The design and construction of high-performance buildings have emerged as a preferred solution for reducing energy consumption and greenhouse gas emissions. However, sometimes there is a considerable gap between the design performance and the actual performance of the buildings. Post Occupancy Evaluations (POE) provide tools to quantify the performance relative to the occupant's health, well-being, and comfort. POE is getting widely accepted to obtain feedback for various parameters such as water, energy, indoor environmental quality, and occupant comfort. Key Performance Indicators (KPIs) can be derived based on the obtained feedback to determine the performance gaps. POE has evolved to be a robust scientific methodology; however, traditional methods of conducting POE have been proven time-consuming, inconsistent, and inefficient. This research aims to conceptualize the next generation of post occupancy evaluations that leverages cutting-edge technologies such as Building Information Modeling (BIM), Internet of Things based sensors (IoT), Geographic Information Systems (GIS), and digital twins. The key contributions of this research are presented in a series of manuscripts. In the first paper, the gaps in the existing POE were determined by conducting a thorough literature review. The observed gaps were classified in data collection, analysis, and visualization categories. Broader POE definition, spot measurements of parameters, and 2D plans and charts for visualization made the existing POE procedure time-consuming. Using digital twins that combine the geometric and parametric data from BIM models and built-environment data from GIS and sensor measurements were recommended as potential solutions to address the observed gaps. The second paper explored the application of BIM-IoT-GIS integration to conduct POE. Use case scenarios were developed to derive system requirements to host the BIM-IoT-GIS-integrated POE. Four sequential tests were conducted to integrate a BIM model from Revit and sensors' data from Excel with ArcGIS pro that contained the surrounding environment data. Based on lessons learned from the tests, an optimized workflow was recommended that can be used across a variety of projects. The third paper used the BIM-IoT-GIS-integration concept to create a holistic proof of concept for digital-twin-enabled POE. The proof of concept was validated by conducting a digital-twin-based POE on the STTC building on the Red River College campus in Winnipeg. The indoor thermal comfort was visualized within the STTC digital twin developed in ArcGIS Pro. The preliminary energy consumption analysis concluded that the STTC buildings' average energy savings were approximately 70,000 KWH/year. The potential users for digital-twin-enabled POE were presented with a comparison of iv existing POE and digital-twin-based POE over a survey and a focus group discussion. Based on opinion-based feedback, the conclusion can be made that digital twins improve the overall efficiency of POE. The fourth paper recommended the digital-twin-enabled POE procedure for UVic's engineering expansion project. It established the semantics for POE, followed by a digital twin execution plan that can be used for developing a digital twin during each phase (from planning to operations) of the project. Furthermore, the benefits of the digital-twin-enabled POE procedure were demonstrated by comparison with the existing POE procedure relative to the project phases. This study concluded that conducting the POE on the UVic ECS expansion project will enable the researchers to determine the effectiveness of sustainable features by comparing the performance of existing and proposed facilities. In conclusion, BIM-IoT-GIS-integrated digital twins address the limitations of data collection, analysis, and visualization. These digital twins will enable multi-objective analysis and spatial-temporal visualization and provide deeper insights into the way these high-performance buildings function. / Graduate / 2023-05-24

[pt] A Internet das Coisas (IoT, do inglês Internet of Things) refere-se à infraestrutura tecnológica emergente formada por objetos cotidianos e ambientes dotados de computação e conectividade a fim de fornecer serviços digitalmente enriquecidos e comportamentos responsivos no mundo físico. Como com toda tecnologia, nas pontas da IoT há as pessoas que projetam e as que usam essa tecnologia de alguma forma. Projetar a interação para a IoT apresenta desafios novos e antigos. Nesta tese, eu abordo dois deles, a metacomunicação e a apropriação. O primeiro tem a ver com as pessoas que projetam a IoT; o último, com as que usam. Aplicando a Engenharia Semiótica como uma lente teórica ao estudo da IoT, realizei seis estudos usando diferentes métodos cujos resultados foram combinados em três contribuições. Primeiro, proponho um modelo semiótico de apropriação de tecnologia como uma ferramenta epistêmica para apoiar projetistas a refletirem sobre como os usuários adotam a tecnologia de IoT. Segundo, proponho uma caracterização semiótica para a tecnologia da IoT como metacomunicação, chamada de engenharia semiótica de tecnologias multiníveis e multilaterais, uma ferramenta inicial para a aplicação de princípios e métodos de Engenharia Semiótica à tecnologia da IoT. Terceiro, minha abordagem de pesquisa foi generalizada em um macro-método para pesquisa em tecnologias inovadoras como uma alternativa útil para pesquisas onde há falta de consenso e/ou diversidade metodológica e epistemológica, como em novas tecnologias. Essas contribuições estendem os conhecimentos da Engenharia Semiótica como teoria e fornecem recursos poderosos para projetistas e pesquisadores refletirem sobre a tecnologia de uma maneira centrada no ser-humano, eu argumento. / [en] The Internet of Things (IoT) refers to the emerging technological infrastructure formed by everyday objects and environments endowed with computing and networking power in order to provide digitally enhanced services and responsive behaviors in the physical world. As with every technology, at the end points of the IoT, there are people designing and using this technology somehow. Designing interaction for the IoT presents old and new challenges. In this thesis, I address two of them, namely metacommunication and appropriation. The former has to do with the people who design the IoT; the latter, with those who use it. By applying Semiotic Engineering as a theoretical lens to the study of IoT technology, I conducted six studies using different research methods which results were combined in three contributions. Firstly, I am proposing a semiotic model of technology appropriation, which is proposed as an epistemic tool to support designers reflect on how users adopt IoT technology. Secondly, I am proposing a semiotic characterization of IoT technology as metacommunication called the semiotic engineering of multi-level and multi-sided technologies, as an initial framework for the application of Semiotic Engineering principles and methods to IoT technology. Thirdly, my research design was generalized into a macro-method for approaching innovative technologies research. I claim that it is an useful alternative in research domains where there is a lack of methodological and epistemological consensus and/or diversity, such as with new technologies. These contributions both extend the body of knowledge of semiotic engineering as a theory and provide powerful resources for designers and researchers to reflect on technology in a human-centered way, I argue.

Today's Internet is seeing a massive shift from traditional client-server applications towards real-time, context-sensitive, and highly immersive applications. The fusion between Cyber-physical systems, The Internet of Things (IoT), Augmented/Virtual-Reality (AR/VR), and the Tactile Internet with the Human-in-the-Loop (TaHIL) means that Ultra-Reliable Low Latency Communication (URLLC) is a key functional requirement. Mobile Edge Computing (MEC) has emerged as a network architectural paradigm to address such ever-increasing resource demands. MEC leverages networking and computational resource pools that are closer to the end-users at the far edge of the network, eliminating the need to send and process large volumes of data over multiple distant hops at central cloud computing data centers. Multiple 'cloudlets' are formed at the edge, and the access to resources is shared and federated across them over multiple network domains that are distributed over various geographical locations. However, this federated access comes at the cost of a fuzzy and dynamically-changing network security perimeter because there are multiple sources of mobility. Not only are the end users mobile, but the applications themselves virtually migrate over multiple network domains and cloudlets to serve the end users, bypassing statically placed network security middleboxes and firewalls. This work aims to address this problem by proposing adaptive network security measures that can be dynamically changed at runtime, and are decoupled from the ever-changing network topology. In particular, we: 1) use the state of the art in programmable networking to protect MEC networks from internal adversaries that can adapt and laterally move, 2) Automatically infer application security contexts, and device vulnerabilities, then evolve the network access control policies to segment the network in such a way that minimizes the attack surface with minimal impact on its utility, 3) propose new metrics to assess the susceptibility of edge nodes to a new class of stealthy attacks that bypasses traditional statically placed Intrusion Detection Systems (IDS), and a probabilistic approach to pro-actively protect them.:Acknowledgments Acronyms & Abbreviations 1 Introduction 1.1 Prelude 1.2 Motivation and Challenges 1.3 Aim and objectives 1.4 Contributions 1.5 Thesis structure 2 Background 2.1 A primer on computer networks 2.2 Network security 2.3 Network softwarization 2.4 Cloudification of networks 2.5 Securing cloud networks 2.6 Towards Securing Edge Cloud Networks 2.7 Summary I Adaptive security in consumer edge cloud networks 3 Automatic microsegmentation of smarthome IoT networks 3.1 Introduction 3.2 Related work 3.3 Smart home microsegmentation 3.4 Software-Defined Secure Isolation 3.5 Evaluation 3.6 Summary 4 Smart home microsegmentation with user privacy in mind 4.1 Introduction 4.2 Related Work 4.3 Goals and Assumptions 4.4 Quantifying the security and privacy of SHIoT devices 4.5 Automatic microsegmentation 4.6 Manual microsegmentation 4.7 Experimental setup 4.8 Evaluation 4.9 Summary II Adaptive security in enterprise edge cloud networks 5 Adaptive real-time network deception and isolation 5.1 Introduction 5.2 Related work 5.3 Sandnet’s concept 5.4 Live Cloning and Network Deception 5.5 Evaluation 5.6 Summary 6 Localization of internal stealthy DDoS attacks on Microservices 6.1 Introduction 6.2 Related work 6.3 Assumptions & Threat model 6.4 Mitigating SILVDDoS 6.5 Evaluation 6.6 Summary III Summary of Results 7 Conclusion 7.1 Main outcomes 7.2 Future outlook Listings Bibliography List of Algorithms List of Figures List of Tables Appendix

<div>The exponential growth of Internet of Things (IoT) and cyber-physical systems is resulting in complex environments comprising of various devices interacting with each other and with users. In addition, the rapid advances in Artificial Intelligence are making those devices able to autonomously modify their behaviors through the use of techniques such as reinforcement learning (RL). There is thus the need for an intelligent monitoring system on the network edge with a global view of the environment to autonomously predict optimal device actions. However, it is clear however that ensuring safety and security in such environments is critical. To this effect, we develop a constrained RL framework for IoT environments that determines optimal devices actions with respect to user-defined goals or required functionalities using deep Q learning. We use anomaly based intrusion detection on the network edge to dynamically generate security and safety policies to constrain the RL agent in the framework. We analyze the balance required between ‘safety/security’ and ‘functionality’ in IoT environments by manipulating the exploration of safe and unsafe benefit state spaces in the RL framework. We instantiate the framework for testing on application layer control in smart home environments, and network layer control including network functionalities like rate control and routing, for SDN based environments.</div>

<p>The production of row crops in the Midwestern (Indiana) region of the US has been facing environmental and economic sustainability issues. There has been an increase in trend for the application of fertilizers (Nitrogen & Phosphorus), farm machinery fuel costs and decrease in labor productivity leading to non-optimized usage of farm-inputs. A structured literature review describes Lean and Green practices such as profitability (return on investments), operational cost reduction, hazardous waste reduction, delivery performance and overall productivity might be adopted in the context of Precision Agriculture practices (variable rate irrigation, variable rate fertilization, cloud-based analytics, and telematics for farm-machinery navigation). </p> <p>The literature review describes low adoption of Internet of Things (IoT) based precision agriculture practices, such as variable rate fertilizer (39 %), variable rate pesticide (8%), variable rate irrigation (4 %), cloud-based data analytics (21 %) and telematics (10 %) amongst Midwestern row crop producers. Barriers for the adoption of IoT based Precision Agriculture practices include cost effectiveness, power requirements, communication range, data latency, data scalability, data storage, data processing and data interoperability. Focused group interviews (n=3) with Subject Matter Expertise (SME’s) (N=18) in IoT based Precision Agriculture practices were conducted to understand and define decision-making variables related to barriers. The content analysis and subsequent ISM model informed an action research approach in the deployment of an IoT wireless sensor nodes for performance improvement. The improvements resulted in variable cost reduction by 94 %, power consumption cost reduction by 60 %, and improved data interoperable and user-interactive IoT wireless sensor-based data pipeline for improved adoption of Precision Agriculture practices. A relationship analysis of performance data (n=2505) from the IoT sensor deployment empirically validated the ISM model and explained the variation in power consumption for mitigation of IoT adoption among producers. The scope of future research for predicting IoT power consumption, based upon the growing season through correlation was developed in this study. </p> <p>The implications of this research inform adopters (row-crop producers), researchers and precision agriculture practitioners that a Lean and Green framework is driven substantively by cost and power concerns in an IoT sensors-based precision agriculture solution. </p>

Many conventional forms of communication technology, such as Wi-Fi, 3G/4G or cable, require a lot of power. For battery powered devices that need to last a long time on a single charge, one alternative is the low-power, long range technology LoRaWAN. This thesis tries to answer the question how well do the properties of LoRaWAN meet the requirements for a battery powered security solution? Two identical prototype remote motion detectors were implemented for this purpose. The results show that while the prototypes do not meet the requirements for energy efficiency, LoRaWAN as a technology easily does. The results shows that if a solution to the reliability issues can be found, LoRaWAN would be well suited for battery powered security solutions. / Många vanliga teknologier som används för kommunikation, så som Wi-Fi, 3G/4G eller fiber, kan vara väldigt strömkrävande. Ett alternativ för batteridrivna enheter som behöver kunna klara sig på en laddning under lång tid, är att använda en lågenergiteknologi med lång räckvidd LoRaWAN. Den här rapporten försöker att besvara frågan om hur väl LoRaWANs egenskaper tillgodoser de krav som ställs på batteridrivna säkerhetslösningar. För detta ändamål utvecklades två identiska prototyper av en batteridriven rörelsesensor. Resultaten visar på att även om prototyperna inte möter energikonsumptionskraven, så gör själva LoRaWAN-tekniken detta. Resultaten visar att om man kan hitta lösningar på problemen med pålitligheten hos LoRaWAN, så kan LoRaWAN mycket väl vara lämpligt för batteridrivna säkerhetslösningar.

Immense amounts of water are wasted daily, and it is as important as ever to optimize our water consumption, especially considering that today around 850 million people lack access to clean water. With the rise of the Internet of Things, creating a monitoring system for this purpose becomes easier, but there arises a problem of interfacing water meters to IoT capable devices.In this thesis a framework for IoT smart water monitoring is presented. Both short range and long range communication techniques are shown, compared and discussed. Similarly, different smart water meters and their characteristics are compared.The main goal of this thesis was to implement an interface between a sensor node and the water meter, ensuring the transmission of data in an easy way. To achieve this goal, a M-Bus library integrated into Contiki-OS is presented, thereby showing that it is possible to interface a water meter with a sensor node. The implemented library is capable of changing some of the configurations of the water meter, receiving data from the water meter, as well as forwarding the data via MQTT or CoAP protocols for further processing on the server side. / Stora mängder vatten slösas dagligen och det är viktigt nu att vi optimerar vattenförbrukningen, särskilt med tanke på att cirka 850 miljoner människor idag saknar tillgång till rent vatten. Med uppkomst av Sakernas Internet blir det lättare att skapa ett övervakningssystem för detta ändamål, men det finns fortfarande problem med att ansluta vattenmätare till IoT-kompatibla enheter.I detta arbete presenteras ett ramverk för smart vattenmätning med IoT. Både kortdistansoch långdistanskommunikationsteknik presenteras, jämförs och diskuteras. På samma sätt jämförs olika smarta vattenmätare och deras egenskaper.Huvudsyftet med denna arbetet var att implementera ett gränssnitt mellan en sensornod och vattenmätare, vilket säkerställer överföring av data på ett enkelt sätt. För att uppnå detta mål presenteras ett M-Bus-bibliotek integrerat i ContikiOS, vilket visar att det är möjligt att koppla en vattenmätare till en sensornod. Det implementerade biblioteket kan ändra delar av vattenmätarens konfigurering, ta emot data från vattenmätaren, samt vidarebefordra data via MQTT eller CoAP för vidare bearbetning hos servern.

Internet of Things (IoT) devices are becoming more ubiquitous than ever before, and while security is not that important for every type of device, it is crucial for some. In this thesis, a widely available Bluetooth smart lock is examined through the lens of security. By using well-known attack methods, an attempt is made to exploit potential vulnerabilities in the system.The researched lock was found to have design flaws that could be considered low-impact vulnerabilities, but using the system without these flaws in mind could lead to harmful outcomes for the lock owner.Except for the design flaws, no real security problems were discovered, but the methods used in this thesis should be applicable for further IoT security research. / IoT-apparater blir allt mer vanliga i samhället. Det är inte ett krav för alla typer av apparater att ha stark säkerhet, men för vissa är det helt avgörande. I denna avhandling undersöks ett allmänt tillgängligt Bluetooth-smartlås utifrån ett säkerhetsperspektiv. Genom att använda välkända angreppsmetoder görs det ett försök att utnyttja potentiella sårbarheter i systemet.Låset visade sig ha designfel som skulle kunna betraktas som sårbarheter med låg hotnivå, men att använda systemet utan dessa designfel i åtanke skulle kunna leda till farliga påföljder för låsägaren.Förutom designfelen upptäcktes inga riktiga säkerhetsproblem, men metoderna som används i denna avhandling bör vara tillämpliga för ytterligare säkerhetsforskning inom IoT.

M. Tech. (Department of Information Technology, Faculty of Applied and Computer Sciences), Vaal University of Technology. / This research was initiated because of a global increase in congestion on roads and the consequent increase in the rate of fatalities on both national and international roads. Annually, 1.3 million people are killed on the roads globally, and millions are injured. It was estimated that 2.4 million people will be killed in road traffic accidents annually by 2030, and in South Africa, over 14 000 deaths were reported in 2016. A study undertaken by the American Automobile Association Foundation for Traffic Safety (AAAFTS), established in 1947 to conduct research and address growing highway safety issues, found that motorcar accidents, on average, cost the United States $300 billion per annum. In the same vain, the World Health Organisation (WHO) asserted in their 2013 Global Status Safety Report on Road Safety that by 2020, traffic accidents would become the third leading cause of death globally. In this organisation’s 2015 report, South Africa was listed as having one of the highest road fatality rates in the world, averaging 27 out of 100 000 people. Cognisance of these statistics that describe wanton loss of life and serious economic implications, among other reasons, led to the development of autonomous vehicles (AVs), such as Google and Uber’s driverless taxis and Tesla’s autonomous vehicle. Companies have invested in self-driving prototypes, and they bolster this investment with continuous research to rectify imperfections in the technologies and to enable the implementation of AVs on conventional roads. This research aimed to address issues surrounding the systems communication concept, and focused on a novel method of the routing facet of AVs by exploring the mechanisms of the virtual system of packet switching and by applying these same principles to route autonomous vehicles. This implies that automated vehicles depart from a source address and arrive at a pre-determined destination address in a manner analogous to packet switching technology in computer networking, where a data packet is allotted a source and destination address as it traverses the Open Systems Interconnection (OSI) model for open system interconnection prior to dissemination through the network. This research aimed to develop an IoT model that reduces road congestion by means of a cost effective and reliable method of routing AVs and lessen dependency on vehicle-to-vehicle (V2V) communication with their heavy and costly sensor equipment and GPS, all of which under certain conditions malfunction. At the same time, as safety remains the foremost concern, the concept aimed to reduce the human factor to a considerable degree. The researcher demonstrated this by designing a computer-simulated Internet of Things (IoT) model of the concept. Experimental research in the form of a computer simulation was adopted as the most appropriate research approach. A prototype was developed containing the algorithms that simulated the theoretical model of IoT vehicular technology. The merits of the constructed prototype were analysed and discussed, and the results obtained from the implementation exercise were shared. Analysis was conducted to verify arguments on assumptions to clarify the theory, and the outcome of the research (an IoT model encompassing vehicular wireless technologies) shows how the basic concept of packet switching can be assimilated as an effective mechanism to route large-scale autonomous vehicles within the IoT milieu, culminating in an effective commuter operating system. Controlled routing will invariably save the traveller time, provide independence to those who cannot drive, and decrease the greenhouse effect, whilst the packet switching characteristic offers greater overall security. In addition, the implications of this research will require a workforce to supplement new growth opportunities.

<p>Despite the many security and privacy concerns associated with Internet-of-Things (IoT) devices, we continue to be barraged by new IoT devices every day. These devices have infiltrated almost every aspect of our lives, from government and corporations to our homes, and now, on and within our person, in the form of smartphones and wearables. These personal IoT devices can collect some of the most intimate pieces of data about their user. For instance, a smartwatch can record its wearer's heart rate, skin temperature, physical activity, and even GPS location data. At the same time, a smartphone has access to almost every piece of information related to its user, including text messages, social media activity, web browser history, and application-specific data. Due to the quantity and quality of data these personal IoT devices record, these devices have become critical sources of evidence during forensic investigations. However, there are instances in which digital forensic investigators need to make doubly sure that the data obtained from these smart devices, in fact, belong to the alleged owner of the smart device and not someone else. To that end, this dissertation provides the first look at using personal IoT device handling as a user identification technique with machine learning models to aid forensic investigations. The results indicated that this technique is capable of significantly differentiating device owners with performance metrics of .9621, .9618, and .9753, for accuracy, F1, and AUC, respectively, when using a smartwatch with statistical time-domain features. When considering the smartphone performance, the performance was only marginally acceptable with accuracy, F1, and AUC values of .8577, .8560, and .8891, respectively.  The results also indicate that female users handled their devices notably differently from male users. This study thus lays the foundation for performing user identification during a forensic investigation to determine whether the smart device owner did, in fact, use the device at the time of the incident.</p>