Implementation of Middleware for Internet of Things in Asset Tracking Applications: In-lining Approach

ThesisInternet of Things (IoT) is a concept that involves giving objects a digital identity and limited artificial intelligence, which helps the objects to be interactive, process data, make decisions, communicate and react to events virtually with minimum human intervention. IoT is intensified by advancements in hardware and software engineering and promises to close the gap that exists between the physical and digital worlds. IoT is paving ways to address complex phenomena, through designing and implementation of intelligent systems that can monitor phenomena, perform real-time data interpretation, react to events, and swiftly communicate observations. The primary goal of IoT is ubiquitous computing using wireless sensors and communication protocols such as Bluetooth, Wireless Fidelity (Wi-Fi), ZigBee and General Packet Radio Service (GPRS). Insecurity, of assets and lives, is a problem around the world. One application area of IoT is tracking and monitoring; it could therefore be used to solve asset insecurity. A preliminary investigation revealed that security systems in place at Central University of Technology, Free State (CUT) are disjointed; they do not instantaneously and intelligently conscientize security personnel about security breaches using real time messages. As a result, many assets have been stolen, particularly laptops. The main objective of this research was to prove that a real-life application built over a generic IoT architecture that innovatively and intelligently integrates: (1) wireless sensors; (2) radio frequency identification (RFID) tags and readers; (3) fingerprint readers; and (4) mobile phones, can be used to dispel laptop theft. To achieve this, the researcher developed a system, using the heterogeneous devices mentioned above and a middleware that harnessed their unique capabilities to bring out the full potential of IoT in intelligently curbing laptop theft. The resulting system has the ability to: (1) monitor the presence of a laptop using RFID reader that pro-actively interrogates a passive tag attached to the laptop; (2) detect unauthorized removal of a laptop under monitoring; (3) instantly communicate security violations via cell phones; and (4) use Windows location sensors to track the position of a laptop using Googlemaps. The system also manages administrative tasks such as laptop registration, assignment and withdrawal which used to be handled manually. Experiments conducted using the resulting system prototype proved the hypothesis outlined for this research

Design and implementation of an automated battery management platform

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2012.Cataloged from department-submitted PDF version of thesis. This electronic version was submitted and approved by the author's academic department as part of an electronic thesis pilot project. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 95-99).This thesis describes the design and the implementation of the hardware platform for automated battery management with battery changing/charging capability for autonomous UAV missions with persistency requirement that extends the mission duration beyond the life of a single UAV battery. The platform is tested through a series of missions lasting at least 3 hours to prove it meets design requirements and to show its feasibility. This thesis also provides a method to modify existing scenarios to proactively plan for the battery maintenance so that the overall system performance is increased. The modifications made to the problem definition increased the state-space significantly, and means of solving a problem of that scale needed to be developed. To address this challenge, this thesis extends a previously developed approach called Incremental Feature Dependency Discovery (iFDD) by allowing to use caches from computer science literature to make conversion from basic features to extended features faster. By doing so, this method significantly reduces the computational complexity.by Tuna Toksoz.S.M

Navigation and Geolocation Within Urban and Semi-Urban Environments Using Low-Rate Wireless Personal Area Networks

IEEE 802.15.4 defines networks and hardware capable of low power, low data rate transmissions. The use of these networks for the “Internet of Things”, machine to machine communications, energy metering, control and automation etc is increasing. In an urban environment, these networks may well soon become so popular and widespread in their usage that their discoverability and coverage density is sufficient for aiding geolocation – in the same way that IEEE 802.11 WiFi networks are used today. This research shows that although possible, there are some current inherent weaknesses in the use of IEEE 802.15.4 networks for location purposes particularly with respect to multilateration

Sensor Networks and Their Applications: Investigating the Role of Sensor Web Enablement

The Engineering Doctorate (EngD) was conducted in conjunction with BT Research on state-of-the-art Wireless Sensor Network (WSN) projects. The first area of work is a literature review of WSN project applications, some of which the author worked on as a BT Researcher based at the world renowned Adastral Park Research Labs in Suffolk (2004-09). WSN applications are examined within the context of Machine-to-Machine (M2M); Information Networking (IN); Internet/Web of Things (IoT/WoT); smart home and smart devices; BT’s 21st Century Network (21CN); Cloud Computing; and future trends. In addition, this thesis provides an insight into the capabilities of similar external WSN project applications. Under BT’s Sensor Virtualization project, the second area of work focuses on building a Generic Architecture for WSNs with reusable infrastructure and ‘infostructure’ by identifying and trialling suitable components, in order to realise actual business benefits for BT. The third area of work focuses on the Open Geospatial Consortium (OGC) standards and their Sensor Web Enablement (SWE) initiative. The SWE framework was investigated to ascertain its potential as a component of the Generic Architecture. BT’s SAPHE project served as a use case. BT Research’s experiences of taking this traditional (vertical) stove-piped application and creating SWE compliant services are described. The author’s findings were originally presented in a series of publications and have been incorporated into this thesis along with supplementary WSN material from BT Research projects. SWE 2.0 specifications are outlined to highlight key improvements, since work began at BT with SWE 1.0. The fourth area of work focuses on Complex Event Processing (CEP) which was evaluated to ascertain its potential for aggregating and correlating the shared project sensor data (‘infostructure’) harvested and for enabling data fusion for WSNs in diverse domains. Finally, the conclusions and suggestions for further work are provided

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

A service orientated architecture and wireless sensor network approach applied to the measurement and visualisation of a micro injection moulding process. Design, development and testing of an ESB based micro injection moulding platform using Google Gadgets and business processes for the integration of disparate hardware systems on the factory shop floor

Factory shop floors of the future will see a significant increase in interconnected devices for monitoring and control. However, if a Service Orientated Architecture (SOA) is implemented on all such devices then this will result in a large number of permutations of services and composite services. These services combined with other business level components can pose a huge challenge to manage as it is often difficult to keep an overview of all the devices, equipment and services. This thesis proposes an SOA based novel assimilation architecture for integrating disparate industrial hardware based processes and business processes of an enterprise in particular the plastics machinery environment. The key benefits of the proposed architecture are the reduction of complexity when integrating disparate hardware platforms; managing the associated services as well as allowing the Micro Injection Moulding (µIM) process to be monitored on the web through service and data integration. An Enterprise Service Bus (ESB) based middleware layer integrates the Wireless Sensor Network (WSN) based environmental and simulated machine process systems with frontend Google Gadgets (GGs) based web visualisation applications. A business process framework is proposed to manage and orchestrate the resulting services from the architecture. Results from the analysis of the WSN kits in terms of their usability and reliability showed that the Jennic WSN was easy to setup and had a reliable communication link in the polymer industrial environment with the PER being below 0.5%. The prototype Jennic WSN based µIM process monitoring system had limitations when monitoring high-resolution machine data, therefore a novel hybrid integration architecture was proposed. The assimilation architecture was implemented on a distributed server based test bed. Results from test scenarios showed that the architecture was highly scalable and could potentially allow a large number of disparate sensor based hardware systems and services to be hosted, managed, visualised and linked to form a cohesive business process

MODELING OF INNOVATIVE LIGHTER-THAN-AIR UAV FOR LOGISTICS, SURVEILLANCE AND RESCUE OPERATIONS

An unmanned aerial vehicle (UAV) is an aircraft that can operate without the presence of pilots, either through remote control or automated systems. The first part of the dissertation provides an overview of the various types of UAVs and their design features. The second section delves into specific experiences using UAVs as part of an automated monitoring system to identify potential problems such as pipeline leaks or equipment damage by conducting airborne surveys.Lighter-than-air UAVs, such as airships, can be used for various applications, from aerial photography, including surveying terrain, monitoring an area for security purposes and gathering information about weather patterns to surveillance. The third part reveals the applications of UAVs for assisting in search and rescue operations in disaster situations and transporting natural gas. Using PowerSim software, a model of airship behaviour was created to analyze the sprint-and-drift concept and study methods of increasing the operational time of airships while having a lower environmental impact when compared to a constantly switched-on engine. The analysis provided a reliable percentage of finding the victim during patrolling operations, although it did not account for victim behaviour. The study has also shown that airships may serve as a viable alternative to pipeline transportation for natural gas. The technology has the potential to revolutionize natural gas transportation, optimizing efficiency and reducing environmental impact. Additionally, airships have a unique advantage in accessing remote and otherwise inaccessible areas, providing significant benefits in the energy sector. The employment of this technology was studied to be effective in specific scenarios, and it will be worth continuing to study it for a positive impact on society and the environment

IntegraDos: facilitating the adoption of the Internet of Things through the integration of technologies

También, han sido analizados los componentes para una integración del IoT y cloud computing, concluyendo en la arquitectura Lambda-CoAP. Y por último, los desafíos para una integración del IoT y Blockchain han sido analizados junto con una evaluación de las posibilidades de los dispositivos del IoT para incorporar nodos de Blockchain. Las contribuciones de esta tesis doctoral contribuyen a acercar la adopción del IoT en la sociedad, y por tanto, a la expansión de esta prominente tecnología. Fecha de lectura de Tesis: 17 de diciembre 2018.El Internet de las Cosas (IoT) fue un nuevo concepto introducido por K. Asthon en 1999 para referirse a un conjunto identificable de objetos conectados a través de RFID. Actualmente, el IoT se caracteriza por ser una tecnología ubicua que está presente en un gran número de áreas, como puede ser la monitorización de infraestructuras críticas, sistemas de trazabilidad o sistemas asistidos para el cuidado de la salud. El IoT está cada vez más presente en nuestro día a día, cubriendo un gran abanico de posibilidades con el fin de optimizar los procesos y problemas a los que se enfrenta la sociedad. Es por ello por lo que el IoT es una tecnología prometedora que está continuamente evolucionando gracias a la continua investigación y el gran número de dispositivos, sistemas y componentes emergidos cada día. Sin embargo, los dispositivos involucrados en el IoT se corresponden normalmente con dispositivos embebidos con limitaciones de almacenamiento y procesamiento, así como restricciones de memoria y potencia. Además, el número de objetos o dispositivos conectados a Internet contiene grandes previsiones de crecimiento para los próximos años, con unas expectativas de 500 miles de millones de objetos conectados para 2030. Por lo tanto, para dar cabida a despliegues globales del IoT, además de suplir las limitaciones que existen, es necesario involucrar nuevos sistemas y paradigmas que faciliten la adopción de este campo. El principal objetivo de esta tesis doctoral, conocida como IntegraDos, es facilitar la adopción del IoT a través de la integración con una serie de tecnologías. Por un lado, ha sido abordado cómo puede ser facilitada la gestión de sensores y actuadores en dispositivos físicos sin tener que acceder y programar las placas de desarrollo. Por otro lado, un sistema para programar aplicaciones del IoT portables, adaptables, personalizadas y desacopladas de los dispositivos ha sido definido