A–Z survey of Internet of Things: Architectures, protocols, applications, recent advances, future directions and recommendations

https://www.science.smith.edu/~jcardell/Courses/EGR328/Readings/EgyptFarming%20WSN.pdf

Precision farming solution in Egypt using the wireless sensor network technology

The rapid evolutions in microcomputing, mini-hardware manufacturing, and machine-to-machine (M2M) communications have enabled novel Internet-of-Things (IoT) solutions to reshape many networking applications. Healthcare systems are among these applications that have been revolutionized with IoT, introducing an IoT branch known as the Internet-of-Medical Things (IoMT) systems. IoMT systems allow remote monitoring of patients with chronic diseases. Thus, it can provide timely patients’ diagnostic that can save their life in case of emergencies. However, security in these critical systems is a major challenge facing their wide utilization. In this article, we present state-of-the-art techniques to secure IoMT systems’ data during collection, transmission, and storage. We comprehensively overview IoMT systems’ potential attacks, including physical and network attacks. Our findings reveal that most security techniques do not consider various types of attacks. Hence, we propose a security framework that combines several security techniques. The framework covers IoMT security requirements and can mitigate most of its known attacks.

Recent Advances in the Internet-of-Medical-Things (IoMT) Systems Security

A smart city is an urban area that collects data using various electronic methods and sensors. Smart cities rely on Information and Communication Technologies (ICT) and aim to improve the quality of services by managing public resources and focusing on comfort, maintenance, and sustainability. The fifth generation (5G) of wireless mobile communication enables a new kind of communication network to connect everyone and everything. 5G will profoundly impact economies and societies as it will provide the necessary communication infrastructure required by various smart city applications. Intelligent Transporting System (ITS) is one of the many smart city applications that can be realized via 5G technology. The paper aims to discuss the impact and implications of 5G on ITS from various dimensions. Before this, the paper presents an overview of the technological context and the economic benefits of the 5G and how key vertical industries will be affected in a smart city, i.e., energy, healthcare, manufacturing, entertainment, and automotive and public transport. Afterward, 5G for ITS is introduced in more detail.

The Role of 5G Technologies in a Smart City: The Case for Intelligent Transportation System

Vehicular communication is one of the critical technologies in intelligent transportation system to provide connectivity between vehicles, road side units, and pedestrians. Multiple wireless accessing technologies designed to provide connectivity in vehicular networks such as conventional Wi-Fi, IEEE 802.11p, and cellular communications. Recently, cellular V2X (C-V2X) is standardized and designed by the third generation partnership project (3GPP) for automotive services. C-V2X supports two communication modes through a single platform to provide both Wi-Fi and cellular communication. LTE-V2X is the current 3GPPRelease 14 standard that has many enhancements to provide the new 3GPPRelease 16 for the new 5G radio generation. 5G-new radio (NR) is expected to address the automotive capabilities, improvement, and services for 2020 and beyond. 5G-NR becomes a competitive technology compared with other wireless technologies because of extensive coverage, high capacity, high reliability, and low delay support. In this paper, we propose the Optimizing of 5G with V2X, and analyzing the current V2X standards, introducing the development of 5G, challenges, features, requirements, design, and technologies.

5G-V2X: standardization, architecture, use cases, network-slicing, and edge-computing

Introducing IoT systems to healthcare applications has made it possible to remotely monitor patients’ information and provide proper diagnostics whenever needed. However, providing high-security features that guarantee the correctness and confidentiality of patients’ data is a significant challenge. Any alteration to the data could affect the patients’ treatment, leading to human casualties in emergency conditions. Due to the high dimensionality and prominent dynamicity of the data involved in such systems, machine learning has the promise to provide an effective solution when it comes to intrusion detection. However, most of the available healthcare intrusion detection systems either use network flow metrics or patients’ biometric data to build their datasets. This paper aims to show that combining both network and biometric metrics as features performs better than using only one of the two types of features. We have built a real-time Enhanced Healthcare Monitoring System (EHMS) testbed that monitors the patients’ biometrics and collects network flow metrics. The monitored data is sent to a remote server for further diagnostic and treatment decisions. Man-in-the-middle cyber-attacks have been used, and a dataset of more than 16 thousand records of normal and attack healthcare data has been created. The system then applies different machine learning methods for training and testing the dataset against these attacks. Results prove that the performance has improved by 7% to 25% in some cases, and this shows the robustness of the proposed system in providing proper intrusion detection.

/pdf/intrusion-detection-system-for-healthcare-systems-using-344dxz3wc0.pdf

Intrusion Detection System for Healthcare Systems Using Medical and Network Data: A Comparison Study

The Advanced Metering Infrastructure (AMI) is one of the Smart Grid (SG) applications that used to upgrade the current power system by proposing a two-way communication system to connect the smart meter devices at homes with the electric control company. The design and deployment of an efficient routing protocol solution for AMI systems are considered to be a critical challenge due to the constrained resources of the smart meter nodes. IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) was recently standardized by the IETF and originally designed to satisfy the routing requirements of lossy and low power networks like wireless sensors (WSN). We have two kinds of AMI applications, on one hand AMI based WSN and on the other hand AMI based PLC communication. In this paper, we proposed a real and simulated implementation of RPL behavior with proper modifications to support the AMI based WSN routing requirements. We evaluate RPL performance using 140 nodes from the wireless sensor testbed (IoT-LAB) and 1000 nodes using Cooja simulator measure RPL performance within medium and high-density networks. We adopted two routing metrics for path selection: First one is HOP Count (HC) and the second is Expected Transmission Unit (ETX) to evaluate RPL performance in terms of packet delivery ratio; network latency; control traffic overhead; and power consumption. Our results illustrate that routes with ETX calculations in low and medium network densities outperform routes using HC and the performance decreases as the network becomes dense. However, Cooja implementation results provides an average reasonable performance for AMI with high-density networks; still many RPL nodes suffering from high packet loss rates, network congestion and many retransmissions due to the selection of optimal paths with highly unreliable links.

https://www.mdpi.com/2079-9292/8/2/186/pdf

RPL Routing Protocol Performance in Smart Grid Applications Based Wireless Sensors: Experimental and Simulated Analysis

Intelligent Sleeping Mechanism for wireless sensor networks

https://www.techscience.com/csse/v35n5/40508/pdf

Anar A. Hady

Papers

Intrusion Detection System for Healthcare Systems Using Medical and Network Data: A Comparison Study

5G-V2X: standardization, architecture, use cases, network-slicing, and edge-computing

RPL Routing Protocol Performance in Smart Grid Applications Based Wireless Sensors: Experimental and Simulated Analysis

Intelligent Sleeping Mechanism for wireless sensor networks

Duty Cycling Centralized Hierarchical Routing Protocol With Content Analysis Duty Cycling Mechanism for Wireless Sensor Networks