A Fuzzy Logic-Based Method for Incorporating Ethics in the Internet of Things

2021 ◽  
Vol 12 (3) ◽  
pp. 98-122
Author(s):  
Sahil Sholla ◽  
Roohie Naaz Mir ◽  
Mohammad Ahsan Chishti
Keyword(s):  
Fuzzy Logic ◽  
Wide Spectrum ◽  
Research Direction ◽  
Smart Devices ◽  
Learning Mechanisms ◽  
Ethical Considerations ◽  
Smart Transportation ◽  
Smart Healthcare ◽  
Human Ethics ◽  
Smart Things

IoT is expected to have far-reaching consequences on society due to a wide spectrum of applications like smart healthcare, smart transportation, smart agriculture, smart home, etc. However, ethical considerations of AI-enabled smart devices have not been duly considered from a design perspective. In this paper, the authors propose a novel fuzzy logic-based method to incorporate ethics within smart things of IoT. Ethical considerations relevant to a machine context are represented in terms of fuzzy ethics variables (FEVs) and ethics rules. For each ethics rule, a value called scaled ethics value (SEV) is used to indicate its ethical desirability. In order to model flexibility in ethical response, the authors employ the concept of ethics modes that selectively allow scenarios depending on the value of SEV. The method offers a viable mechanism for smart devices to imbue ethical sensitivity that can pave the way for a technology society amenable to human ethics. However, the method does not account for varying ethics, as such incorporating learning mechanisms represent a promising research direction.

scholarly journals Enhancing the Reliability of Cellular Internet of Things through Agreement

2020 ◽  
Vol 10 (21) ◽  
pp. 7699
Author(s):  
Shin-Hung Pan ◽  
Shu-Ching Wang
Keyword(s):  
Internet Of Things ◽  
Large Scale ◽  
Fault Tolerant ◽  
Smart Cities ◽  
Smart Devices ◽  
The Internet ◽  
Smart Transportation ◽  
Fifth Generation ◽  
Smart Healthcare ◽  
Wide Range

Because the Internet of Things (IoT) can provide a global service network through various smart devices, the IoT has been widely used in smart transportation, smart cities, smart healthcare, and factory automation through the Internet connection. With the large-scale establishment and 5G (fifth generation) wireless networks, the cellular Internet of Things (CIoT) will continue to be developed and applied to a wide range of applications. In order to provide a reliable application of CIoT, a safe and reliable network topology MECIoT is proposed in this study. To improve the reliability and fault-tolerant capability of the network proposed, the problem of reaching agreement should be revisited. Therefore, the applications in the system can still be performed correctly even if some processing units (PUs) in the system have failed. In this study, a new protocol is proposed to allow all normal PUs in MECIoT to reach an agreement with the minimum amount of data exchanges required and the maximum number of failed PUs allowed in MECIoT. In the end, the optimality of the protocol has been proven by mathematical method.

A Seven-Layered Model Architecture, Network Model, Protocol Stack, Security, Application, Issues and Challenges in Internet of Vehicle

2020 ◽  
Vol 14 ◽  
Author(s):  
Intyaz Alam ◽  
Sushil Kumar ◽  
Pankaj Kumar Kashyap
Keyword(s):  
Internet Of Things ◽  
Network Model ◽  
Transportation Systems ◽  
Vehicle Speed ◽  
Protocol Stack ◽  
Seamless Integration ◽  
Communication Architecture ◽  
Smart Transportation ◽  
Smart Healthcare ◽  
Essential Components

Background: Recently, Internet of Things (IoT) has brought various changes in the existing research field by including new areas such as smart transportation, smart home facilities, smart healthcare, etc. In smart transportation systems, vehicles contain different components to access information related to passengers, drivers, vehicle speed, and many more. This information can be accessed by connecting vehicles with Internet of Things leading to new fields of research known as Internet of Vehicles. The setup of Internet of Vehicle (IoV) consists of many sensors to establish a connection with several other sensors belonging to different environments by exploiting different technologies. The communication of the sensors faces a lot of challenging issues. Some of the critical challenges are to maintain security in information exchanges among the vehicles, inequality in sensors, quality of internet connection, and storage capacity. Objective: To overcome the challenging issues, we have designed a new framework consisting of seven-layered architecture, including the security layered, which provides seamless integration by communicating the devices present in the IoV environment. Further, a network model consisting of four components such as Cloud, Fog, Connection, and Clients has been designed. Finally, the protocol stack which describes the protocol used in each layer of the proposed seven-layered IoV architecture has been shown. Methods: In this proposed architecture, the representation and the functionalities of each layer and types of security have been defined. Case studies of this seven-layer IoV architecture have also been performed to illustrate the operation of each layer in real-time. The details of the network model including all the elements inside each component, have also been shown. Results: We have discussed some of the existing communication architecture and listed a few challenges and issues occurring in present scenarios. Considering these issues, which is presently occurring in the existing communication architecture. We have developed the seven-layered IoV architecture and the network model with four essential components known as the cloud, fog, connection, and clients. Conclusion: This proposed architecture provides a secure IoV environment and provides life safety. Hence, safety and security will help to reduce the cybercrimes occurring in the network and provides good coordination and communication of the vehicles in the network.

Researching moral distress among New Zealand nurses

2014 ◽  
Vol 22 (1) ◽  
pp. 117-130 ◽  
Author(s):  
Martin Woods ◽  
Vivien Rodgers ◽  
Andy Towers ◽  
Steven La Grow
Keyword(s):  
New Zealand ◽  
Nurse Educators ◽  
Moral Distress ◽  
Response Rate ◽  
Ethical Considerations ◽  
Optimal Care ◽  
Adequate Response ◽  
Human Ethics ◽  
Distress Scale ◽  
Service Managers

Background: Moral distress has been described as a major problem for the nursing profession, and in recent years, a considerable amount of research has been undertaken to examine its causes and effects. However, few research projects have been performed that examined the moral distress of an entire nation’s nurses, as this particular study does. Aim/objective: The purpose of this study was to determine the frequency and intensity of moral distress experienced by registered nurses in New Zealand. Research design: The research involved the use of a mainly quantitative approach supported by a slightly modified version of a survey based on the Moral Distress Scale–Revised. Participants and research context: In total, 1500 questionnaires were sent out at random to nurses working in general areas around New Zealand and 412 were returned, giving an adequate response rate of 27%. Ethical considerations: The project was evaluated and judged to be low risk and recorded as such on 22 February 2011 via the auspices of the Massey University Human Ethics Committee. Findings: Results indicate that the most frequent situations to cause nursing distress were (a) having to provide less than optimal care due to management decisions, (b) seeing patient care suffer due to lack of provider continuity and (c) working with others who are less than competent. The most distressing experiences resulted from (a) working with others who are unsafe or incompetent, (b) witnessing diminished care due to poor communication and (c) watching patients suffer due to a lack of provider continuity. Of the respondents, 48% reported having considered leaving their position due to the moral distress. Conclusion: The results imply that moral distress in nursing remains a highly significant and pertinent issue that requires greater consideration by health service managers, policymakers and nurse educators.

Deep learning based Blockchain solution for preserving privacy in future vehicles

2020 ◽  
pp. 1-14
Author(s):  
Varsha R ◽  
Meghna Manoj Nair ◽  
Siddharth M. Nair ◽  
Amit Kumar Tyagi
Keyword(s):  
Deep Learning ◽  
Autonomous Vehicles ◽  
Recommendation System ◽  
Privacy Preserving ◽  
Smart Devices ◽  
The Road ◽  
Blockchain Technology ◽  
Technological Advances ◽  
Previous Decade ◽  
Smart Things

The Internet of Things (smart things) is used in many sectors and applications due to recent technological advances. One of such application is in the transportation system, which is of primary use for the users to move from one place to another place. The smart devices which were embedded in vehicles are useful for the passengers to solve his/her query, wherein future vehicles will be fully automated to the advanced stage, i.e. future cars with driverless feature. These autonomous cars will help people a lot to reduce their time and increases their productivity in their respective (associated) business. In today’s generation and in the near future, privacy preserving and trust will be a major concern among users and autonomous vehicles and hence, this paper will be able to provide clarity for the same. Many attempts in previous decade have provided many efficient mechanisms, but they all work only with vehicles along with a driver. However, these mechanisms are not valid and useful for future vehicles. In this paper, we will use deep learning techniques for building trust using recommender systems and Blockchain technology for privacy preserving. We also maintain a certain level of trust via maintaining the highest level of privacy among users living in a particular environment. In this research, we developed a framework that could offer maximum trust or reliable communication to users over the road network. With this, we also preserve privacy of users during traveling, i.e., without revealing identity of respective users from Trusted Third Parties or even Location Based Service in reaching a destination. Thus, Deep Learning based Blockchain Solution (DLBS) is illustrated for providing an efficient recommendation system.

scholarly journals A Resource Oriented Route Selection Framework Using Contextual Information Based on Fuzzy Logic

Electronics ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 1023 ◽  
Author(s):  
Khadak Singh Bhandari ◽  
Gi Hwan Cho
Keyword(s):  
Fuzzy Logic ◽  
Objective Function ◽  
Smart City ◽  
Contextual Information ◽  
Network Dynamics ◽  
Residual Energy ◽  
Smart Devices ◽  
Route Selection ◽  
Network Simulator ◽  
Lossy Networks

Internet of Things (IoT) is expected to have a significant impact on city’s service provisioning and make a smart city more accessible and pragmatic since the deployment of heterogeneous smart devices in each infrastructure of cities is increasing. So far, the IPv6 routing protocol for low power and lossy networks (RPL) is considered to fit on IoT infrastructure for achieving the expected network requirements. While RPL meets the IoT network requirements quite well, there are some issues that need to be addressed, such as adaptability to network dynamics. This issue significantly limits the use of RPL in many smart city application scenarios, such as emergency alerts with high traffic flows. As part of a smart city vision, IoT applications are becoming more diverse, which requires context-awareness in routing protocols to support the behavior of the network. To address this issue, we design an objective function that performs the route selection based on fuzzy logic techniques while using contextual information from the application. For this, we present a new context-oriented objective function (COOF) that comprises both nodes as well as link metrics. Further, we suggest two new routing metrics, known as queue fluctuation index (QFI) and residual energy index (REI), which consider the status of queue utilization and remaining energy, respectively. The metrics used are designed to respond to the dynamic needs of the network. The proposed approach has been examined and evaluated in different scenarios when compared to other similar approach and default RPL objective functions. Simulation experiments are conducted in Cooja network simulator for Contiki OS. The evaluation results show that COOF can cope with network dynamics and IoT-based smart city application requirements.

scholarly journals A Survey of Context-Aware Messaging-Addressing for Sustainable Internet of Things (IoT)

2020 ◽  
Vol 12 (10) ◽  
pp. 4105
Author(s):  
Alaa Omran Almagrabi ◽  
Yasser D. Al-Otaibi
Keyword(s):  
Internet Of Things ◽  
Smart Cities ◽  
Contextual Information ◽  
Spatial Models ◽  
Context Aware ◽  
Engineering Technology ◽  
Smart Transportation ◽  
Context Aware Computing ◽  
Iot Applications ◽  
Smart Healthcare

Nowadays, communication engineering technology is merging with the Internet of Things (IoT), which consists of numerous connected devices (referred to as things) around the world. Many researchers have shown significant growth of sensor deployments for multiple smart engineering technologies, such as smart-healthcare, smart-industries, smart-cities, and smart-transportation, etc. In such intelligent engineering technologies, sensors continuously generate a bunch of messages in the network. To enhance the value of the data in the messages, we must know the actuality of the data embedded inside the messages. For this purpose, the contextual information of the data creates a vital challenge. Recently, context-aware computing has emerged to be fruitful in dealing with sensor information. In the ubiquitous computing domain, location is commonly considered one of the most essential sources of context. However, whenever users or applications are concerned with objects, and their site or spatial relationships, location models or spatial models are necessary to form a model of the environment. This paper investigates the area of context-aware messaging and addressing services in diverse IoT applications. The paper examines the notion of context and the use of context within the data exchanged by the sensors in an IoT application for messaging and addressing purposes. Based on the importance and need for context of the information, we identify three critical categories of new IoT applications for context-aware messaging and addressing services: emergency applications, applications for guiding and reminding, and social networking applications. For this purpose, a representative range of systems is reviewed according to the application type, the technology being used, their architecture, the context information, and the services they provide. This survey assists the work of defining an approach for context-aware messaging services domain by discovering the area of context-aware messaging.

scholarly journals GNSS-Free Outdoor Localization Techniques for Resource-Constrained IoT Architectures: A Literature Review

2021 ◽  
Vol 11 (22) ◽  
pp. 10793
Author(s):  
Azin Moradbeikie ◽  
Ahmad Keshavarz ◽  
Habib Rostami ◽  
Sara Paiva ◽  
Sérgio Ivan Lopes
Keyword(s):  
Large Scale ◽  
Smart Cities ◽  
Low Cost ◽  
Security And Privacy ◽  
Smart Manufacturing ◽  
Localization Accuracy ◽  
Smart Transportation ◽  
Smart Healthcare ◽  
Definition Of ◽  
Outdoor Localization

Large-scale deployments of the Internet of Things (IoT) are adopted for performance improvement and cost reduction in several application domains. The four main IoT application domains covered throughout this article are smart cities, smart transportation, smart healthcare, and smart manufacturing. To increase IoT applicability, data generated by the IoT devices need to be time-stamped and spatially contextualized. LPWANs have become an attractive solution for outdoor localization and received significant attention from the research community due to low-power, low-cost, and long-range communication. In addition, its signals can be used for communication and localization simultaneously. There are different proposed localization methods to obtain the IoT relative location. Each category of these proposed methods has pros and cons that make them useful for specific IoT systems. Nevertheless, there are some limitations in proposed localization methods that need to be eliminated to meet the IoT ecosystem needs completely. This has motivated this work and provided the following contributions: (1) definition of the main requirements and limitations of outdoor localization techniques for the IoT ecosystem, (2) description of the most relevant GNSS-free outdoor localization methods with a focus on LPWAN technologies, (3) survey the most relevant methods used within the IoT ecosystem for improving GNSS-free localization accuracy, and (4) discussion covering the open challenges and future directions within the field. Some of the important open issues that have different requirements in different IoT systems include energy consumption, security and privacy, accuracy, and scalability. This paper provides an overview of research works that have been published between 2018 to July 2021 and made available through the Google Scholar database.

scholarly journals Optimized Resource Allocation in IoT using Fuzzy Logic and Bio-Inspired Algorithms

2021 ◽  
Author(s):  
Deepak Kumar Sharma ◽  
Jahanavi Mishra ◽  
Aeshit Singh ◽  
Raghav Govil ◽  
Krishna Kant Singh ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Fuzzy Logic ◽  
Load Balancing ◽  
Network Performance ◽  
Global Network ◽  
Smart Devices ◽  
Delivery Ratio ◽  
Iot Devices ◽  
Nature Inspired Algorithms ◽  
Brute Force Approach

Abstract IoT smart devices are a confluence of microprocessors, sensors, power source and transceiver modules to effectively sense, communicate and transfer data. Energy efficiency is a key governing value of the network performance of smart devices in distributed IoT networks.Low and discrete power and limited amount of memory and finite amount of resources form some major bottlenecks in the workflow.Dynamic load balancing, reliability and flexibility are heavily relied upon by cloud computing for its accessibility.Resources are dynamically provided to the end client in an as-come on-demand fashion with the global network that is the Internet. Proportionally the need for services is increasing at a rate that is astonishing compared to any other forms of development. Load balancing seems a major challenge faced due to the architecture and the modular nature of our cloud environment. Loads need to be distributed dynamically to all the nodes. In this paper, we have introduced a technique that combines fuzzy logic with various nature inspired algorithms - grey wolf algorithm and firefly algorithm in order to effectively balance the load in a network of IoT devices. The performances of various nature inspired algorithms are compared with a brute force approach on the basis of energy efficiency, network lifetime maximization, node failure rate and packet delivery ratio.

scholarly journals A Secure and Privacy-Preserving Three-Factor Anonymous Authentication Scheme for Wireless Sensor Networks in Internet of Things

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Qi Xie ◽  
Zixuan Ding ◽  
Bin Hu
Keyword(s):  
Internet Of Things ◽  
Smart Grids ◽  
Authentication Scheme ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Smart Transportation ◽  
Anonymous Authentication ◽  
Smart Healthcare ◽  
Stolen Verifier Attack ◽  
Three Factor

The Internet of things is playing more and more important role in smart healthcare, smart grids, and smart transportation, and using wireless sensor network (WSN), we can easily obtain and transmit information. However, the data security and users’ privacy are the biggest challenges for WSN because sensor nodes have low computing power and low storage capacity and are easy to be captured, and wireless networks are vulnerable. In 2021, Shuai et al. proposed a lightweight three-factor anonymous authentication scheme for WSN. However, we found that their protocol is vulnerable to stolen-verifier attack, modification of messages’ attack, and no perfect forward secrecy. Then, a new three-factor anonymous authentication scheme using elliptic curve cryptography (ECC) is proposed. Through informal and formal security analyses, our scheme can resist various known attacks and maintains low computational complexity.

An Analysis of Integration of Internet of Things and Cloud Computing

2019 ◽  
Vol 16 (10) ◽  
pp. 4345-4349
Author(s):  
Latika Kakkar ◽  
Deepali Gupta ◽  
Sapna Saxena ◽  
Sarvesh Tanwar
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Data Storage ◽  
Secure Communication ◽  
Traffic Monitoring ◽  
Third Party ◽  
Smart Devices ◽  
The Internet ◽  
Battery Life ◽  
Smart Healthcare

The Internet of Things (IoT) comprises of various smart devices which are networked together to detect, accumulate, process, improve and interchange significant data over the Internet. IoT has improved our lifestyle by offering various applications such as intelligent home, smart healthcare, traffic monitoring and smart city devices. The IoT devices have restriction of power, battery life, memory and network constraints, so cloud can be used for accumulating and analyzing the IoT data. Due to the considerable increase in data transfer over Internet and other devices, the confidential information from the IoT sources required to be secure from any third party access. Cloud computing (CC) on the other side provides a protected, abrupt and advantageous data storage and computing services all over the internet. The integration of both these technologies can prove to be beneficial for each other. Therefore, we need an efficient and authentic method for secure communication in the IoT and cloud based big data environment. This paper provides a review of amalgamation of the IoT and cloud by featuring the implementation challenges and integration benefits.

Sign in / Sign up

Export Citation Format

Share Document