, Xiangnan Li
In the modern era of sports training, the synergy between motion capture and Virtual Reality (VR) offers an innovative approach to enhancing training precision. This systematic review delves into the application of motion capture within VR for sports training, highlighting its transformative potential. Through a comprehensive literature search, we examined the myriad applications, from physical conditioning
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Methods for volume inference of non-medical objects from images: A short review J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2024-01-17 Baticté Nabitchita, Norberto Jorge Gonçalves, Paulo Jorge Coelho, Luís Pimenta, Eftim Zdravevski, Petre Lameski, Mónica Costa, Paulo Alexandre Neves, Ivan Miguel Pires
Nowadays, the object’s volume is essential for monitoring any scene. Technological equipment is evolving, and mobile devices and other devices embed high-resolution cameras. The high-resolution cameras open a window for different research studies, where the volume measurement is vital for differentareas. This study aims to identify image processing techniques for measuring the object’s volume. Thus
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Hybrid fuzzy response threshold-based distributed task allocation in heterogeneous multi-robot environment J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2023-12-15 Dani Reagan Vivek Joseph, Shantha Selvakumari Ramapackiyam
Task allocation is a vital challenge in a multi-robot environment. A hybrid fuzzy response threshold-based method is proposed to address the problem of task allocation in a heterogeneous mobile robot environment. The method follows a distributed task allocation approach where every robot chooses its task and performs it, resulting in concurrent execution. The algorithm uses a fuzzy inference system
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From programming-to-modeling-to-prompts smart ubiquitous applications J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2023-12-12 Mohammed Fethi Khalfi, Mohammed Nadjib Tabbiche, Reda Adjoudj
Since its introduction by Mark Weiser, ubiquitous computing has received increased interest in the dawn of technological advancement. Supported by wireless technology advancement, embedded systems, miniaturization, and the integration of various intelligent and communicative devise, context-aware ubiquitous applications actively and intelligently use rich contextual information to assist their users
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A UAV deployment strategy based on a probabilistic data coverage model for mobile CrowdSensing applications J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2023-12-08 Michele Girolami, Erminia Cipullo, Tommaso Colella, Stefano Chessa
Mobile CrowdSensing (MCS) is a computational paradigm designed to gather sensing data by using personal devices of MCS platform users. However, being the mobility of devices tightly correlated with mobility of their owners, the locations from which data are collected might be limited to specific sub-regions. We extend the data coverage capability of a traditional MCS platform by exploiting unmanned
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Memoization based priority-aware task management for QoS provisioning in IoT gateways J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2023-12-05 Gunjan Beniwal, Anita Singhrova
Fog computing is a paradigm that works in tandem with cloud computing. The emergence of fog computing has boosted cloud-based computation, especially in the case of delay-sensitive tasks, as the fog is situated closer to end devices such as sensors that generate data. While scheduling tasks, the fundamental issue is allocating resources to the fog nodes. With the ever-growing demands of the industry
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Technologies for monitoring patients with Alzheimer’s disease: A systematic mapping study and taxonomy J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2023-11-23 Savanna Denega Machado, João Elison da Rosa Tavares, Jorge Luis Victória Barbosa
Alzheimer’s Disease (AD) is an incurable disease and a type of dementia. About 55 million people around the world have AD. However, technologies have been used to assist in the healthcare of AD, supporting physicians in the palliative care of patients. This article presents a systematic mapping study (SMS) to identify articles that use technologies to monitor patients with AD in order to show an overview
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An automated energy management framework for smart homes J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2023-11-17 Houssam Kanso, Adel Noureddine, Ernesto Exposito
Over the last fifty years, societies across the world have experienced multiple periods of energy insufficiency with the most recent one being the 2022 global energy crisis. In addition, the electric power industry has been experiencing a steady increase in electricity consumption since the secondindustrial revolution because of the widespread usage of electrical appliances and devices. Newer devices
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Performance of matrix completion approaches for aquaponics data J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2023-11-16 Nandesh O N, Rikitha Shetty, Saniha Alva, Aditi Paul, Pallaviram Sure
Technological innovations in Internet of Things (IoT) have resulted in smart agricultural solutions such as a remotely monitored Aquaponics system and a wireless sensor network (WSN) of such systems (nodes). IoT enables continuous sensing of temperature and pH data at each node of the WSN, which isperiodically transmitted to a remote fusion centre. In this regard, the data matrices acquired at the
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Wavelet-domain human activity recognition utilizing convolutional neural networks J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2023-11-16 Mohammad Tavakkoli, Ehsan Nazerfard, Maryam Amirmazlaghani
Human activity recognition (HAR) is a crucial area of research in human-computer interaction. Despite previous efforts in this field, there is still a need for more accurate and robust methods that can handle time-series data from different sensors. In this study, we propose a novel method that generates an image using wavelet transform to extract time-frequency features of the recorded signal. Our
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Wavelet-based temporal models of human activity for anomaly detection in smart robot-assisted environments 1 J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2023-11-03 Manuel Fernandez-Carmona, Sariah Mghames, Nicola Bellotto
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
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IoT forensics in ambient intelligence environments: Legal issues, research challenges and future directions J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2023-10-31 Pankaj Sharma, Lalit Kumar Awasthi
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
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Research on human sleep improvement method based on DQN J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2023-10-26 Yunzhi Tian, Qiang Zhou, Wan Li
To solve the problems of sleep disorders such as difficulty in falling asleep and insufficient sleep depth caused by uncomfortable indoor temperature, this paper proposes a deep reinforcement learning method based on deep Q-network (DQN) with human sleep electroencephalogram (EEG) as input to improve human sleep. Firstly, the EEG is subjected to a short-time Fourier transform to construct a time-frequency
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Design and implementation of hybrid low power wide area network architecture for IoT applications J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2023-10-24 B. Shilpa, Rajesh Kumar Jha, Vaibhav Naware, Anuradha Vattem, Aftab M. Hussain
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
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Improving resource recycling based on deep learning J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2023-10-24 Yunjian Xu, Aiyin Guo
The manual sorting of recyclable garbage has caused several issues such as the wastage of human resources and low resource utilization. To solve this problem, an improved Single Shot Multibox Detector (SSD) deep learning approach has been developed for recyclable garbage detection. To reduce the number of parameters and make the model easier to deploy and apply, a lightweight network called RepVGG
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Imbalance-learning road crash assessment under reduced visibility settings: A proactive multicriteria decision-making system J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2023-10-25 Zouhair Elamrani Abou Elassad, Dauha Elamrani Abou Elassad, Hajar Mousannif
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 hasbeen paid so far to evaluating reduced-visibility crash occurrences within a heuristic ensemble system
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Energy-efficient multisensor adaptive sampling and aggregation for patient monitoring in edge computing based IoHT networks J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2023-09-05 Ali Kadhum Idrees, Duaa Abd Alhussein, Hassan Harb
The need for remote healthcare monitoring systems that utilize limited resources’ biosensors is growing. These biosensors increase the amount of transmitted data across the Internet of Healthcare Things (IoHT) network. Therefore, it is necessary to decrease the transmitted data and make a decisionat the edge gateway to save the energy of the biosensors and produce a quick response for the medical staff
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A new long short-term memory based approach for soil moisture prediction J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2023-09-05 Bamory Ahmed Toru Koné, Rima Grati, Bassem Bouaziz, Khouloud Boukadi
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
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A Petri net oriented approach for advanced building energy management systems J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2023-08-23 Stefano Marrone, Lelio Campanile, Roberta De Fazio, Michele Di Giovanni, Ugo Gentile, Fiammetta Marulli, Laura Verde
Sustainability is one of the main goals to pursue in several aspects of everyday life; the recent energy shortage and the price raise worsen this problem, especially in the management of energy in buildings. As the Internet of Things (IoT) is an assessed computing paradigm able to capture meaningful data from the field and send them to cloud infrastructures, other approaches are also enabled, namely
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Gas mask wearing detection based on faster R-CNN J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2023-08-17 Bangrong Wang, Jun Wang, Xiaofeng Xu, Xianglin Bao
Gas masks are essential respiratory protective equipment commonly used by laborers who work in harsh environments. However, respiratory diseases and accidents can occur due to the absence of gas masks. To prevent these accidents, this paper developed an object detector that uses convolutional neural networks (CNNs) to detect whether workers are wearing gas masks. To achieve this goal, a gas mask detection
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Building information modeling and affective occupancy evaluation: A scoping review J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2023-08-17 José Luis Gómez-Sirvent, Desirée Fernández-Sotos, Francisco López de la Rosa, Antonio Fernández-Caballero
Building Information Modeling (BIM) is a powerful process for creating and managing data throughout the life cycle of a building. Traditionally, measuring the well-being of building occupants has been addressed solely through objective physical variables such as temperature or relative air humidity. However, recent studies indicate that the built environment influences subjective aspects of human well-being
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Adaptive path planning for unknown environment monitoring J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2023-07-31 Nandhagopal Gomathi, Krishnamoorthi Rajathi
The purpose of this paper is to offer a unique adaptive path planning framework to address a new challenge known as the Unknown environment Persistent Monitoring Problem (PMP). To identify the unknown events’ occurrence location and likelihood, an unmanned ground vehicle (UGV) equipped with a LightDetection and Ranging (LIDAR) and camera is used to record such events in agriculture land. A certain
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Prediction-based channel assignment for minimizing channel switching in mobile WBANs J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2023-07-26 Prajna Paramita Pradhan, Sanghita Bhattacharjee
As the world’s population rises, the healthcare system experiences significant changes. Wireless body area network (WBAN) is an emerging technology that has considerable impact on medical and non-medical applications. However, two crucial challenges in WBANs are interference minimization and channel assignment. High interference may increase collision probability, transmission delay, and energy consumption
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Design of a wheeled type in-pipe inspection robot to overcome motion singularity in curved pipes J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2023-07-17 Rajendran Sugin Elankavi, D. Dinakaran, Arockia Selvakumar Arockia Doss, R.M. Kuppan Chetty, M.M. Ramya
This paper discusses the development and design of two wheeled-type In-Pipe Inspection Robots (IPIRs), Kuzhali I and Kuzhali II, which were created to address the limitations of traditional human inspection methods and earlier robot designs. Specifically, the robots aim to overcome the motion singularity experienced by IPIRs when navigating through curved pipes. Kuzhali I was developed with wheels
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PAMDI: Privacy aware missing data inference scheme for sparse mobile crowd sensing J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2023-03-27 Tejendrakumar Thakur, Ningrinla Marchang
The ubiquity of mobile devices has birthed one of the most promising IoT applications called Mobile Crowd Sensing (MCS) wherein mobile devices carried around by a crowd are used to sense phenomena of interest. Subsequently, sensed data are collected, aggregated and analysed to extract useful information. Sparse Mobile Crowd Sensing (SMCS) aims at reducing the sensing overhead (e.g., battery consumption
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Internet of Things (IoT)-based indoor plant care system J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2023-03-27 Gleiston Guerrero-Ulloa, Alejandra Méndez-García, Valeria Torres-Lindao, Vivian Zamora-Mecías, Carlos Rodríguez-Domínguez, Miguel J. Hornos
Abstract The list of Sustainable Development Goals created by the United Nations include good health and well-being as one of its primary objectives. Pollution is a concern worldwide, and pollution levels inside buildings (homes or workplaces) can be higher than outdoors. To alleviate this problem and improve air quality, ornamental plants can be used. This paper presents the application of Internet
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A systematic literature review of Smart Home Technology acceptance J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2023-03-17 Neil Daruwala, Ursula Oberst
Research on automated domestic appliances, categorized as Smart Home Technology (SHT), has increased exponentially over the last decade and has taken various guises, from qualitative descriptive investigation to empirically based analysis. Given the unresolved uncertainties surrounding the SHT acceptance literature and concern regarding the relatively low smart home device uptake, there is a need to
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Towards an explainable irrigation scheduling approach by predicting soil moisture and evapotranspiration via multi-target regression J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2023-03-17 Emna Ben Abdallah, Rima Grati, Khouloud Boukadi
Significant population growth and ongoing socioeconomic development have increased reliance on irrigated agriculture and agricultural intensification. However, accurately predicting crop water demand is problematic since it is affected by several factors such as weather, soil, and water properties.Many studies have shown that a hybrid irrigation system based on two irrigation strategies (i.e., evapotranspiration
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Data-driven evaluation of machine learning models for climate control in operational smart greenhouses J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2023-03-13 Juan Morales-García, Andrés Bueno-Crespo, Raquel Martínez-España, José M. Cecilia
Nowadays, human overpopulation is stressing our ecosystems in different ways, agriculture being a critical example as different predictions point towards food shortages in the near future. Accordingly, smart farming is becoming key to the optimization of natural resources so that different crops can be grown efficiently, consuming as few resources as possible. In particular, greenhouses have proved
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Hybrid indoor positioning for smart homes using WiFi and Bluetooth low energy technologies J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2023-03-14 Yunus Haznedar, G. Zeynep Gurkas Aydin, Zeynep Turgut
In indoor positioning problems, GPS technology used in outdoor positioning needs to be improved due to the characteristic features of wireless signals. There currently needs to be a generally accepted standard method for indoor positioning. In this study, an ecosystem consisting of Beacon devices,Bluetooth intelligent devices, and Wi-Fi access points has been created to propose an effective indoor
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An obstacle aware efficient MANET routing with optimized Bi-LSTM and multi-objective constraints on improved heuristic algorithm J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2023-02-24 R.M. Bhavadharini, P. Mercy Rajaselvi Beaulah, C.U. Om Kumar, R. Krithiga
Mobile Ad Hoc Networks (MANETs) are self-organizing, self-configuring, and infrastructure-less networks for performing multi-hop communication. The source mobile node can transmit the information to any other destination node, but it has limitations with energy consumption and battery lifetime. Since it appeals to a huge environment, there is a probability of obstacle present. Thus, the network requires
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A model-based simulator for smart homes: Enabling reproducibility and standardization J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2023-02-08 Silvestro Veneruso, Yannis Bertrand, Francesco Leotta, Estefanía Serral, Massimo Mecella
Scientific contributions in the area of smart environments cover different tasks of ambient intelligence including action and activity recognition, anomaly detection, and automated enactment. Algorithms solving these tasks need to be validated against sensor logs of smart environments. In order toacquire these datasets, expensive facilities are needed, containing sensors, actuators and an acquisition
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Computational methods for predicting human behaviour in smart environments J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2023-02-07 Rob Dunne, Oludamilare Matthews, Julio Vega, Simon Harper, Tim Morris
This systematic literature review presents the computational methods of human behaviour prediction research from Pentland and Liu’s seminal 1999 paper on human behaviour prediction to the latest research to date. The PRISMA framework for systematic reviews was used as the review methodology to structure this information aggregation. This review provides a high-level summary of the field with key areas
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Seq2seq model for human action recognition based on skeleton and two-layer bidirectional LSTM J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2023-01-30 Shouke Wei, Jindong Zhao, Junhuai Li, Meixue Yuan
Human action recognition (HAR) plays an important role in social interaction in various fields. This study proposes a light-weight skeleton and two-layer bidirectional LSTM-based Seq2Seq model (SB2_Seq2Seq) for HAR to trade off recognition accuracy, users’ privacy and computer resource usage. An experiment was conducted to compare the proposed SB2_Seq2Seq with other skeleton-based Seq2Seq models and
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Prediction of regional carbon emissions using deep learning and mathematical–statistical model J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2023-01-27 Yutao Mu, Kai Gao, Ronghua Du
Detecting carbon emissions is the key to carbon peaking and carbon neutrality goals. Existing research has focused on utilizing data-driven method to study carbon emissions off a single object. This study proposes a regional carbon emissions prediction method. The area objects are divided into dynamic objects for vehicles and static objects for buildings. For the dynamic object, carbon emissions is
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A novel directional sampling-based path planning algorithm for ambient intelligence navigation scheme in autonomous mobile robots J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2023-01-26 Sivasankar Ganesan, Senthil Kumar Natarajan
Path planning algorithms determine the performance of the ambient intelligence navigation schemes in autonomous mobile robots. Sampling-based path planning algorithms are widely employed in autonomous mobile robot applications. RRT*, or Optimal Rapidly Exploring Random Trees, is a very effective sampling-based path planning algorithm. However, the RRT* solution converges slowly. This study proposes
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Effects of environmental control before sleeping on autonomic nervous activity and sleep: A pilot study J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2023-01-23 Yuko Matsuhisa, Kazuhiro Ide, Toru Nakamura, Yuki Kunugida, Takuya Yamamura, Makoto Komazawa, Koichi Masuda, Yosky Kataoka
Sleep disorders are one of the causes that impair our quality of life, and adjustment of autonomic nervous activity can improve the sleep quality. The authors examined the effects on the sleep quality with adjustment of autonomic nervous activity by individually optimizing complex environment before sleep. Sixteen subjects underwent an environment optimization experiment during the day and subsequent
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Care living instrument for neonatal infant connectivity solution (CliNicS) in smart environment J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2022-11-24 B. Sivasankari, A. Ahilan, A. Jeyam, A. Jasmine Gnanamalar
Hyperbilirubinemia or jaundice occurs in 60% of healthy babies and 80% of preterm infants because of an increase in unconjugated bilirubin in red blood cells. It is subjective to determine the severity of jaundice by visual assessment of the skin color of a newborn, and clinical judgement is dependent on the doctor’s knowledge. The paper explains the development of a non-invasive bilirubin detection
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Study on the CNN model optimization for household garbage classification based on machine learning J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2022-11-17 Wenzhuo Xie, Shiping Li, Wei Xu, Haotian Deng, Weihan Liao, Xianbao Duan, Xuehua Wang
In order to solve the problem of household garbage classification accurately and efficiently, convolutional neural network classifier is an effective method. In this study, a garbage classification device was designed, and the image dataset Wit-Garbage for garbage classification was constructed based on the device by collecting garbage images under different light intensity and weather environment
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An IoT-based smart healthcare system using location-based mesh network and big data analytics J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2022-11-15 Hsin-Chang Lin, Ming-Jen Chen, Jung-Tang Huang
Elderly people requiring care the entire day usually depend on the availability of their family members to give assistance. However, the family members might not provide appropriate help especially in an emergent situation. The application of Internet of Things (IoT) technology with a variety of interconnected devices provides the solution. We propose an IoT-based smart healthcare system comprising
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A cloud-based middleware for multi-modal interaction services and applications J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2022-11-08 Bilgin Avenoğlu, Vincent J. Koeman, Koen V. Hindriks
Smart devices, such as smart phones, voice assistants and social robots, provide users with a range of input modalities, e.g., speech, touch, gestures, and vision. In recent years, advancements in processing of these input channels enable more natural interaction (e.g., automated speech, face, andgesture recognition, dialog generation, emotion expression etc.) experiences for users. However, there
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A low-cost air quality monitoring system based on Internet of Things for smart homes J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2022-08-11 Mehmet Taştan
Global climate change and COVID-19 have changed our social and business life. People spend most of their daily lives indoors. Low-cost devices can monitor indoor air quality (IAQ) and reduce health problems caused by air pollutants. This study proposes a real-time and low-cost air quality monitoring system for smart homes based on Internet of Things (IoT). The developed IoT-based monitoring system
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Feature selection by machine learning models to identify the public’s changing priorities during the COVID-19 pandemic J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2022-08-10 Kenan Mengüç, Nezir Aydin
People around the world have experienced fundamental transformations during mass events. The Industrial Revolution, World War II, and the collapse of the Berlin Wall are some of the cases that have caused radical societal changes. COVID-19 has also been a process of mass experiences regarding society. Determining the mass impact the pandemic has had on society shows that the pandemic is facilitating
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A highly efficient garbage pick-up embedded system based on improved SSD neural network using robotic arms J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2022-08-08 Shih-Hsiung Lee, Chien-Hui Yeh
With the social evolution, economic development, and continuously improved living standards, the dramatically increasing garbage produced by human beings has seriously affected our living environment. There are 3 main ways to dispose of garbage: sanitary landfill, incineration, or recycling. At present, a huge amount of labor resources is required for pre-sorting before garbage disposal, which greatly
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Design of Internet of Things enabled personalized healthcare device for vital signs monitoring J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2022-08-08 A. Pravin Renold, K.V. Ranjith Kumar
Due to the advancement in personal health care devices, healthcare monitoring of an individual at anytime and from any location becomes a reality. The major issue with most personal healthcare device is their high power consumption and frequent charging. It prevents such devices from being used incritical regions where there is no provision for continuous power or medical infrastructure. Energy harvesting
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ReYOLO: A traffic sign detector based on network reparameterization and features adaptive weighting J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2022-07-26 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
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Probabilistic data structures in smart city: Survey, applications, challenges, and research directions J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2022-07-25 Mandeep Kumar, Amritpal Singh
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
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Smart building evacuation system with hybrid network based CNC-C architecture J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2022-07-13 P. Dinesh Anton Raja, C. Arunachalaperumal, M. Divya
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,
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Paradigms for the conceptualization of Cyber-Physical-Social-Thinking hyperspace: A Thematic Synthesis J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2022-07-11 Aurora Macías, Elena Navarro
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
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VASE: Smart glasses for the visually impaired J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2022-05-27 Seemu Sharma, Nidhi Kalra, Lavanya Gupta, Neha Varma, Srishti Agrawal, Vipasha Verma
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
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Fuzzy multi-agent assistance system for elderly care based on user engagement J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2022-05-11 Alfonso Rojas-Domínguez, Carlos Lino-Ramírez, David Gutiérrez-Hernández, Héctor Puga, Víctor 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
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Ultra-wideband data as input of a combined EfficientNet and LSTM architecture for human activity recognition J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2022-05-10 Alexandre Beaulieu, Florentin Thullier, Kévin Bouchard, Julien Maître, Sébastien Gaboury
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
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Refillable PUF authentication protocol for constrained devices J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2022-05-10 Arthur Desuert, Stéphanie Chollet, Laurent Pion, David 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.. Thisgreatly limits the deployment of usual security solutions. As the absence of security is not acceptable
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Preface to JAISE 14(2) J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2022-03-24 Hamid Aghajan,Juan Carlos Augusto,Andrés Muñoz
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Enhancing the park experience by giving visitors control over the park’s soundscape J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2022-03-18 Toon De Pessemier, Timothy Van Renterghem, Kris Vanhecke, Anissa All, Karlo Filipan, Kang Sun, Bert De Coensel, Lieven De Marez, Luc Martens, Dick Botteldooren, Wout Joseph
Sound pollution is an ever growing problem in modern society, and especially in urban environments. In this paper, we investigate if and how artificial sounds can improve the experience of visitors of an urban park with a lot of traffic noise. By using a mobile app, park visitors can control the sound playback by selecting the natural sounds they like, such as birds or a waterfall, and setting the
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Reliable routing in Wireless Body Area Network using optimum number of relay nodes for enhancing network lifetime J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2022-03-16 Sriyanjana Adhikary, Samiran Chattopadhyay, Biswajit Ghosh, Sankhayan Choudhury, Shubha Brata Nath, Nilkantha Garain
Wireless Body Area Network (WBAN) is an emerging technology that has the potential to redefine healthcare sector around the world. It can perform proactively by ubiquitously monitoring human health. But its enormous scope is challenged by limited battery power of the sensors, energy and bandwidth.Moreover, the random motion of human beings makes sensor positioning difficult and restricts efficiently
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Bidirectional ACO intelligent fire evacuation route optimization J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2022-03-15 Jingfang Wang
Cities are in a period of rapid urban development and high-rise buildings are constantly emerging. The characteristics of a fire in a high-rise building are the rapid spread of the fire, the difficulty of fighting the fire, and the difficulty of evacuation. Intelligent fire evacuation requires dynamic planning of paths in fire field, it is necessary to automatically adjust the evacuation route in the
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Development of dual access energy monitoring for the smart control system J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2022-03-15 Shubham Devidas Gujar, S. Fouziya Sulthana, Rajesh Anbazhagan
The rapid growth of smart manufacturing leads to an increase in the power consumption of the equipment used and has the challenges like misuse of equipment, operator safety, and protection of equipment from any electrical disturbances or sudden power surge. This paper aims in creating a smart access control unit with a Dual Access Energy Monitoring (DAEM) system. Here, the equipment is restricted to
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Acknowledgment of JAISE reviewers in 2021 J. Ambient Intell. Smart Environ. (IF 1.7) Pub Date : 2022-01-14 Hamid Aghajan,Juan Carlos Augusto,Andrés Muñoz Ortega