<p dir="ltr">With advances in hardware and mobile computing capabilities, Mixed Reality (MR), which encompasses technologies from Augmented Reality (AR) to Virtual Reality (VR), has evolved from a laboratory concept into a mainstream product, as seen with popular releases like the Oculus Quest and Vision Pro. MR combines elements of both physical and virtual environments, enabling interactions and visualizations that transcend the limitations of the physical world. In this thesis, we aim to move beyond the conventional approach of treating MR as a standalone display medium. Specifically, we leverage advancements in IoT (internet of things) technology to fully integrate them into the interaction design.</p><p dir="ltr">On a broader level, our work in this thesis focuses on novel IoT design and integration, exploring how they can expand interaction possibilities in MR. This thesis is based on our four published conference papers (MechARspace, ColabAR, InstruMentAR, and LearnIoTVR), which explore the symbiosis between IoT and MR in different dimensions. In particular, we design IoT-enabled MR experiences to 1) promote social presence during remote collaboration, 2) enrich playfulness during the interaction, 3) streamline the in-situ creation of instrument tutorials, and 4) foster STEM education at minimum cost. Throughout our work, we focus on making novel interactions that improve user experiences while addressing real-world challenges. Additionally, we focus on designing with cost-effectiveness and usability in mind, aiming to lower entry barriers. Our goal is to allow end-users to adopt and engage with our system effortlessly.</p><p dir="ltr">Takeaways from the research series include 1) The usage of IoT modules, with their sensing and actuating capabilities, significantly enriches interaction modalities compared to traditional display-only MR interactions, 2) IoT, with its universal connectivity, enables spontaneous interactions commonly encountered in daily life, and 3) Mixed Reality, with its capability to generate immersive 3D experiences, can create a realistic digital replica of real-world IoT environments in a flexible and cost-effective way, supporting a wide range of applications.</p>

The increasing heterogeneity and connectivity of computer systems, from low-end embedded devices to high-end servers, present a unique security challenge. The ubiquity of these systems and their role in critical infrastructure has made them prime targets for cyberattacks, with potentially disastrous consequences. To address these threats, a broad spectrum of security techniques has been developed, combining hardware and software components. Among these, Trusted Computing technologies stand out, providing hardware Roots of Trust (RoTs), such as Trusted Execution Environments (TEEs), and robust software layers to implement foundational security primitives and services. However, these advanced architectures require specific hardware features, leaving devices without such capabilities — particularly resource-constrained low-end devices — vulnerable. For these devices, security must rely more heavily on software-based approaches, which can bridge the gap by providing critical protections in the absence of specialized hardware. This thesis highlights the need for balanced software-hardware security solutions to accommodate diverse hardware platforms. Focusing on Trusted Computing architectures and services, it proposes several software-hardware co-designs to either create security primitives from scratch, or extend existing ones. The research begins with the development of a novel software-based security stack that operates without relying on hardware security features. This stack, implemented on constrained low-end devices, achieves security guarantees comparable to those of high-end counterparts, even in the absence of fundamental components such as a Memory Protection Unit (MPU). At the core of our stack is a software-based Trusted Computing Base (TCB), functioning as a bare-metal \acrshort{tee} with a self-contained RoT. The TCB enables key security primitives, including memory isolation and privilege separation, and supports Trusted Applications (TAs) such as remote attestation and secure code update. The TCB is further extended with two key security mechanisms: a control-flow integrity system and a secure checkpointing solution for intermittent computing. Then, this thesis shows an example of software-hardware co-design from the opposite perspective, where a security feature like memory tagging implemented in hardware but not yet adequately used by existing software, can be leveraged to introduce a novel and more advanced exploit mitigation technique. By addressing the security gap between low- and high-end devices, this research demonstrates how flexible software-hardware architectures can enhance the security of modern multi-device ecosystems.

<p dir="ltr">With the ability to connect to networks and send and receive data, Internet of Things (IoT) devices involve associated security risks and threats, for a given environment. These threats are even more of a concern in a Smart Home network, where there is a lack of a dedicated security IT team, unlike a corporate environment. While efficient user interface(UI) and ease of use is at the front and center of IoT devices within Smart Home which enables its wider adoption, often security and privacy have been an afterthought and haven’t kept pace when needed. Therefore, a unsafe possibility exists where malicious actors could exploit vulnerable devices in a domestic home environment.</p><p dir="ltr">This thesis involves a detailed study of the cybersecurity for a Smart Home and also examines the various types of cyberthreats encountered, such as DDoS, Man-In-Middle, Ransomware, etc. that IoT devices face. Given, IoT devices are commonplace in most home automation scenarios, its crucially important to detect intrusions and unauthorized access. Privacy issues are also involved making this an even more pertinent topic. Towards this, various state of the art industry standard tools, such as Nmap, Nessus, Metasploit, etc. were used to gather data on a Smart Home environment to analyze their impacts to detect security vulnerabilities and risks to a Smart Home. Results from the research indicated various vulnerabilities, such as open ports, password vulnerabilities, SSL certificate anomalies and others that exist in many cases, and how precautions when taken in timely manner can help alleviate and bring down those risks.</p><p dir="ltr">Also, an IoT monitoring dashboard was developed based on open-source tools, which helps visualize threats and emphasize the importance of monitoring. The IoT dashboard showed how to raise alerts and alarms based on specific threat conditions or events. In addition, currently available cybersecurity regulations, standards, and guidelines were also examined that can help safeguard against threats to commonly used IoT devices in a Smart Home. It is hoped that the research carried out in this dissertation can help maintain safe and secure Smart Homes and provide direction for future work in the area of Smart Home Cybersecurity.</p>

This study addresses the challenges faced by industries requiring precise water quality monitoring by developing and evaluating a modular multi-sensor system. Existing solutions often lack scalability and flexibility, necessitating multiple devices for comprehensive analysis. The methodology employed a recursive prototype development approach, integrating various hardware and software components, including microcontrollers and a user-friendly mobile application. The prototype facilitated real-time data acquisition and management through a dedicated server, supporting essential water quality parameters such as pH, temperature, and conductivity. Results indicate that the system significantly enhances measurement accuracy and operational efficiency. However, the implementation of a smart home connectivity standard was unsuccessful, highlighting the complexities associated with integrating new communication protocols. Despite this, the system offers a scalable, cost-effective solution for continuous water quality monitoring, presenting significant improvements over existing technologies in terms of flexibility, user engagement, and data reliability. / Denna studie behandlar de utmaningar som industrier står inför som kräver noggrann övervakning av vattenkvalitet genom att utveckla och utvärdera ett modulärt multisensorsystem. Befintliga lösningar saknar ofta skalbarhet och flexibilitet, vilket kräver flera enheter för omfattande analys. Metodiken använde en rekursiv prototyputvecklingsansats, som integrerade olika hårdvaru- och mjukvarukomponenter, inklusive mikrokontroller och en användarvänlig mobilapplikation. Prototypen underlättade insamling och hantering av realtidsdata genom en dedikerad server, som stödde viktiga vattenkvalitetsparametrar såsom pH, temperatur och konduktivitet. Resultaten indikerar att systemet avsevärt förbättrar mätnoggrannhet och operationell effektivitet. Dock var implementeringen av smarta hem-anslutningsstandard inte framgångsrik, vilket belyser komplexiteten med att integrera nya kommunikationsprotokoll. Trots detta erbjuder systemet en skalbar, kostnadseffektiv lösning för kontinuerlig övervakning av vattenkvalitet, med betydande förbättringar jämfört med befintliga teknologier när det gäller flexibilitet, användarengagemang och datareliabilitet.

Noise is defined as any undesired sound. Urban noise and its effect on citizens area significant environmental problem, and the increasing level of noise has become a critical problem in some cities. Fortunately, noise pollution can be mitigated by better planning of urban areas or controlled by administrative regulations. However, the execution of such actions requires well-established systems for noise monitoring. In this thesis, we present a solution for noise measurement and classification using a low-power and inexpensive IoT unit. To measure the noise level, we implement an algorithm for calculating the sound pressure level in dB. We achieve a measurement error of less than 1 dB. Our machine learning-based method for noise classification uses Mel-frequency cepstral coefficients for audio feature extraction and four supervised classification algorithms (that is, support vector machine, k-nearest neighbors, bootstrap aggregating, and random forest). We evaluate our approach experimentally with a dataset of about 3000 sound samples grouped in eight sound classes (such as car horn, jackhammer, or street music). We explore the parameter space of the four algorithms to estimate the optimal parameter values for the classification of sound samples in the dataset under study. We achieve noise classification accuracy in the range of 88% – 94%.

[pt] À medida que a população cresce, mais alimentos precisarão ser produzidos nas próximas quatro décadas do que nos últimos 10.000 anos. No entanto, o mundo moderno ainda depende da produção de monoculturas de alto rendimento, cada vez mais ameaçada por condições climáticas incomuns, escassez de água e terra insuficiente. A fim de superar esses problemas e alimentar o mundo, é necessário um caminho prático para fornecer alimentos frescos, com qualidade e em escala, com mínima dependência do clima e com uso de água e pegada de carbono reduzidos. Uma abordagem razoável é construir fazendas verticais dentro das cidades em um ambiente fechado repleto de sensores e iluminação artificial controlada por software para uma produção e gestão eficiente do plantio de alimentos. Esta tese propõe a instanciação de um modelo, chamado Ciclo do Software dos Lugares (SoPC), que é capaz de responder a estímulos ambientais em um sistema fechado de produção de plantas com iluminação artificial que possibilite a criação de ambientes com auto-aprendizagem. Esta tese descreve o SoPC, as abordagens e processos de implementação de uma mini fábrica de plantas com iluminação artificial com base na discussão em cinco ciclos de pesquisa-ação. / [en] As the population grows, more food will need to be produced in the next four decades than has been in the past 10,000 years. However, the modern world still depends on high yield monoculture production which is increasingly threatened by unusual weather, water shortages, and insufficient land. In order to overcome these problems and feed the world, a practical path to provide quality fresh healthy food at scale with minimal weather dependency, water usage and reduced carbon footprint is necessary. One reasonable approach is to build vertical farms inside the cities in a close environment full of sensors and artificial lighting controlled by software for efficient production of food crops. This thesis proposes a model, entitled Software of Places Cycle (SoPC), that should be able to answer to environmental stimuli in a closed plant production system using artificial lighting in order to create a self-learning environment. This thesis describes the SoPC, the approaches and processes of implementing a mini Plant Factory using Artificial Lighting based on the discussion on five action-research cycles. The thesis main contribution is a conceptual model to guide the development and maintenance of a mini-PFAL (m-PFAL), a minor contribution is the deployment of the SoP, i.e., the very notion of having software dedicated to a specific place.

Internet des objets (IoT) est actuellement à notre portée. De nombreux domaines ont bénéficié de cette technologie. Cela va d'une application simple, comme l'identification d'un objet jusqu'à la gestion d'un système plus complexe. L'identification par radiofréquence (RFID) est l'une des technologies a une part importante dans l’IoT aujourd'hui. C’est une technologie embarqué, pas cher et ne nécessite aucune source d'alimentation supplémentaire dans le cas de tag passif. Avec sa fonctionnalité omniprésente, cette technologie permet de positionner un objet dans une zone spécifique. L’Assistance et l'Autonomie des personnes à Domicile (AAL) est l'un des nombreux domaines qui bénéficient de l'IoT. Il vise à aider les personnes âgées dans leurs routines quotidiennes en fournissant de nouveaux services d'assistance dans les maisons intelligentes (smart home). La présence de RFID dans une maison intelligente sont d'une grande aide pour une personne âgée et/ou déficiente, par exemple, pour l’aider à trouver un objet dans son environnement quotidien. Cependant, même avec tous ces avantages d’assistance dans notre vie, il est malheureusement à double tranchant où l'avantage qu'il apporte à un objet pourrait à son tour se tourner contre lui-même. En effet, pour pouvoir aider les personnes âgées à localiser un objet, le système nécessite certaines données relatives au positionnement de l'objet, tout au moins son identification. Étant donné que la couverture de l'étiquette RFID passive est très faible, une fois sa présence détectée, il est difficile de la cacher. La capacité de cette technologie à localiser des objets donne l'occasion à une tierce personne de profiter du système. Parallèlement au besoin persistant et constant de confidentialité par les utilisateurs, l'objectif de cette thèse consiste à améliorer la confidentialité dans la localisation d'un objet grâce à un nouveau protocole basé sur la deuxième génération de RFID passive. Le protocole proposé doit pouvoir empêcher un objet d'être identifié et localisé par des parties non autorisées ou par un lecteur malveillant. La première contribution de ce travail est l'évaluation de la gestion anti-collision RFID. Elle est réalisée par la création d'un modèle OMNET++, construit sur la base de la dernière norme RFID développée par GS1 et adaptée par ISO / IEC appelé Gen2V2 (RFID classe 2 Génération 2 Version 2). Dans cette norme une étiquette RFID passive ne nécessite aucune source d'alimentation interne. Il communique en utilisant la fréquence UHF. La norme Gen2V2 propose une liste de suites cryptographiques qui peuvent être utilisées comme méthodes pour authentifier une étiquette et un lecteur. Cette nouvelle génération d'étiquettes est soutenue par une alliance de fabricants appelée RAIN (RAdio frequency IdentifatioN) qui favorise l'adoption du Gen2V2. Nous évaluons les performances globales du protocole anti-collision et nous comparons ensuite quatre de ses suites cryptographiques, à savoir PRESENT80, XOR, AES128 et cryptoGPS pour garantir l’authentification lecteur/tag. Parmi les performances évaluées dans ce modèle, nous nous sommes intéressé au nombre de collisions et à la durée requise pour interroger un groupe d'étiquettes. Nous avons intégré en fonctionnalité de localisation dans le modèle en s’appuyant sur les messages échangés avant l’authentification, ce qui peut conduire à une localisation malveillante d'un objet. Pour augmenter la confidentialité de la localisation au sein des applications AAL, nous proposons donc une deuxième contribution qui est une nouvelle méthode de localisation basée sur les échanges standard Gen2V2 en anonymisant l'identité de l'étiquette. / Internet of things (IoT) is currently on our doorsteps. Numerous domains have beneted from this technology. It ranges from a simple application such as identifying an object up to handling a more complex system. The Radio Frequency IDentication (RFID) is one of the enabling technologies that drive the IoT to its position today. It is small, cheap and does not require any additional power sources. Along with its ubiquitous functionality, this technology enables the positioning of an object within a specic area. Ambient Assisted Living (AAL) is one of the many domains that benet from the IoT. It aims at assisting elderly people in their daily routines by providing new assistive services in smart homes for instance. RFIDs in a smart home come as a great help to an elderly person, for example, to nd an object that they misplaced. However, even with all its benets in simplifying our lives, it is unfortunately double-edged where the advantage that it brings to an object could in turn go against itself. Indeed to be able to help the older adults to locate an object, the system requires certain data in relation to the positioning of the object and its identication. As the passive RFID tag coverage is very small, once its presence is detected, it is dicult to hide it. The ability of this technology in localizing objects gives an opportunity to a third person to take an advantage of the system. In parallel with the persistent and constant need of privacy and secrecy by the users, the objective of this thesis consists of improving the privacy in localizing an object through a new protocol based on the latest version of the RFID second generation passive tag. The proposed protocol must be able to prevent an object from being identied and located by unauthorized parties or a malicious reader. The rst contribution of this work is the assessment of the RFID anti collision management. It is performed through the creation of an OMNET++ framework, modelled and built based on the latest RFID standard developed by GS1 and incorporated by ISO/IEC called Gen2V2 (RFID class 2 Generation 2 Version 2). It is a passive RFID tag that does not require any internal power sources to operate. It communicates using the UHF frequency. The Gen2V2 standard provides a list of cryptographical suites that can be used as a method to authenticate a tag and a reader. This new generation of tags is supported by an alliance of manufacturers called RAIN (RAdio frequency IdenticatioN) that promotes the adoption of the Gen2V2. The anti collision management overall performance is then compared with its theoretical value and four of its cryptographical suites namely PRESENT80, XOR, AES128 and cryptoGPS. Among the performances evaluated within the framework is the number of collisions and the duration required to interrogate a group of tags. Note that an addition of a localization functionality within the framework reveals that exchanged messages through wireless channel prior to the authentication can lead to a malicious localization of an object. To increase the localization privacy within AAL application, we propose therefore a second contribution which is a new localization method that is based on the current Gen2V2 standard exchanges by anonymizing the tag identity.

[pt] A popularização da Internet das Coisas (IoT) abriu uma série de oportuni-dades para a geração de novas aplicações que não eram possíveis anteriormente. No cenário atual de IoT existem marketplaces que vendem soluções completas para os clientes com objetos inteligentes, gateways para a transmissão dos dados e provedores que analisam estes por uma taxa de assinatura. Partimos da visão de que no futuro deverá ocorrer uma uberização de IoT, onde cada pessoa poderá oferecer dados de sensores e acesso a atuadores para outra e que eles estarão categorizados com base no QoS dos objetos que os fornecem, similarmente como são classificadas commodities hoje. Além disso, haverá plataformas multilaterais onde essas informações poderão ser negociadas em combinação com provedores de conectividade, para transmitir os dados, e de análise. Uma plataforma que fornece esse serviço deve garantir que o fluxo de dados (e do estado) de objetos seja contínuo, sem expor para o cliente algum problema de conectividade entre eles e os provedores. Ou seja, ela deve ter mecanismos para detectá-los e rapidamente selecionar novos provedores, isso dentro de um cenário de intensa troca de dados. Este trabalho apresenta como contribuições um mecanismo de detecção contínuo de problemas de conectividade que utiliza o paradigma Publish-Subscribe para o envio de mensagens de identificação de problemas e uma solução arquitetural de uma plataforma baseada em conceitos de marketplaces para IoT, que inclui os serviços de comoditização dos provedores de serviço e o matchmaking para selecionar uma combinação destes para prestar serviços para o cliente. Um estudo de caso no domínio de marketplaces é conduzido, com a análise dos serviços da plataforma em vários cenários de testes e a avaliação do mecanismo de detecção de problemas de conectividade, com a simulação de diferentes falhas na conexão. / [en] The popularization of the Internet of Things (IoT) opened up a series of opportunities for the generation of new applications that were not previously possible. In the current scenario of IoT there are marketplaces that sell complete solutions for users with smart objects, gateways for data transmission and providers that analyze these for a subscription fee. We start from the view that in the future an uberization of IoT should occur, where each person can offer sensor data and access to actuators to another and that they will be categorized based on the QoS of the objects that provide them, similarly as commodities are classified today. In addition, there will be multilateral platforms where this information can be negotiated in combination with connectivity providers, to transmit data, and analytics. A platform that provides this service must ensure that the data (and state) flow of objects is continuous, without exposing to the user any connectivity problems between them and the providers. That is, it must have mechanisms to detect problems and quickly select new providers, all this in a scenario of intense data exchange. This work presents as contributions a continuous connectivity problem detection mechanism that uses a Publish-Subscribe paradigm to send problem identification messages and an architectural solution of a platform based on marketplaces concepts for IoT, which includes the commoditization of service providers and a matchmaking service to select a combination of these to provide services to the customer. A case study in the domain of marketplaces is conducted, with the analysis of the services of the platform with several tests scenarios and the evaluation of the mechanism of detection of connectivity problems, with the simulation of different connection failures.

Les entités physiques prises en compte par les applications dites M2M dans les télécoms sont aujourd’hui de plus en plus hétérogènes. Le défi adressé par ce travail est donc l’intégration, et la configuration automatiques de toutes ces différentes variétés d’entités physiques d’une façon homogène dans les systèmes M2M, en généralisant les approches de configuration automatique déjà connues et utilisées pour les objets communicants numériques. Cette thèse présente un cadre théorique général et des mécanismes de base pour l’identification de modèles de telles entités physiques dans les systèmes d’information embarqués répartis, en englobant dans une même approche les équipements et les sous-ensembles de l’espace, faisant se rejoindre les points de vue ”internet des objets” et ”environnement interactif” dans une nouvelle vision unifiée de l’intelligence ambiante. Ce travail, motivé initialement par les applications à la gestion d’énergie domestique, cherche à intégrer au réseau local de la maison des entités physiques qui ont un impact énergétique mais ne sont dotés d’aucune connexion réseau, ce qui correspond à une extension qualitative du périmètre de l’Internet des Objets. Cette intégration se fait de manière tout à fait similaire à ce qui est fait classiquement pour des équipements numériques état de l’art, c’est-à-dire par des mécanismes de découverte et configuration spontanés. Ces mécanismes comportent les étapes suivantes : détection de la présence d’une entité physique par analyse de la coïncidence d’évènements significatifs reçus de capteurs ; sélection d’un premier modèle générique représentatif de l’entité physique détectée depuis une ontologie de référence en analysant des données reçues les capteurs ; création d’un composant logiciel représentant l’entité physique détectée, à partir du modèle sélectionné, et associant les capteurs et actionneurs utiles ; supervision et contrôle de l’entité cible par l’intermédiaire de ce composant logiciel ; mise à jour incrémentale du modèle de l’entité identifiée par analyse des données issues des capteurs associés. Ce travail est parti d’applications dans l’environnement de la maison, pour lesquelles il a été validé et mis en œuvre. Mais notre approche a vocation à être généralisée et étendue à des environnements comme les bâtiments ou la ville, en offrant suivant le même principe une infrastructure partagée pour toutes les applications M2M dans ces environnements / The physical entities which are taken into account by Machine to Machine (M2M) telecom applications are more and more heterogeneous. The challenge addressed by our research is the automatic integration and configuration of all these types of physical entities in M2M systems, with a homogeneous solution that generalizes self-configuration approaches used for networked digital devices. This thesis presents a general theoretical framework and basic mechanisms for the identification and configuration of such physical entity models in distributed embedded information systems. Our approach deals jointly with equipment and space entities encompassing the ”Internet of Things” (IoT) and ”interactive environment” viewpoints in a renewed interpretation of ambient intelligence. This work has been motivated initially by home energy management applications, trying to integrate into the Home Area Network all home entities that play a role in energy management, but do not have a networked interface of their own. This corresponds to a qualitative extension of the perimeter of the Home Area Network. This integration is achieved in a way similar to what is done for state of the art digital devices, through a spontaneous discovery and configuration mechanism, with the following stages: detection of the presence of a physical entity by analyzing the coincidence of significant events detected by sensors; selection of the first generic model corresponding to the detected physical entity from a reference ontology, on the basis of received sensors data; creation of a software component representing the detected physical entity, based on the selected model, associated with relevant sensors and actuators; provision of application interface for monitoring and control of the target entity through this intermediate software component; iterative update of the identified entity model on the basis of data from associated sensors. The proposed approach has been validated and implemented in home environments, but it is intended to be generalized and expanded to environments such as buildings or cities, offering a similarly shared infrastructure for all M2M applications in these environments

隨著物聯網這個萬物連網的概念順勢推動智慧家庭在市場裡蓬勃發展，可預期未來ISP(Internet Service Provider)業者勢必面臨大量智慧家庭中各種不同應用服務互相競爭頻寬資源的情況，甚至遇到網路滿載壅塞時造成應用服務不堪使用的情形。 為改善上述問題，本文以ISP業者管理智慧家庭中眾多的物聯網設備為情境，透過軟體定義網路 (Software Defined Network，SDN)進行頻寬排程配置，排程演算法以可兼顧公平性(fairness)、時間延遲(delay)及應用服務優先權(service priority)的A-MLWDF (Adaptive Modified Largest Weighted Delay First) [7]演算法，確保優先配置頻寬給智慧家庭中優先權較高、時效較為急迫的流量，以降低應用服務的延遲來提升智慧家庭網路之服務品質(Quality of Service，QoS)。 本研究透過OMNet++模擬器建構SDN環境與傳統環境中有眾多物聯網設備之智慧家庭。家中物聯網設備包含M2M (Machine to Machine)和非M2M(non Machine to Machine)裝置，以提供各種智慧家庭應用服務。我們透過SDN架構進行頻寬配置，達到集中式管控家中的頻寬資源，其中排程演算法包括PF、MLWDF、A-MLWDF。實驗結果顯示，以上排程演算法雖然於SDN環境下在公平性與抖動率表現並不顯著，公平性約改善1.6%及抖動率約降低1%左右，但在產能與延遲方面表現較為顯著，能有效提高產能約52%，及降低延遲約 52%。 / With the concept of IoT (Internet of Things) spread rapidly, it is the opportunity to promote smart homes in the expanding market. We can see that the future ISP (Internet Service Provider) has to face a large number of smart homes having bandwidth competition in a variety of different applications and causing application services unavailable due to network congestion.     In order to resolve the above problems, we propose that each ISP (Internet Service Provider) has to manage a large number of IoT devices in a smart home to performs bandwidth scheduling through Software Defined Network (SDN). We choose to use A-MLWDF scheduling algorithm (Adaptive Modified Largest Weighted Delay First) [7] which considers fairness, delay and service priority. A-MLWDF is able to ensure services of higher priority and emergent traffic be allocated bandwidth earlier and greatly reduce delay and thus effectively enhance Quality of Service (QoS) of smart homes.     In this research, we implement a SDN environment by using OMNet++ to simulate the bandwidth competition among smart homes with IoT devices. The IoT devices consists of M2M (Machine to Machine) and non-M2M (non Machine to Machine) devices which offer a variety of intelligent home application services. We configure the bandwidth allocation under SDN control. The scheduling algorithms include PF, MLWDF and A-MLWDF. When the network traffic is congested, SDN can significantly increase throughput and reduce latency compared to traditional network management. The experimental results show that above scheduling algorithms using SDN environment having no significant performance improvements in fairness and jitter. The fairness increases around 1.6% and the jitter reduces around 1%. However, it shows significant improvement on throughout and delay. The throughput increases around 52% and the delay reduces around 52%.