Adaptive mobile Web server framework for Mist computing in the Internet of Things

2018 ◽  
Vol 14 (3/4) ◽  
pp. 247-267 ◽  
Author(s):  
Mohan Liyanage ◽  
Chii Chang ◽  
Satish Narayana Srirama
Keyword(s):  
Internet Of Things ◽  
Assisted Living ◽  
Fog Computing ◽  
Ambient Assisted Living ◽  
Base Station ◽  
Content Type ◽  
The Real ◽  
Platform As A Service ◽  
Station Grid ◽  
And Performance

Purpose The distant data centre-centric Internet of Things (IoT) systems face the latency issue especially in the real-time-based applications, such as augmented reality, traffic analytics and ambient assisted living. Recently, Fog computing models have been introduced to overcome the latency issue by using the proximity-based computational resources, such as the computers co-located with the cellular base station, grid router devices or computers in local business. However, the increasing users of Fog computing servers cause bottleneck issues and consequently the latency issue arises again. This paper aims to introduce the utilisation of Mist computing (Mist) model, which exploits the computational and networking resources from the devices at the very edge of the IoT networks. Design/methodology/approach This paper proposes a service-oriented mobile-embedded Platform as a Service (mePaaS) framework that allows the mobile device to provide a flexible platform for proximal users to offload their computational or networking program to mePaaS-based Mist computing node. Findings The prototype has been tested and performance has been evaluated on the real-world devices. The evaluation results have shown the promising nature of mePaaS. Originality/value The proposed framework supports resource-aware autonomous service configuration that can manage the availability of the functions provided by the Mist node based on the dynamically changing hardware resource availability. In addition, the framework also supports task distribution among a group of Mist nodes.

scholarly journals A Survey on Internet of Things and Cloud Computing for Healthcare

Electronics ◽  
2019 ◽  
Vol 8 (7) ◽  
pp. 768 ◽  
Author(s):  
L. Minh Dang ◽  
Md. Jalil Piran ◽  
Dongil Han ◽  
Kyungbok Min ◽  
Hyeonjoon Moon
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Data Storage ◽  
Assisted Living ◽  
Data Exchange ◽  
Fog Computing ◽  
Ambient Assisted Living ◽  
Healthcare Industry ◽  
Healthcare Applications ◽  
Privacy And Security

The fast development of the Internet of Things (IoT) technology in recent years has supported connections of numerous smart things along with sensors and established seamless data exchange between them, so it leads to a stringy requirement for data analysis and data storage platform such as cloud computing and fog computing. Healthcare is one of the application domains in IoT that draws enormous interest from industry, the research community, and the public sector. The development of IoT and cloud computing is improving patient safety, staff satisfaction, and operational efficiency in the medical industry. This survey is conducted to analyze the latest IoT components, applications, and market trends of IoT in healthcare, as well as study current development in IoT and cloud computing-based healthcare applications since 2015. We also consider how promising technologies such as cloud computing, ambient assisted living, big data, and wearables are being applied in the healthcare industry and discover various IoT, e-health regulations and policies worldwide to determine how they assist the sustainable development of IoT and cloud computing in the healthcare industry. Moreover, an in-depth review of IoT privacy and security issues, including potential threats, attack types, and security setups from a healthcare viewpoint is conducted. Finally, this paper analyzes previous well-known security models to deal with security risks and provides trends, highlighted opportunities, and challenges for the IoT-based healthcare future development.

Ambient Assisted Living and Internet of Things

2019 ◽  
pp. 100-115 ◽  
Author(s):  
Gonçalo Marques
Keyword(s):  
Internet Of Things ◽  
Assisted Living ◽  
Ambient Assisted Living ◽  
Physical Object ◽  
World Population ◽  
Ageing Population ◽  
Communication Devices ◽  
Great Relevance ◽  
The One ◽  
Systems Architectures

The study of systems and architectures for ambient assisted living (AAL) is undoubtedly a topic of great relevance given the ageing of the world population. On the one hand, AAL technologies are designed to meet the needs of the ageing population in order to maintain their independence as long as possible. On the other hand, internet of things (IoT) proposes that various “things,” which include not only communication devices but also every other physical object on the planet, are going to be connected and will be controlled across the internet. The continuous technological advancements turn possible to build smart objects with great capabilities for sensing and connecting turn possible several advancements in AAL and IoT systems architectures. Advances in networking, sensors, and embedded devices have made it possible to monitor and provide assistance to people in their homes. This chapter reviews the state of art on AAL and IoT and their applications for enhanced indoor living environments and occupational health.

scholarly journals Air Quality Monitoring Using Assistive Robots for Ambient Assisted Living and Enhanced Living Environments through Internet of Things

Electronics ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 1375 ◽  
Author(s):  
Gonçalo Marques ◽  
Ivan Miguel Pires ◽  
Nuno Miranda ◽  
Rui Pitarma
Keyword(s):  
Social Networks ◽  
Air Quality ◽  
Internet Of Things ◽  
Indoor Air ◽  
Assisted Living ◽  
Ambient Assisted Living ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Assistive Robot ◽  
Living Environments

This paper presents iAirBot, an assistive robot for indoor air quality monitoring based on Internet of Things. The system can communicate with occupants and triggers alerts automatically using social networks. The information can be accessed by the caregiver to plan interventions for enhanced living environments in a timely manner. The results are promising, as the proposed architecture presents a cost-effective assistive robot for indoor quality monitoring. It connects several technological fields and knowledge areas, such as ambient assisted living, Internet of Things, wireless sensor networks, social networks, and indoor air quality. When compared to other systems, iAirBot stands out for the modularity and scalability of its sensors network, as well as the use of social networks for information sharing. Therefore, iAirBot is a significant system for enhanced living environments, occupational health, and well-being.

Decision-making framework for using ambient assisted living

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Majid H. Alsulami ◽  
Mohammed S. Alsaqer ◽  
Anthony S. Atkins
Keyword(s):  
Decision Making ◽  
Saudi Arabia ◽  
Health Care Providers ◽  
Assisted Living ◽  
Ambient Assisted Living ◽  
The Elderly ◽  
Care Providers ◽  
Content Type ◽  
Decision Making Framework

Purpose Technology plays an important role in assisting elderly people to live independently, longer and improve their quality of life and health, in supporting their daily activities, etc. The ageing population becomes a global phenomenon. The population of Saudi Arabia continues to age (>60 years of age) currently (5%) compared to other group ages. In 2050, it will increase rapidly to 20.9% of the Saudi population. The current research aims at examining the barriers that health-care providers in the Kingdom of Saudi Arabia are experiencing in the adoption of ambient assisted living (AAL) technologies among the elderly. The study aims to identify a challenging issue with the increasing the number of elderly among the population in the country, which has highlighted the need to use AAL technology to improve the quality of life among the elderly. Design/methodology/approach This study involved a community of practice (CoP) study as a method of data collection where data collected were presented and discussed in line with the existing literature review findings. Findings In total, 14 factors were identified in this study and discussed in the context of Saudi Arabia, which resulted in developing a decision-making framework for using AAL by health-care providers. Those factors are essential in boosting the usage of technology in improving elderly health in Saudi Arabia. Research limitations/implications This study includes implications for developing a decision-making framework for using AAL. Social implications This study clarifies that technology can connect elderly people with society. Originality/value In total, 14 factors were identified in this study and discussed in the context of Saudi Arabia.

Adaptive window based fall detection using anomaly identification in fog computing scenario

2021 ◽  
Vol 17 (1) ◽  
pp. 15-37
Author(s):  
Rashmi Shrivastava ◽  
Manju Pandey
Keyword(s):  
Feature Extraction ◽  
Assisted Living ◽  
Detection System ◽  
Fog Computing ◽  
Ambient Assisted Living ◽  
Window Size ◽  
Fall Detection ◽  
Detection Methods ◽  
Support Vector ◽  
Adaptive Window

Human fall detection is a subcategory of ambient assisted living. Falls are dangerous for old aged people especially those who are unaccompanied. Detection of falls as early as possible along with high accuracy is indispensable to save the person otherwise it may lead to physical disability even death also. The proposed fall detection system is implemented in the edge computing scenario. An adaptive window-based approach is proposed here for feature extraction because window size affects the performance of the classifier. For training and testing purposes two public datasets and our collected dataset have been used. Anomaly identification based on a support vector machine with an enhanced chi-square kernel is used here for the classification of Activities of Daily Living (ADL) and fall activities. Using the proposed approach 100% sensitivity and 98.08% specificity have been achieved which are better when compared with three recent research based on unsupervised learning. One of the important aspects of this study is that it is also validated on actual real fall data and got 100% accuracy. This complete fall detection model is implemented in the fog computing scenario. The proposed approach of adaptive window based feature extraction is better than static window based approaches and three recent fall detection methods.

scholarly journals Sistema heterogéneo para la monitorización de la actividad diaria en el hogar y el bienestar de personas mayores

2021 ◽  
pp. 632-639
Author(s):  
Francisco Miguel Calatrava Nicolás ◽  
Francisco José Ortiz Zaragoza ◽  
José Alfonso Vera Repullo ◽  
Joaquín Roca González ◽  
Manuel Jiménez Buendía ◽  
...  
Keyword(s):  
Operating System ◽  
Internet Of Things ◽  
Assisted Living ◽  
Ambient Assisted Living ◽  
Robot Operating System ◽  
El Sistema

En este artículo se presenta el diseño de un sistema heterogéneo cuya finalidad es la de cuidar la salud y el bienestar de las personas mayores que viven solas en su hogar. Se intenta seguir la iniciativa del programa europeo AAL (Ambient Assisted Living) Dicho sistema se encuentra formado por un dispositivo robótico móvil, un conjunto de sensores domóticos de bajo coste, un dispositivo médico tipo pulsera de actividad y una aplicación de Android para el estudio del estado anímico. El sistema ha sido integrado haciendo uso de ROS (Robot Operating System), de tecnologías IoT (Internet of Things) tales como Node-RED y la plataforma domótica Home-Assistant. Este sistema heterogéneo se desarrolla en la actualidad en un proyecto nacional Retos de la Sociedad.

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