LPWAN Technologies: Emerging Application Characteristics, Requirements, and Design Considerations

Low power wide area network (LPWAN) is a promising solution for long range and low power Internet of Things (IoT) and machine to machine (M2M) communication applications. This paper focuses on defining a systematic and powerful approach of identifying the key characteristics of such applications, translating them into explicit requirements, and then deriving the associated design considerations. LPWANs are resource-constrained networks and are primarily characterized by long battery life operation, extended coverage, high capacity, and low device and deployment costs. These characteristics translate into a key set of requirements including M2M traffic management, massive capacity, energy efficiency, low power operations, extended coverage, security, and interworking. The set of corresponding design considerations is identified in terms of two categories, desired or expected ones and enhanced ones, which reflect the wide range of characteristics associated with LPWAN-based applications. Prominent design constructs include admission and user traffic management, interference management, energy saving modes of operation, lightweight media access control (MAC) protocols, accurate location identification, security coverage techniques, and flexible software re-configurability. Topological and architectural options for interconnecting LPWAN entities are discussed. The major proprietary and standards-based LPWAN technology solutions available in the marketplace are presented. These include Sigfox, LoRaWAN, Narrowband IoT (NB-IoT), and long term evolution (LTE)-M, among others. The relevance of upcoming cellular 5G technology and its complementary relationship with LPWAN technology are also discussed

IEEE Access Special Section Editorial: Green Communications on Wireless Networks

Green communications, focusing on energy efficiency, is a hot topic in both academic and industry communities since they can significantly improve sustainability concerning power resources and environmental conditions. Later, with much focus on this area, several green communication methods started enrolling into a more thoughtful phase, with compelling applications in several networks. For instance, a simple and effective green communication solution is to arrange a sleep mode device incorporated by several MAC protocols with broad wireless network applications. However, it is required to examine the trade-off between green communications' energy efficiency and network requirements. In addition, it is crucial to appraise the performance concerning the energy consumption, the throughput, and the response time, regarding green communications under different wireless network conditions (e.g., different traffic and different channels)

Application of G.hn broadband powerline communication for industrial control using COTS components

Broadband powerline communication is a technology developed mainly with consumer applications and bulk data transmission in mind. Typical use cases include file download, streaming, or last-mile internet access for residential buildings. Applications gaining momentum are smart metering and grid automation, where response time requirements are relatively moderate compared to industrial (real-time) control. This work investigates to which extent G.hn technology, with existing, commercial off-the-shelf components, can be used for real-time control applications. Maximum packet rate and latency statistics are investigated for different G.hn profiles and MAC algorithms. An elevator control system serves as an example application to define the latency and throughput requirements. The results show that G.hn is a feasible technology candidate for industrial IoT-type applications if certain boundary conditions can be ensured

Network as a Sensor for Smart Crowd Analysis and Service Improvement

With the growing availability of data processing and machine learning infrastructures, crowd analysis is becoming an important tool to tackle economic, social, and environmental challenges in smart communities. The heterogeneous crowd movement data captured by IoT solutions can inform policy-making and quick responses to community events or incidents. However, conventional crowd-monitoring techniques using video cameras and facial recognition are intrusive to everyday life. This article introduces a novel non-intrusive crowd monitoring solution which uses 1,500+ software-defined networks (SDN) assisted WiFi access points as 24/7 sensors to monitor and analyze crowd information. Prototypes and crowd behavior models have been developed using over 900 million WiFi records captured on a university campus. We use a range of data visualization and time-series data analysis tools to uncover complex and dynamic patterns in large-scale crowd data. The results can greatly benefit organizations and individuals in smart communities for data-driven service improvement

The Beginning of a 'Smart Development Era' in Azerbaijan: Smart Technologies and/vs Smart Decision-Making

The past few years in Azerbaijan have been marked by growing government interest in using 'smart' solutions in urban and rural planning. The results of the Karabakh conflict pushed these aspirations even further, with ‘smart’ technologies being seen as the key instruments in the redevelopment of the de-occupied territories. Since cities are vital mechanisms for economic growth, it is generally believed that applying modern technologies in urban and regional planning can increase the economic performance of a nation while ensuring sustainability. This article will discuss Azerbaijan's existing experience in 'smart' development and examine the extent to which the wider public participates (or will have an opportunity to participate) in the ongoing and future reforms

Digital twins: a survey on enabling technologies, challenges, trends and future prospects

Digital Twin (DT) is an emerging technology surrounded by many promises, and potentials to reshape the future of industries and society overall. A DT is a system-of-systems which goes far beyond the traditional computer-based simulations and analysis. It is a replication of all the elements, processes, dynamics, and firmware of a physical system into a digital counterpart. The two systems (physical and digital) exist side by side, sharing all the inputs and operations using real-time data communications and information transfer. With the incorporation of Internet of Things (IoT), Artificial Intelligence (AI), 3D models, next generation mobile communications (5G/6G), Augmented Reality (AR), Virtual Reality (VR), distributed computing, Transfer Learning (TL), and electronic sensors, the digital/virtual counterpart of the real-world system is able to provide seamless monitoring, analysis, evaluation and predictions. The DT offers a platform for the testing and analysing of complex systems, which would be impossible in traditional simulations and modular evaluations. However, the development of this technology faces many challenges including the complexities in effective communication and data accumulation, data unavailability to train Machine Learning (ML) models, lack of processing power to support high fidelity twins, the high need for interdisciplinary collaboration, and the absence of standardized development methodologies and validation measures. Being in the early stages of development, DTs lack sufficient documentation. In this context, this survey paper aims to cover the important aspects in realization of the technology. The key enabling technologies, challenges and prospects of DTs are highlighted. The paper provides a deep insight into the technology, lists design goals and objectives, highlights design challenges and limitations across industries, discusses research and commercial developments, provides its applications and use cases, offers case studies in industry, infrastructure and healthcare, lists main service providers and stakeholders, and covers developments to date, as well as viable research dimensions for future developments in DTs