Smart agriculture is an increasingly popular field in which the technology of wireless sensor networks (WSN) has played a large role. Significant research has been done at Cal Poly and elsewhere to develop a computer vision (CV) and machine learning (ML) pipeline to monitor crops and accurately predict crop yield numbers. By autonomously providing farmers with this data, both time and money are saved. During the past development of a prediction pipeline, the primary focuses were CV and ML processing while a lack of attention was given to the collection of quality image data. This lack of focus in previous research presented itself as incomplete and inefficient processing models. This thesis work attempts to solve this image acquisition problem through the initial development and design of an Internet of Things (IoT) prototype network to collect consistent image data with no human interaction. The system is developed with the goals of being low-power, low-cost, autonomous, and scalable. The proposed IoT network nodes are based on the ESP32 SoC and communicate over-the-air with the gateway node via Bluetooth Low Energy (BLE). In addition to BLE, the gateway node periodically uplinks image data via Wi-Fi to a cloud server to ensure the accessibility of collected data. This research develops all functionality of the network, comprehensively characterizes the power consumption of IoT nodes, and provides battery life estimates for sensor nodes. The sensor node developed consumes a peak current of 150mA in its active state and sleeps at 162µA in its standby state. Node-to-node BLE data transmission throughput of 220kbps and node-tocloud Wi-Fi data transmission throughput of 709.5kbps is achieved. Sensor node device lifetime is estimated to be 682 days on a 6600mAh LiPo battery while acquiring five images per day. This network can be utilized by any application that requires a wireless sensor network (WSN), high data rates, low power consumption, short range communication, and large amounts of data to be transmitted at low frequency intervals.

Många kommuner i Sverige har påbörjat arbetet med publicering avöppna data, men de har många problem som behöver lösas. Den härstudien riktade in sig på att kartlägga problem som kommuner har, och tareda på eventuella lösningar som andra kommuner har hittat för atthantera det. Resultaten i studien tar upp problem som kommunerna harerfarit, och vilka lärdomar de tar med sig, samt kunskaper som kan förasvidare till andra kommuner som har liknande problem. Kontakt medkommuner har gjorts synkront genom digitala intervjuer, därrespondenterna har berättat om sitt nuläge av publicering av öppna data,och vad de har lärt sig. Resultatet som studien visade på innehåller blandannat förslag på hur man kan överkomma varierande problem, som t exägandeskap av data och specialistkompetenser.

The Internet of Things (IoT) is an important and expanding technology used for a large variety of applications to monitor and automate processes. The aim of this thesis is to present a way to find and assign locally unique IDs to access points (APs) in enormous wireless IoT systems where mobile tags are traversing the network and communicating with multiple APs simultaneously. This is done in order to improve the robustness of the system and increase the battery time of the tags. The resulting algorithm is based on transforming the problem into a graph coloring problem and solving it using approximate methods. Two metaheuristics: Simulated annealing and tabu search were implemented and compared for this purpose. Both of these showed similar results and neither was clearly superior to the other. Furthermore, the presented algorithm can also exclude nodes from the coloring based on the results in order to ensure a proper solution that also satisfies a robustness criterion. A metric was also created in order for a user to intuitively evaluate the quality of a given solution. The algorithm was tested and evaluated on a system of 222 APs for which it produced good results.

<p dir="ltr">We are in the midst of the fourth industrial revolution, and manufacturers are looking<br>to digitally transform their processes in order to leverage new technologies such as adap-<br>tive automation, virtual reality and digital twin driven simulation. A key aspect of this<br>revolution compared to previous is the increased availability of data and accessibility of<br>machines throughout the production process enabled by cyber-physical systems (CPS) and<br>IoT. However, the integration of many devices is challenging, requiring significant capital<br>and expertise. This can limit smaller players from benefiting from technological gains as<br>well as stymie research, particularly advanced human-computer-interaction (HCI) investiga-<br>tions which are becoming increasingly relevant.<br>Thus in this thesis we develop a framework for CPS creation and communication that<br>is amenable to the needs of HCI and convergence research. We develop several middleware<br>components to bridge the communication gap of many common fabrication machines and<br>other devices. The middleware translates device specific protocols into a shared language to<br>alleviate the user interface (UI) programs of this responsibility and promote reuse. Addi-<br>tionally, we develop an extension to the glTF model format to leverage this shared protocol<br>to enable the UI to load and interact with an arbitrary number of devices in an intuitive<br>manner at runtime. Finally, we discuss several applications to demonstrate the system’s<br>utility for research.</p>

In recent years, there is an increasing use of smart Internet of Things (IoT) devices in our everyday lives. Cyberattacks on consumer IoT devices are also increasing. IoT certification is an active topic of research with many proposed frameworks for IoT cybersecurity certification and also proposing labels that can be used to represent the security and privacy levels of consumer IoT devices. The research problem that this thesis tried to solve was first, to understand why certification for consumer IoT devices was less used than expected, and second, define robust and complete processes for security and certification on consumer IoT devices, that will be used to broadly raise their security level. From a literature review performed, we became aware that the reason why little progress towards consumer IoT cybersecurity certification is not that research and frameworks do not exist, but there are multiple other responsible factors. Such factors are the lack of a universal cybersecurity framework and the fact that the consumers are not involved in the certification process of the frameworks. The framework that was designed in this thesis project tries to address all of the above factors. Design Science Research (DSR) was used as the methodology for developing and evaluating the artifact of this work, which is a framework that describes how to properly apply and certify cybersecurity on consumer IoT devices, building on top of existing cybersecurity procedures, frameworks and tools. During the design of the framework, further literature searches were performed for identifying important steps that need to be carried out. The framework proposed in this project, does not limit itself to the vendor of such devices as the only involved actor, but consumers and cybersecurity regulating authorities are also involved in the process. The evaluation of the framework showed that, if applied, it could adequately improve the cybersecurity of existing consumer IoT products by detecting and solving all of the common vulnerabilities and security weaknesses, as it was demonstrated on one use case selected. The significance of this work is that it is the first step towards a universal cybersecurity certification for consumer IoT devices.

State and specifically location estimation is a core concept in automation and is a well-researched field. One such estimation technique is Moving Horizon Estimation (MHE). In this thesis, the MHE variant single-shooting estimation will estimate the location and velocity of a moving object. The moving object is equipped with an  Inertial Measuring Unit (IMU)  measuring acceleration and angular velocity. This thesis will explore pre-integrating the IMU measurement on the device attached to the moving object and using them in another device running the MHE. The acceleration and angular velocity measurements are measured in the local frame of reference of the moving object, rotating the measurement to a global frame of reference requires a known rotation of the tracked object, finding this rotation is also a task in this thesis. This thesis found the presented theory ill-equipped to estimate the object's state without an angle measurement, this thesis assumed any such measurement is made from a magnetometer but the solution presented is not biased towards any other method of measuring angles. With the addition of an angel measurement, the estimation performs at a decimeter-level precision for location.

Rockfall, which is the detachment of rocks from a mountain, is a major hazard in the mining industry. To help combat this issue, this thesis aims to develop a sensor platform that is able to detect both the potential risk for rockfall and if any rocks do hit the ground. The platform requires wireless communication in order to output relevant information and in order to be part of an IoT-network of sensors.The design of the platform used three different sensors, a geophone, an accelerometer and a microphone. The main focus of the design process was to keep the platform low power, enabling long operation times. The final design had data output from both the microphone and accelerometer, with the accelerometer able to pick up the impact from a falling barbell. Wireless transmission of data is possible for up to 7.5 meters using Bluetooth Low Energy. The low power design was met, with an average current consumption of 26 milliamperes during transmission using Bluetooth Low Energy. That gives a theoretical operation time of 27 days with the battery used. As the accelerometer can pick up a falling object and with a theoretical lifetime of 27 days for the platform, it can be argued that the goals, except for detecting potential risk for rockfall, were met. In order to properly function, however, the platform needs more development, but the most important conclusion of the work is that it seems possible to build this type of platform. Further research and development outside the scope of the thesis is connecting several platforms together.

A promising approach to raising the caliber and accessibility of healthcare services is the development of Smart Healthcare Systems. However, the union of wireless networks and smart medical devices has created additional security issues, such as the possibility of identity theft, data breaches, and denial-of-service assaults. These flaws emphasize the significance of creating a safe and dependable smart healthcare system that can safeguard patient data and guarantee the confidentiality of private medical information. This study suggests adopting 5G security standards to address the security issues with smart healthcare systems. The STRIDE threat modeling approach, which includes six threat categories (spoofing, tampering, repudiation, information disclosure, denial of service, and elevation of privilege), is used in this study to investigate potential threats in smart healthcare systems. The report suggests using strong encryption protocols, such as AES-CCM and ECDH, between smart healthcare equipment and5G-AKA to reduce these potential threats. The proposed approach showed appreciable advancements in data security and privacy. According to the findings, 5G security standards can be used to efficiently reduce security risks in smart healthcare systems and establish a trustworthy and secure platform for delivering medical services. The study emphasizes the significance of including strong security controls in Smart Healthcare Systems to secure patient information and raise the standard of treatment generally.

With the dramatic growth of vehicles around the world, Vehicular Ad-hoc Networks (VANETs) have been proposed as a solution to advance road safety, improve transportation efficiency, and satisfy road users. In the VANET environment, vehicles communicate with each other and with road infrastructure in an ad-hoc manner. This communication may be safety-related or non-safety-related and may often include vehicle information (e.g., location, direction, speed, and control), road conditions, and events. A key component in assessing the veracity of the information is the trustworthiness of the information source. Thus, trust evaluation is one of the main requirements of VANET design. In this work, we investigate performance improvements in the trust evaluation framework of VANETs. First, we propose a risk-based trust evaluation model (RTEAM) to estimate the risk of taking action or refraining from action regarding a reported event (in case of receiving conflicting messages about the event's existence). Some trust metrics such as direct trust, hop-based trust values, proximity to the event, and consequences of acting on a wrong decision are used to estimate the risk of the vehicle’s actions. Vehicles make individual decisions by seeking the action with the lowest risk. Second, we propose a fog-based reputation evaluation model (FREM) to support trust management framework. We promote fog computing as a new paradigm since it can provide several services to users in the edge layer. In our work, Fog supports the decision-making process in the reputation evaluation framework. Fog nodes play a key role in collecting vehicles' reputation records and cooperating with the roadside units (RSUs) to update these records. We propose the use of Digital Trustworthiness Cards (DTC), where the latest reputation evaluation of a vehicle automatically appears on its card. The benefits of the DTC are twofold: 1) the communication load on vehicles is reduced, and 2) historical trust records are established for each vehicle. We also take advantage of fog’s familiarity and greater knowledge of the vehicles that frequently visit its zones; with more intimate knowledge, fog can smartly employ vehicles to perform specific tasks based on their experiences. Further, we implement a strategy for establishing trust based on specific task categories. This permits a nuanced evaluation of the vehicle best suited for the task at hand and has the further benefit of preventing malicious vehicles from being naively trusted based on successful completion of unimportant or non-safety-related tasks. Finally, we expand the role of the fog in the decision-making process when vehicles need to ensure the existence of serious events. We propose a fog-based event validation model (FEVM) to validate the event’s existence through cooperation between vehicles and fog nodes. The vehicles are used as mobile fog nodes, which compute their confidence in events based on the available information. Fog nodes then validate the event after combining vehicles’ confidence values by applying the Extended Dempster-Shafer (EDS) theory of evidence. To test our proposed models, we conduct many experiments to investigate their performance and compare them with other existing models.

Im Hinblick auf die Klimaziele der Bundesrepublik Deutschland konzentriert sich das Projekt Diggi Twin auf die nachhaltige Gebäudeoptimierung. Grundlage für eine ganzheitliche Gebäudeüberwachung und -optimierung bildet dabei die Digitalisierung und Automation im Sinne eines Smart Buildings. Das interdisziplinäre Projekt der FH Aachen hat das Ziel, ein bestehendes Hochschulgebäude und einen Neubau an klimaneutrale Standards anzupassen. Im Rahmen des Projekts werden bekannte Verfahren, wie das Building Information Modeling (BIM), so erweitert, dass ein digitaler Gebäudezwilling entsteht. Dieser kann zur Optimierung des Gebäudebetriebs herangezogen werden, sowie als Basis für eine Erweiterung des Bewertungssystems Nachhaltiges Bauen (BNB) dienen. Mithilfe von Sensortechnologie und künstlicher Intelligenz kann so ein präzises Monitoring wichtiger Gebäudedaten erfolgen, um ungenutzte Energieeinsparpotenziale zu erkennen und zu nutzen. Das Projekt erforscht und setzt methodische Erkenntnisse zu BIM und digitalen Gebäudezwillingen praxisnah um, indem es spezifische Fragen zur Energie- und Ressourceneffizienz von Gebäuden untersucht und konkrete Lösungen für die Gebäudeoptimierung entwickelt.