scholarly journals An Accessible Smart Home Based on Integrated Multimodal Interaction

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5464
Author(s):  
Ana Patrícia Rocha ◽  
Maksym Ketsmur ◽  
Nuno Almeida ◽  
António Teixeira
Keyword(s):  
Smart Home ◽  
Multimodal Interaction ◽  
Environmentally Friendly ◽  
Smart Homes ◽  
Information And Communications Technology ◽  
Communications Technology ◽  
Home Based ◽  
Project Smart ◽  
Multiple Devices ◽  
Adaptive Interaction

Our homes are becoming increasingly sensorized and smarter. However, they are also becoming increasingly complex, making accessing them and their advantages difficult. Assistants have the potential for improving the accessibility of smart homes, by providing everyone with an integrated, natural, and multimodal way of interacting with the home’s ecosystem. To demonstrate this potential and contribute to more environmentally friendly homes, in the scope of the project Smart Green Homes, a home assistant highly integrated with an ICT (Information and communications technology) home infrastructure was developed, deployed in a demonstrator, and evaluated by seventy users. The users’ global impression of our home assistant is in general positive, with 61% of the participants rating it as good or excellent overall and 51% being likely or very likely to recommend it to others. Moreover, most think that the assistant enhances interaction with the smart home’s multiple devices and is easy to use by everyone. These results show that a home assistant providing an integrated view of a smart home, through natural, multimodal, and adaptive interaction, is a suitable solution for enhancing the accessibility of smart homes and thus contributing to a better living ambient for all of their inhabitants.

scholarly journals TC-CNN: A Tree Classified model using AI for identifying malware intrusions in open Networks

2021 ◽  
Vol 58 (2) ◽  
pp. 6561-6573
Author(s):  
P. Ramachandran , Dr. R. Balasubramanian
Keyword(s):  
Information And Communications Technology ◽  
Intrusion Detection Systems ◽  
The Internet ◽  
Threat Detection ◽  
Communications Technology ◽  
Detection Systems ◽  
Open Networks ◽  
Multiple Devices ◽  
Internet Medium ◽  
Network Server

Proliferation of the internet by multiple devices has led to dramatic increases in network traffic.  The Internet medium has also been growing with this usage, but this fast growth has also resulted in new threats making networks vulnerable to intruders and attackers or malicious users. This has made network security an important factor due to excessive usage of ICT (Information and Communications Technology) as threats to IVTs has also grown manifold. Securing data is a major issue, especially when they are transmitted across open networks. IDSs (Intrusion Detection Systems)  are methods or techniques or algorithm which cater to detection of intrusions while on transit. IDSs are useful in identifying harmful operations. Secure automated threat detection and prevention is a more effective procedure to reduce workloads of monitors by scanning the network, server functions and inform monitors on suspicious activity. IDSs monitor systems continually in the angle of threat. This paper’s proposed technique detects suspicious activities using AI (Artificial Intelligence) and analyzes networks concurrently for defense from harmful activities. The proposed algorithm’s experimental results conducted on the UNSW_NB15_training-set shows good performances in terms of accuracy clocking above 96%. 

scholarly journals Development of a Role Model for the Use of Smart Home Based Data in Medical Care

2021 ◽  
Author(s):  
Isabel Richter ◽  
Corinna Mielke ◽  
Reinhold Haux
Keyword(s):  
Literature Review ◽  
Health System ◽  
Medical Care ◽  
Patient Care ◽  
Smart Home ◽  
Role Model ◽  
Smart Homes ◽  
Care Process ◽  
Home Based ◽  
Home Systems

Smart home systems create new opportunities for patient care. In this paper, a role model is created for the different groups of people involved in the care process of an occupant. Based on a systematic literature review seven roles were identified. A second literature review deals with the topic Feedback of Smart Home Systems. Combining both reviews visualization proposals were created and are presented for two of the roles. The role model is adapted to German health system but could be transformed for different countries. To confirm the results an evaluation of role model and visualization proposal should be done in collaboration with possible users of smart homes.

scholarly journals Recognition of Daily Activities of Two Residents in a Smart Home Based on Time Clustering

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1457 ◽  
Author(s):  
Jinghuan Guo ◽  
Yiming Li ◽  
Mengnan Hou ◽  
Shuo Han ◽  
Jianxun Ren
Keyword(s):  
Activity Recognition ◽  
Adaptive Systems ◽  
Smart Home ◽  
Population Aging ◽  
Smart Homes ◽  
Daily Activities ◽  
Matching Method ◽  
Home Based ◽  
Great Progress ◽  
F Measure

With the development of population aging, the recognition of elderly activity in smart homes has received increasing attention. In recent years, single-resident activity recognition based on smart homes has made great progress. However, few researchers have focused on multi-resident activity recognition. In this paper, we propose a method to recognize two-resident activities based on time clustering. First, to use a de-noising method to extract the feature of the dataset. Second, to cluster the dataset based on the begin time and end time. Finally, to complete activity recognition using a similarity matching method. To test the performance of the method, we used two two-resident datasets provided by Center for Advanced Studies in Adaptive Systems (CASAS). We evaluated our method by comparing it with some common classifiers. The results show that our method has certain improvements in the accuracy, recall, precision, and F-Measure. At the end of the paper, we explain the parameter selection and summarize our method.

scholarly journals Smart Home Gateway Based on Integration of Deep Reinforcement Learning and Blockchain Framework

Processes ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1593
Author(s):  
Zeinab Shahbazi ◽  
Yung-Cheol Byun ◽  
Ho-Young Kwak
Keyword(s):  
Reinforcement Learning ◽  
Smart Home ◽  
Smart Homes ◽  
Smart Devices ◽  
Home Gateway ◽  
Home Based ◽  
Information And Communication ◽  
Smart Home Gateway ◽  
Iot Devices ◽  
The Right

The development of information and communication technology in terms of sensor technologies cause the Internet of Things (IoT) step toward smart homes for prevalent sensing and management of resources. The gateway connections contain various IoT devices in smart homes representing the security based on the centralized structure. To address the security purposes in this system, the blockchain framework is considered a smart home gateway to overcome the possible attacks and apply Deep Reinforcement Learning (DRL). The proposed blockchain-based smart home approach carefully evaluated the reliability and security in terms of accessibility, privacy, and integrity. To overcome traditional centralized architecture, blockchain is employed in the data store and exchange blocks. The data integrity inside and outside of the smart home cause the ability of network members to authenticate. The presented network implemented in the Ethereum blockchain, and the measurements are in terms of security, response time, and accuracy. The experimental results show that the proposed solution contains a better outperform than recent existing works. DRL is a learning-based algorithm which has the most effective aspects of the proposed approach to improve the performance of system based on the right values and combining with blockchain in terms of security of smart home based on the smart devices to overcome sharing and hacking the privacy. We have compared our proposed system with the other state-of-the-art and test this system in two types of datasets as NSL-KDD and KDD-CUP-99. DRL with an accuracy of 96.9% performs higher and has a stronger output compared with Artificial Neural Networks with an accuracy of 80.05% in the second stage, which contains 16% differences in terms of improving the accuracy of smart homes.

scholarly journals Development of a system for the security assessment for smart homes based on the IoT

Connectivity ◽  
2021 ◽  
Vol 149 (1) ◽  
Author(s):  
Ya. O. Halay ◽  
◽  
A. P. Bondarchuk ◽  
O. M. Tkalenko ◽  
O. V. Polonevych ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Smart Home ◽  
Smart Homes ◽  
Assessment System ◽  
Security And Privacy ◽  
The Internet ◽  
Security Assessment ◽  
Security Attacks ◽  
Home Based ◽  
The Internet Of Things

This article is about developing a security assessment system for smart homes that use Internet of Things technology. The Internet of Things (IoT) is a nascent paradigm focused on the relationship of things or devices to each other and users. Over time, most connections on the Internet of Things go from «people interact with things» to «things interact with things». This technology is expected to be an important milestone in the development of smart homes to bring convenience and efficiency to our lives and our homes. But the introduction of this IoT technology in our homes will be important for the safety of these technologies. Connecting all smart objects inside the house to the Internet and to each other leads to new security and privacy issues, such as the confidentiality, authenticity, and integrity of the data that is perceived and exchanged. These technologies are very vulnerable to various security attacks that make a smart home based on IoT unsafe to live in, so security risks need to be assessed to assess the situation of smart homes. For any technology to be successful and widely used, it must gain the trust of users, ensuring sufficient security and confidentiality. As in all sectors, maintaining security will be the most important challenge to overcome. As homes become more computerized and filled with devices, potential computer security attacks and their impact on residents need to be investigated. This paper uses a methodology that focuses mainly on information assets and examines containers (technical, physical and human) and conducts security risk assessments to highlight various security vulnerabilities in the smart home based on the Internet of Things, the consequences and proposing measures against identified problems. that meet most safety requirements. Finally, it offers recommendations for users.

Sign in / Sign up

Export Citation Format

Share Document