Some individuals and older adults have trouble remembering when to take their medication. A medication dispenser machine is one suggested solution to this problem. The purpose of this thesis is to design a prototype of a wireless machine for storing and releasing patients’ medication dosages at a certain time. The user can insert the medication schedule through a platform connected to the machine via wireless technology. In order to achieve the purpose, a literature study was conducted to gather and analyze information about wireless communication technologies to determine the most appropriate wireless technology for the thesis end device. The Arduino MKR NB 1500 is the core component of the prototype of the wireless system. Several types of tests were conducted on the system to evaluate its performance, as well as to determine NB-IoT coverage in real-world scenarios. The NB-IoT technology was proven to be the more suitable technology for the wireless pill dispensing machine and for other IoT applications. Moreover, the system performed satisfactorily in solving the defined problem. Despite this, the system could be improved in terms of design, mechanisms, and hygiene system of medicines. / Vissa människor eller äldre vuxna har svårighet att komma ihåg att ta sin medicin och hantera dem själva. En medicindispenser maskin är den föreslagna lösningen för detta problem. Syftet med detta examensarbete är att designa en prototyp av en trådlös maskin för att lagra och frigöra patienternas läkemedelsdoser vid en viss tidpunkt. Användaren kan infoga medicinschemat via en plattform ansluten till maskinen med hjälp av en lämplig trådlös teknik. För att uppnå syftet genomfördes en litteraturstudie för att samla in och analysera information om trådlös kommunikationsteknik för att bestämma den mest lämpliga trådlösa tekniken för arbetets slut enhet. Arduino MKR NB 1500 är kärnkomponenten i prototypen av det trådlösa systemet. Flera typer av tester utfördes på systemet för att utvärdera dess prestanda, samt för att fastställa NB-IoT-täckning i verkliga scenarier. NB-IoT tekniken har visat sig vara den mer lämpliga tekniken för den trådlösa medicindispenser maskinen och för andra IoT-applikationer. Dessutom fungerade systemet tillfredsställande för att lösa det definierade problemet. Trots detta skulle systemet kunna förbättras när det gäller design, mekanismer och hygiensystem för läkemedel.

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The automation industry interest in Internet of Things (IoT) and Microsoft Azure IoT Hub has increased, as it provides improvements in terms of reducing costs, increases revenue and provides efficient management of devices and machines. Prevas is a company working in this field and in this project the assignment was to look at the possibilities of improving an already existing solution they have.The aim was to set up a connection between a Programmable Logic Controller (PLC) and a Azure IoT hub and get the two components to communicate with each other. Through a simple application the PLC and the Azure IoT hub will exchange data with each other. To establish communication of results, the IoT Edge runtime has been installed to transform the Raspberry Pi into an IoT Edge device. The application was created in Node Red, where it was possible to create a connection and communication between the PLC and the Azure IoT hub. Through this application, notifications and messages can be sent between the PLC and the cloud. In the application, it is checked that a machine is working during specific times and if the machine is off when it should be running, an error message will be sent to the IoT hub. / Inom automationsindustrin har intresset för Internet of Things (IoT) och Microsoft Azure IoT-hubben ökat då det ger förbättringar i form av minskade kostnader och ökade intäkter. IoT tillhandahåller en effektiv hantering av enheter och maskiner då allt kan styras från en och samma plats. Prevas är ett företag som arbetar inom detta, och i detta projekt var uppdraget att se på möjligheterna att förbättra en befintlig lösning som de har.Syftet var att sätta upp en anslutning mellan en Programmable Logic Controller (PLC) och Azure IoT-hubben och få de två komponenterna att kommunicera. Genom en enkel applikation ska PLC:n och Azure IoT-hubben utbyta data med varandra. För att upprätthålla kommunikation för resultat har IoT Edge runtime installerats för att omvandla Raspberry Pi:n till en edge-enhet. Applikationen skapades i Node Red, där det var möjligt att skapa en anslutning och kommunikation mellan PLC:n och Azure IoT-hubben. Genom denna applikation kan meddelanden skickas mellan molnet och enheten. I applikationen så kontrolleras det att en maskin arbetar under specifika tider och är maskinen avstängd när den ska vara igång kommer ett felmeddelande att skickas till IoT-hubben.

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Various initiatives are carried out towards developing Smart cities that aim to make cities more sustainable. The Internet of Things (IoT) is a key aspect, where sensors are integrated in various „things‟, creating devices that are aware of, and respond to their environment. Bus shelters are among the facilities that are highly used by people in the city while commuting. Despite this high usage, they have remained the same technologically over the years. However, with new IoT technologies, bus shelters have the potential to be improved, providing a better experience to commuters, as well as creating value for businesses and public transport providers.This paper proposes a novel method that integrates IoT in bus shelters, enhancing the way information is displayed to the public through display screens. The information in focus involves digital signage advertising, public announcements or other information concerning the happenings nearby. The location and the time that the information is displayed are key factors considered, to effectively communicate the relevant information to the target audience. Furthermore, through the use of sensors, data analytics can be generated that describe the commuter traffic flow, thus providing useful information for public transport providers.Various use case scenarios are considered whereby smart bus shelters can be useful and a small scale prototype is developed to illustrate a proof of concept for the proposed solution. From the prototype, we demonstrate dynamic advertising through social media and show the potential of machine learning in predicting commuter flow from sensor data. We evaluate our work using questionnaires for the business and commuters, in order to find out the value created through implementing such a system. Additionally, we conduct functional testing of the prototype to evaluate its functionality. Other benefits are considered, such as reducing energy consumption by appliances such as lights, screens and smart heating systems for bus shelters.With our work, we hope to inspire further research into more suitable and innovative ways, in which bus shelters can be technologically enhanced. Furthermore, we believe that enhancements in bus shelters to provide a better experience for commuters while waiting for the bus, is a factor that could encourage more use of public transportation, providing value to public transport providers and local municipalities.

No / This paper addresses interoperability issues in an IoT-based cloud environment consisting of multiple WSN clusters made up of connected objects embedded with smart devices which are fully integrated to the Web, forming the Web-ofThings (WoT). Two levels of interoperability are considered: Device-level interoperability and semantic-level interoperability. Eminent issues relating to device heterogeneity and platform dependencies are resolved by using an OSGi (Open Service Gateway initiative) framework as the software fabric for IoT deployment. However, OSGi alone is not enough to resolve data heterogeneity issues, and even less in providing a semantic mapping of devices and their data streams in a generic deployment. To enable this level of interoperability, a novel system that envisages an all-purpose collaboration framework for the WoT to deliver Sensing and Collaboration as a Service (SeaaS/CaaS) is presented.

The rapid growth of the Internet of Things (IoT) has led to a situation where individual manufacturers develop their own communication protocols and frameworks that are often incompatible with other systems. Part of this is due to the use of incompatible communication hardware, and part is due to the entrenched proprietary systems. This has created a heterogeneous communication landscape, where it is difficult for devices to coordinate their efforts. To remedy this, a number of IoT Frameworks have been proposed to provide a common interface between IoT devices. There are many approaches to common frameworks, each with their strengths and weaknesses, but there is no clear winner among them. This thesis presents a virtual network testbed for implementing smart home IoT Frameworks. It consists of a simulated home network made up of multiple Virtual Machines (VM), simulated smart home devices and an implementation of the OpenHAB framework to integrate the devices. Simulated devices are designed to be network- accurate representations of actual devices, a LIFX smart lightbulb was developed and an existing Nest thermostat simulation was integrated. The demonstrated setup serves as a proof of concept for the idea of a home network testbed. Such a testbed could allow for the development of new IoT frameworks or the comparison of existing ones, and it could also serve as an education aid to illustrate how smart home IoT devices communicate with one another. / Master of Science

As Internet of Things (IoT) technology continues to become more commonplace, demand for self-sustainable and low-power networking schemes has increased. Future IoT devices will require a ubiquitous energy source and will need to be capable of low power communication. RF energy can be harvested through ambient or dedicated RF sources to satisfy this energy demand. In addition, these RF signals can be modified to convey information. This thesis surveys a variety of RF energy harvesting methods. A new low complexity energy harvesting system (circuit and antenna) is proposed. Low power communication schemes are examined, and low complexity and efficient transmitter designs are developed that utilize RF backscattering, harmonics, and intermodulation products. These communication schemes operate with minimal power consumption and can be powered solely from harvested RF energy. The RF energy harvester and RF-powered transmitters designs are validated through simulation, prototyping, and measurements. The results are compared to the performance of state-of-the-art devices described in the literature. / Master of Science / Future devices are expected to feature high levels of interconnectivity and have long lifetimes. RF energy from dedicated power beacons or ambient sources, such as Wi-Fi, cellular, DTV, or radio stations can be used to power these devices allowing them to be battery-less. These devices that harvest the RF energy can use that energy to transmit information. This thesis develops various methods to harvest RF energy and use this energy to transmit information as efficiently as possible. The designs are verified through simulation and experimental results.

Due to the ever increasing supply of new Internet of Things (IoT) devices being added onto a network, it is vital secure the devices from incoming cyber threats. The manufacturing process of creating and developing a new IoT device allows many new companies to come out with their own device. These devices also increase the network risk because many IoT devices are created without proper security implementation. Utilizing traffic patterns as a method of device type detection will allow behavior identification using only Internet Protocol (IP) header information. The network traffic captured from 20 IoT devices belonging to 4 distinct types (IP camera, on/off switch, motion sensor, and temperature sensor) are generalized and used to identify new devices previously unseen on the network. Our results indicate some categories have patterns that are easier to generalize, while other categories are harder but we are still able recognize some unique characteristics. We also are able to deploy this in a test production network and adapted previous methods to handle streaming traffic and an additional noise categorization capable of identify non-IoT devices. The performance of our model is varied between classes, signifying that much future work has to be done to increase the classification score and overall usefulness. / Master of Science / IoT (Internet of Things) devices are an exploding field, with many devices being created, manufactured, and utilized per year. With the rise of so many internet capable devices, there is a risk that the devices may have vulnerabilities and exploits able to allow unauthorized users to access. While a problem for a consumer network, this is an increased problem in an enterprise network, since much of the information on the network is sensitive and should be kept confidential and private. While a ban of IoT devices on a network is able to solve this problem, with the rise of machine learning able to characterize and recognize patterns, a smarter approach can be created to distinguish when and which types of IoT devices enter the network. Previous attempts to identify IoT devices used signature schemes specific to a single device, but this paper aims to generalize traffic behaviors and identifying a device category rather than a specific IoT device to ensure future new devices can also be recognized. With device category identification in place on an internet network, smarter approaches can be implemented to ensure the devices remain secure while still able to be used.

The unprecedented rise of IoT has revolutionized every business vertical enthralling people to embrace IoT applications in their day-to-day lives to accrue multifaceted benefits. It is absolutely fair to say that a day without connected IoT systems, such as smart devices, smart enterprises, smart homes or offices, etc., would hamper our conveniences, drastically. Many IoT applications for these connected systems are safety-critical, and any unauthorized access could have severe consequences to their consumers and society. In the overall IoT security spectrum, human-to-machine authentication for IoT applications is a critical and foremost challenge owing to highly prescriptive characteristics of conventional user authentication schemes, i.e., knowledge-based or token-based authentication schemes, currently used in them. Furthermore, studies have reported numerous users’ concerns, from both the security and usability perspectives, that users are facing in using available authentication schemes for IoT applications. Therefore, an impetus is required to upgrade user authentication schemes for new IoT age applications to address any unforeseen incidents or unintended consequences. This dissertation aims at designing next-generation user authentication schemes for IoT applications to secure connected systems, namely, smart devices, smart enterprises, smart homes, or offices. To accomplish my research objectives, I perform a thorough study of ways and types of user authentication mechanisms emphasizing their security and usability ramifications. Subsequently, based on the substantive findings of my studies, I design, prototype, and validate our proposed user authentication schemes. I exploit both physiological and behavioral biometrics to design novel schemes that provide implicit (frictionless), continuous (active) or risk-based (non-static) authentication for multi-user scenarios. Afterward, I present a comparative analysis of the proposed schemes in terms of accuracy against the available state-of-the-art user authentication solutions. Also, I conduct SUS surveys to evaluate the usability of user authentication schemes.