Evaluation of a LoRa mesh network for smart metering in rural locations

Accompanying the advancement on the Internet of Things (IoT), the concept of remote monitoring and control using IoT devices is becoming popular. Digital smart meters hold many advantages over traditional analog meters, and smart metering is one of application of IoT technology. It supports the conventional power system in adopting modern concepts like smart grids, block-chains, automation, etc. due to their remote load monitoring and control capabilities. However, in many applications, the traditional analog meters still are preferred over digital smart meters due to the high deployment and operating costs, and the unreliability of the smart meters. The primary reasons behind these issues are a lack of a reliable and affordable communication system, which can be addressed by the deployment of a dedicated network formed with a Low Power Wide Area (LPWA) platform like wireless radio standards (i.e., LoRa devices). This paper discusses LoRa technology and its implementation to solve the problems associated with smart metering, especially considering the rural energy system. A simulation-based study has been done to analyse the LoRa technology’s applicability in different architecture for smart metering purposes and to identify a cost-effective and reliable way to implement smart metering, especially in a rural microgrid (MG)

Smart Monitoring and Control in the Future Internet of Things

The Internet of Things (IoT) and related technologies have the promise of realizing pervasive and smart applications which, in turn, have the potential of improving the quality of life of people living in a connected world. According to the IoT vision, all things can cooperate amongst themselves and be managed from anywhere via the Internet, allowing tight integration between the physical and cyber worlds and thus improving efficiency, promoting usability, and opening up new application opportunities. Nowadays, IoT technologies have successfully been exploited in several domains, providing both social and economic benefits. The realization of the full potential of the next generation of the Internet of Things still needs further research efforts concerning, for instance, the identification of new architectures, methodologies, and infrastructures dealing with distributed and decentralized IoT systems; the integration of IoT with cognitive and social capabilities; the enhancement of the sensing–analysis–control cycle; the integration of consciousness and awareness in IoT environments; and the design of new algorithms and techniques for managing IoT big data. This Special Issue is devoted to advancements in technologies, methodologies, and applications for IoT, together with emerging standards and research topics which would lead to realization of the future Internet of Things

IoT Data Processing for Smart City and Semantic Web Applications

The world has been experiencing rapid urbanization over the last few decades, putting a strain on existing city infrastructure such as waste management, water supply management, public transport and electricity consumption. We are also seeing increasing pollution levels in cities threatening the environment, natural resources and health conditions. However, we must realize that the real growth lies in urbanization as it provides many opportunities to individuals for better employment, healthcare and better education. However, it is imperative to limit the ill effects of rapid urbanization through integrated action plans to enable the development of growing cities. This gave rise to the concept of a smart city in which all available information associated with a city will be utilized systematically for better city management. The proposed system architecture is divided in subsystems and is discussed in individual chapters. The first chapter introduces and gives overview to the reader of the complete system architecture. The second chapter discusses the data monitoring system and data lake system based on the oneM2M standards. DMS employs oneM2M as a middleware layer to achieve interoperability, and DLS uses a multi-tenant architecture with multiple logical databases, enabling efficient and reliable data management. The third chapter discusses energy monitoring and electric vehicle charging systems developed to illustrate the applicability of the oneM2M standards. The fourth chapter discusses the Data Exchange System based on the Indian Urban Data Exchange framework. DES uses IUDX standard data schema and open APIs to avoid data silos and enable secure data sharing. The fifth chapter discusses the 5D-IoT framework that provides uniform data quality assessment of sensor data with meaningful data descriptions

Redes autónomas e inteligentes para la monitorización de variables ambientales

El entendimiento de nuestro entorno, ya sea urbano o natural, es un tema de constante interés en la sociedad, tanto por razones de mejora de calidad de vida como preservación ecológica. En las últimas décadas, la tecnología ha sido la principal aliada para lograr este objetivo, siendo uno de los principales contribuyentes las redes de sensores inalámbricos, o WSN por sus siglas en inglés. No obstante, sigue existiendo una fuerte necesidad de monitorización en distintas temáticas, además que los avances tecnológicos recientes permiten profundizar en el conocimiento en algunas áreas de estudio. En este sentido, este trabajo pretende evaluar la tecnología de WSN reciente con el fin de diseñar y desarrollar sistemas que aporten soluciones a problemáticas reales. Por consiguiente, con el conocimiento obtenido a partir de lo anterior, se busca también contribuir a las WSN en un sentido científico literario. Dicho lo anterior, la presente tesis realiza aportaciones en dos campos: el tecnológico y el metodológico. Desde una perspectiva técnica, se presenta la implementación de un sistema autónomo para monitorización en viviendas y un sistema de monitorización no supervisado para zonas ecológicas marinas protegidas. El primero busca cubrir una necesidad de estimación del consumo energético-térmico de los sistemas de calefacción, con el cual poder gestionar de mejor manera este recurso. Para ello se desarrolló el prototipo de un nodo sensor WiFi de bajo consumo energético, capaz de sustentar su demanda de potencia con una etapa de energy harvesting termoeléctrico. Se utilizó este enfoque para poder ofrecer una solución intuitiva con poca interacción por parte de los usuarios. Con respecto al segundo, se pretende proveer una alternativa a los sistemas de monitorización de líneas costeras, donde se busca realizar análisis de corrientes marinas superficiales y variables físicas del entorno. Para este desarrollo fue necesario que el sistema pudiese ser desplegado de la manera más sencilla posible, minimizando el impacto en el entorno dada su clasificación como parque nacional protegido. Por estos motivos se diseñó, desarrolló e implementó una red de boyas de deriva asistida por dron, donde las primeras actuaban como nodos sensores y el dron ejercía como recolector de datos remoto, utilizando un protocolo de comunicaciones inalámbrico basado en la modulación LoRa.En tema de aportaciones metodológicas, se realizó una recopilación literaria de métricas para el análisis, selección y diseño de una WSN, con el afán de definir el impacto que estas presentan en dicha labor. Esto a su vez propició el desarrollo de una propuesta de metodología aplicable a nuevas implementaciones o sistemas activos con posibles mejoras. La metodología se realizó con el objetivo de proveer una serie de directrices claras al momento de diseñar una WSN, buscando también cubrir los aspectos más relevantes de estas mismas, es decir, la parte de hardware, red y requerimientos de una aplicación. Aunado a lo anterior, se ejemplifica el uso de dicha metodología, aplicada a tres escenarios tecnológicos distintos, para demostrar la relevancia de un diseño apropiado de una WSN.<br /

IoT and Sensor Networks in Industry and Society

The exponential progress of Information and Communication Technology (ICT) is one of the main elements that fueled the acceleration of the globalization pace. Internet of Things (IoT), Artificial Intelligence (AI) and big data analytics are some of the key players of the digital transformation that is affecting every aspect of human's daily life, from environmental monitoring to healthcare systems, from production processes to social interactions. In less than 20 years, people's everyday life has been revolutionized, and concepts such as Smart Home, Smart Grid and Smart City have become familiar also to non-technical users. The integration of embedded systems, ubiquitous Internet access, and Machine-to-Machine (M2M) communications have paved the way for paradigms such as IoT and Cyber Physical Systems (CPS) to be also introduced in high-requirement environments such as those related to industrial processes, under the forms of Industrial Internet of Things (IIoT or I2oT) and Cyber-Physical Production Systems (CPPS). As a consequence, in 2011 the German High-Tech Strategy 2020 Action Plan for Germany first envisioned the concept of Industry 4.0, which is rapidly reshaping traditional industrial processes. The term refers to the promise to be the fourth industrial revolution. Indeed, the first industrial revolution was triggered by water and steam power. Electricity and assembly lines enabled mass production in the second industrial revolution. In the third industrial revolution, the introduction of control automation and Programmable Logic Controllers (PLCs) gave a boost to factory production. As opposed to the previous revolutions, Industry 4.0 takes advantage of Internet access, M2M communications, and deep learning not only to improve production efficiency but also to enable the so-called mass customization, i.e. the mass production of personalized products by means of modularized product design and flexible processes. Less than five years later, in January 2016, the Japanese 5th Science and Technology Basic Plan took a further step by introducing the concept of Super Smart Society or Society 5.0. According to this vision, in the upcoming future, scientific and technological innovation will guide our society into the next social revolution after the hunter-gatherer, agrarian, industrial, and information eras, which respectively represented the previous social revolutions. Society 5.0 is a human-centered society that fosters the simultaneous achievement of economic, environmental and social objectives, to ensure a high quality of life to all citizens. This information-enabled revolution aims to tackle today’s major challenges such as an ageing population, social inequalities, depopulation and constraints related to energy and the environment. Accordingly, the citizens will be experiencing impressive transformations into every aspect of their daily lives. This book offers an insight into the key technologies that are going to shape the future of industry and society. It is subdivided into five parts: the I Part presents a horizontal view of the main enabling technologies, whereas the II-V Parts offer a vertical perspective on four different environments. The I Part, dedicated to IoT and Sensor Network architectures, encompasses three Chapters. In Chapter 1, Peruzzi and Pozzebon analyse the literature on the subject of energy harvesting solutions for IoT monitoring systems and architectures based on Low-Power Wireless Area Networks (LPWAN). The Chapter does not limit the discussion to Long Range Wise Area Network (LoRaWAN), SigFox and Narrowband-IoT (NB-IoT) communication protocols, but it also includes other relevant solutions such as DASH7 and Long Term Evolution MAchine Type Communication (LTE-M). In Chapter 2, Hussein et al. discuss the development of an Internet of Things message protocol that supports multi-topic messaging. The Chapter further presents the implementation of a platform, which integrates the proposed communication protocol, based on Real Time Operating System. In Chapter 3, Li et al. investigate the heterogeneous task scheduling problem for data-intensive scenarios, to reduce the global task execution time, and consequently reducing data centers' energy consumption. The proposed approach aims to maximize the efficiency by comparing the cost between remote task execution and data migration. The II Part is dedicated to Industry 4.0, and includes two Chapters. In Chapter 4, Grecuccio et al. propose a solution to integrate IoT devices by leveraging a blockchain-enabled gateway based on Ethereum, so that they do not need to rely on centralized intermediaries and third-party services. As it is better explained in the paper, where the performance is evaluated in a food-chain traceability application, this solution is particularly beneficial in Industry 4.0 domains. Chapter 5, by De Fazio et al., addresses the issue of safety in workplaces by presenting a smart garment that integrates several low-power sensors to monitor environmental and biophysical parameters. This enables the detection of dangerous situations, so as to prevent or at least reduce the consequences of workers accidents. The III Part is made of two Chapters based on the topic of Smart Buildings. In Chapter 6, Petroșanu et al. review the literature about recent developments in the smart building sector, related to the use of supervised and unsupervised machine learning models of sensory data. The Chapter poses particular attention on enhanced sensing, energy efficiency, and optimal building management. In Chapter 7, Oh examines how much the education of prosumers about their energy consumption habits affects power consumption reduction and encourages energy conservation, sustainable living, and behavioral change, in residential environments. In this Chapter, energy consumption monitoring is made possible thanks to the use of smart plugs. Smart Transport is the subject of the IV Part, including three Chapters. In Chapter 8, Roveri et al. propose an approach that leverages the small world theory to control swarms of vehicles connected through Vehicle-to-Vehicle (V2V) communication protocols. Indeed, considering a queue dominated by short-range car-following dynamics, the Chapter demonstrates that safety and security are increased by the introduction of a few selected random long-range communications. In Chapter 9, Nitti et al. present a real time system to observe and analyze public transport passengers' mobility by tracking them throughout their journey on public transport vehicles. The system is based on the detection of the active Wi-Fi interfaces, through the analysis of Wi-Fi probe requests. In Chapter 10, Miler et al. discuss the development of a tool for the analysis and comparison of efficiency indicated by the integrated IT systems in the operational activities undertaken by Road Transport Enterprises (RTEs). The authors of this Chapter further provide a holistic evaluation of efficiency of telematics systems in RTE operational management. The book ends with the two Chapters of the V Part on Smart Environmental Monitoring. In Chapter 11, He et al. propose a Sea Surface Temperature Prediction (SSTP) model based on time-series similarity measure, multiple pattern learning and parameter optimization. In this strategy, the optimal parameters are determined by means of an improved Particle Swarm Optimization method. In Chapter 12, Tsipis et al. present a low-cost, WSN-based IoT system that seamlessly embeds a three-layered cloud/fog computing architecture, suitable for facilitating smart agricultural applications, especially those related to wildfire monitoring. We wish to thank all the authors that contributed to this book for their efforts. We express our gratitude to all reviewers for the volunteering support and precious feedback during the review process. We hope that this book provides valuable information and spurs meaningful discussion among researchers, engineers, businesspeople, and other experts about the role of new technologies into industry and society

On the Support of Massive Machine-to-Machine Traffic in Heterogeneous Networks and Fifth-Generation Cellular Networks

The widespread availability of many emerging services enabled by the Internet of Things (IoT) paradigm passes through the capability to provide long-range connectivity to a massive number of things, overcoming the well-known issues of ad-hoc, short-range networks. This scenario entails a lot of challenges, ranging from the concerns about the radio access network efficiency to the threats about the security of IoT networks. In this thesis, we will focus on wireless communication standards for long-range IoT as well as on fundamental research outcomes about IoT networks. After investigating how Machine-Type Communication (MTC) is supported nowadays, we will provide innovative solutions that i) satisfy the requirements in terms of scalability and latency, ii) employ a combination of licensed and license-free frequency bands, and iii) assure energy-efficiency and security

Design of Real-Time Simulation Testbed for Advanced Metering Infrastructure (Ami) Network

Conventional power grids are being superseded by smart grids, which have smart meters as one of the key components. Currently, for the smart metering communication, wireless technologies have predominantly replaced the traditional Power Line Communication (PLC). Different vendors manufacture smart meters using different wireless communication technologies. For example, some vendors use WiMAX, others prefer Low-Power Wireless Personal Area Networks (Lo-WPAN) for the Media Access Control (MAC) and physical layer of the smart meter network, also known as Advanced Metering Infrastructure (AMI) network. Different communication techniques are used in various components of an AMI network. Thus, it is essential to create a testbed to evaluate the performance of a new wireless technology or a novel protocol to the network. It is risky to study cyber-security threats in an operational network. Hence, a real-time simulation testbed is considered as a substitute to capture communication among cyber-physical subsystems. To design the communication part of our testbed, we explored a Cellular Internet of Things (CIoT) : Co-operative Ultra NarrowBand (C-UNB) technology for the physical and the MAC layer of the Neighborhood Area Network (NAN) of the AMI. After successful evaluation of its performance in a Simpy python simulator, we integrated a module into Network Simulator-3 (NS-3). As NS-3 provides a platform to incorporate real-time traffic to the AMI network, we can inject traffic from power simulators like Real Time Digital Simulator (RTDS). Our testbed was used to make a comparative study of different wireless technologies such as IEEE 802.11ah, WiMAX, and Long Term Evolution (LTE). For the traffic, we used HTTP and Constrained Application Protocol (CoAP), a widely used protocol in IoT. Additionally, we integrated the NS-3 module of Device Language Message Specification - Companion Specification for Energy Metering (DLMS-COSEM), that follows the IEC 62056 standards for electricity metering data exchange. This module which comprises of application and transport layers works in addition with the physical and MAC layer of the ii C-UNB module. Since wireless communication is prone to eavesdropping and information leakages, it is crucial to conduct security studies on these networks. Hence, we performed some cyber-attacks such as Denial of Service (DoS), Address Resolution Protocol (ARP) spoofing and Man-in-the-Middle (MiTM) attacks in the testbed, to analyze their impact on normal operation of AMI network. Encryption techniques can alleviate the issue of data hijacking, but makes the network traffic invisible, which prevents conventional Intrusion Detection Systems (IDS) from undertaking packet-level inspection. Thus, we developed a Bayesian-based IDS for ARP spoof detection to prevent rogue smart meters from modifying genuine data or injecting false data. The proposed real time simulation testbed is successfully utilized to perform delay and throughput analysis for the existing wireless technologies alongwith the evaluation of the novel features of C-UNB module in NS-3. This module can be used to evaluate a broad range of traffic. Using the testbed we also validated our IDS for ARP spoofing attack. This work can be further utilized by security researchers to study different cyber attacks in the AMI network and propose new attack prevention and detection solution. Moreover, it can also allow wireless communication researchers to improve our C-UNB module for NS-3

Developing a monitoring systerm for early detection of LPG leakages for gas filling stations in Ghana

Capstone Project submitted to the Department of Engineering, Ashesi University in partial fulfillment of the requirements for the award of Bachelor of Science degree in Computer Engineering, April 2019Following the dreadful gas explosion at Atomic Junction, Accra-Ghana in the year 2017[2], the innocent public and owners of gas filling stations across the country continue to face fear in managing Liquified Petroleum Gas (LPG) filling stations. Gas explosions have caused loss of precious lives and huge economic loss to owners of gas filling stations and the government. In the past four years, the rate of fire explosion in Ghana has plummeted steadily and if measures are not put in place, the nation will be thrown into another series of gas explosions. To avert this situation, this project presents a monitoring system for the early detection of LPG leakages using the concept of Internet of Things (IoT). The proposed solution presents the design and implementation of an integrated circuit unit which employs sensors, LCD display, buzzer and some other components all connected to ATMega8-p microcontroller. The sensor data obtained from these devices are sent from the microcontroller to a web application via GSM. The main features of the web application include data collection and analysis, database and tracking of gas stations. The impact of the LPG monitoring system is high. The results presented show that gas explosions are minimized if prompt precautions and safety knowledge about gas leakages are given to stakeholders involved in managing gas filling stations.Ashesi Universit

Research on Reliable Low-Power Wide-Area Communications Utilizing Multi-RAT LPWAN Technologies for IoT Applications

Předkládaná disertační práce je zaměřena na „Výzkum spolehlivé komunikace pro IoT aplikace v bezdrátových sítích využívajících technologie Multi-RAT LPWAN“. Navzdory značnému pokroku v oblasti vývoje LPWA technologií umožňující masivní komunikace mezi zařízeními (mMTC), nemusí tyto technologie výkonnostně dostačovat pro nově vznikající aplikace internetu věcí. Hlavním cílem této disertační práce je proto nalezení a vyhodnocení limitů současných LPWA technologií. Na základě těchto dat jsou nevrženy nové mechanismy umožňující snazší plánování a vyhodnocování síťového pokrytí. Navržené nástroje jsou vyladěny a validovány s využitím dat získaných z rozsáhlých měřících kampaních provedených v zákaznických LPWA sítích. Tato disertační práce dále obsahuje návrh LPWA zařízení vybavených více komunikačními rozhraními (multi-RAT) které mohou umožnit překonání výkonnostních limitů jednotlivých LPWA technologií. Současná implementace se zaměřuje zejména na snížení spotřeby zařízení s více rádiovými rozhraními, což je jejich největší nevýhodou. K tomuto účelu je využito algoritmů strojového učení, které jsou schopné dynamicky vybírat nejvhodnější rozhraní k přenosu.This doctoral thesis addresses the “Research on Reliable Low-Power Wide-Area Communications Utilizing Multi-RAT LPWAN Technologies for IoT Applications”. Despite the immense progress in massive Machine-Type Communication (mMTC) technology enablers such as Low-Power Wide-Area (LPWA) networks, their performance does not have to satisfy the requirements of novelty Internet of Things (IoT) applications. The main goal of this Ph.D. work is to explore and evaluate the limitations of current LPWA technologies and propose novel mechanisms facilitating coverage planning and assessment. Proposed frameworks are fine-tuned and cross-validated by the extensive measurement campaigns conducted in public LPWA networks. This doctoral thesis further introduces the novelty approach of multi-RAT LPWA devices to overcome the performance limitation of individual LPWA technologies. The current implementation primarily focuses on diminishing the greatest multi-RAT solutions disadvantage, i.e., increased power consumption by employing a machine learning approach to radio interface selection.