Context. Internet of Things (IoT) is an extension of the Internet, which now includes physical objects of the real world. The main purpose of Internet of Things is to increase a quality of people’s daily life. A smart home is one of the promising areas in the Internet of Things which increases rapidly. It allows users to control their home devices anytime from any location in the world using Internet connectivity and automate their work based on the physical environment conditions and user preferences. The main issues in deploying the architecture of IoT are the security of the communication between constrained low-power devices in the home network and device performance. Battery lifetime is a key QoS parameter of a battery-powered IoT device which limits the level of security and affects the performance of the communication. These issues have been deepened with the spread of cheap and easy to use microcontrollers which are used by electronic enthusiasts to build their own home automation projects. Objectives. In this study, we investigated wireless communication technologies used in low-power and low-bandwidth home area networks to determine which of them are most suitable for smart home applications. We also investigated the correlation between security, power consumption of constrained IoT device, and performance of wireless communication based on a model of a home automation system with a sensor node. Sensor node was implemented using Arduino Nano microcontroller and RF 433 MHz wireless communication module. Methods. To achieve the stated objectives of this research following methods were chosen: literature review to define common applications and communication technologies used in a smart home scenario and their requirements, comparison of wireless communication technologies in smart home, study of Arduino microcontroller technology, design and simulation of a part of  home automation project based on Arduino, experimental measurements  of execution time and power consumption of Arduino microcontroller with RF 433 MHz wireless module when transmitting data with different levels of security, and analysis of experimental results. Results. In this research, we presented a detailed comparison of ZigBee, WiFi, Bluetooth, Z-Wave, and ANT communication technologies used in a smart home in terms of the main characteristics. Furthermore, we considered performance, power consumption, and security. A model of a home automation system with a sensor node based on Arduino Nano was described with sleep management and performance evaluation. The results show that the battery lifetime of Arduino in a battery-powered sensor node scenario is determined by the communication speed, sleep management, and affected by encryption. Conclusions. The advanced communication strategy can be used to minimize the power consumption of the device and increase the efficiency of the communication. In that case, our security measures will reduce the productivity and lifetime of the sensor node not significantly. It’s also possible to use symmetric encryption with smaller block size.

Tato diplomová práce se zabývá systémem automatizace domácnosti umožňujícím ovládání domácích spotřebičů prostřednictvím běžné televize. Systém využívá standardu X10 a bezdrátové technologie ZigBee. Řídicí software staví na OS GNU/Linux a systému domácího kina MythTV. V rámci této diplomové práce byla vyvinuta aplikace zprostředkující komunikaci mezi MythTV a hardwarem. Modulární koncept postavený na dynamicky zaváděných modulech dělá tuto aplikaci snadno rozšiřitelnou a použitelnou i mimo předkládaný automatizační systém. Za účelem testování a demonstrace funkčnosti byl dále navržen bezdrátový teploměr a převodník VGA na SCART.

This project revolves around creating a home automation system prototype with the main focus being the ability to lock/unlock a door through the internet. The system consists of a central device, a server and an Android application.The central device is a microprocessor, in this case, a Raspberry Pi that connects to the Internet and receives an order to control a motor which in turn turns the lock with the help of gears. The ability to rotate the motor in both directions is achieved by the use of an H-bridge. The server manages users and devices, and handles the communication between the application and the central device. Users and devices are stored in a database on the server. The application is a frontend which presents the user with a list of devices to interact with.The main prototype where the Raspberry Pi acted as a central device was abandoned due to time and resource constraints. It was instead used to control the motor directly. This brought up some problems concerning powering the device using batteries. The software of the prototype is mostly working but due to the same time limitations not all planned features could be implemented.

Les environnements domotiques sont des environnements ubiquitaires dans lesquels des équipements domestiques, disséminés dans une habitation, fournissent des services utilisables à distance au travers d'un réseau. Des systèmes domotiques sont proposés pour permettre aux utilisateurs de contrôler les équipements en fonction de leurs besoins.Idéalement, ces systèmes orchestrent l'exécution des services fournis par les équipements pour réaliser des services complexes. Mieux encore, ces systèmes doivent s'adapter à la variété des environnements en termes d'équipements et des besoins des utilisateurs. Ils doivent également pouvoir s'adapter dynamiquement, si possible de manière autonome, au changement de leur contexte d'exécution (apparition ou disparition d'un équipement, évolution des besoins).Dans cette thèse, nous apportons une réponse à cette problématique avec SAASHA, un système domotique multi-agents à base de composants. La combinaison de ses deux paradigmes permet de gérer l'adaptation à trois niveaux : présentation (interfaces utilisateur),organisation (architecture du système) et comportement (architecture interne des agents).Les agents perçoivent le contexte et ses changements. Les utilisateurs se voient proposer une vue dynamique du contexte leur permettant de définir des scénarios personnalisés sous forme de règles. Les agents se répartissent les rôles pour réaliser les scénarios. Ils modifient dynamiquement leur architecture interne grâce à la génération, au déploiement et à l'assemblage de composants pour se doter de nouveaux comportements de contrôle des équipements et des scénarios. Les agents collaborent ainsi pour exécuter les scénarios. En cas de changement, ces trois niveaux d'adaptation sont mis en oeuvre de manière dynamique et autonome pour maintenir la continuité de service. Un prototype de SAASHA, basé sur les standards industriels UPnP et OSGi, a été développé pour évaluer la faisabilité de notre proposition. / Home automation environments are ubiquitous environments where domestic devices, scattered throughout a home, provide services that can be used remotely over a network. Home automation systems are proposed to enable the users of controlling the devices according to their needs. Ideally, these systems orchestrate the execution of the services provided by the devices to achieve complex services. Even more, these systems must adapt to the variety of environments in terms of devices and users needs. They must also be able to adapt dynamically, if possible in an autonomous manner, to the changes of their execution context (appearance or disappearance of a device, changing needs).In this thesis, we provide an answer to this problematic with SAASHA, a multi-agent home automation system based on components. The combination of these two paradigms enables managing the adaptation on three levels: presentation (user interface), organization (system architecture) and behavior (internal architecture of agents). The agents perceive their context and its changes. The Users are offered a dynamic view of the context allowing them to define custom scenarios as rules. The agents divide the roles among them to realize the scenarios. They modify dynamically their internal architecture throughout the generation, deployment and assembly of components to adopt new device control behaviors and scenarios. The agents collaborate to execute the scenarios. In case of a change, these three levels of adaptation are updated dynamically and autonomously to maintain the service continuity. A SAASHA prototype, based on UPnP and OSGi industry standards, has been developed to assess the feasibility of our proposal.

Nos últimos anos, um dos principais desafios globais está relacionado com a eficiência energética, sendo o desperdício de energia um dos fatores a ser destacado. Tal desperdício pode ser superado com o uso do Sistema de Automação Residencial (SAR). Vale frisar que os SARs são fortemente dependentes da sua infraestrutura interna, visto que esta é a base de uma casa inteligente. A Rede de Sensores e Atuadores sem Fio (RSASF) é uma solução promissora e de fácil implantação para ser utilizada como infraestrutura em um SAR. Entretanto, o uso das RSASFs como infraestrutura para monitorar e atuar (isto é, processo de tomada de decisão) no contexto de um SAR traz um novo problema. Tal problema remete não apenas a falta de um método para realizar a decisão dentro do próprio nó da RSASF, mas também a ausência em investigar um trade-off entre a precisão nas tomadas de decisões e o consumo de energia dos nós da rede. Além disso, a falta de uma infraestrutura distribuída, com baixo overhead e que reduza a latência do serviço são algumas das novas problemáticas para serem exploradas. Com isso, tem-se como desafio embarcar uma maior inteligência em dispositivos com recursos escassos, característica presente em uma RSASF. Para superar tais limitações, esta tese apresenta duas soluções de decisões inteligentes para uma infraestrutura residencial, nomeadas como ResiDI e ImPeRIum. O ResiDI é baseado em uma rede neural para atuar no processo de tomada de decisão dentro da RSASF, bem como em um mecanismo de correlação temporal para maximizar a eficiência energética da infraestrutura de comunicação. Já o ImPeRIum é baseado em um conjunto heterogêneo de dispositivos inteligentes para formar um ambiente computacional de fog, o qual gerencia as aplicações da residência por meio de uma rede neural. As soluções foram avaliadas extensivamente em diferentes cenários e comparadas com um trabalho da literatura. Os resultados reais e simulados, avaliados mediante uma análise estatística paramétrica e não-paramétrica, mostrou atingir o objetivo desta tese, sendo quatro deles notáveis: (i) aumento da precisão nas tomadas de decisões; (ii) redução no consumo de energia dos nós da rede; (iii) redução no tempo de resposta da atuação com baixa sobrecarrega; e (iv) eficiência na disseminação das informações. / In recent years, energy efficiency has become a major global challenge, and energy waste is a factor that needs to be highlighted. Such waste can be overcome with the use of Home Automation System (HAS). It should be stressed that the HASs are strongly dependent on its internal network, since this is the basis of a smart home. Wireless Sensor and Actuator Networks (WSANs) provide a modern and ubiquitous infrastructure for a smart home. However, the use of WSANs to monitor and act (i.e. decision-making process) as a control infrastructure within the context of HAS poses a new problem. Such problem refers not only to the lack of a method to execute the decision-making process within the WSAN, but also to the lack of investigating a trade-off between the decision-making accuracy and the extension of the WSAN nodes life-time. In addition, the lack of a distributed infrastructure, with low overhead in processing and that reduces service latency are some of the new problems to be addressed in the literature. With this, one has as a challenge to embark on greater intelligence in devices with scarce resources, a feature present in a WSAN. To overcome such limitations, this thesis presents two intelligent decision-making solutions for residential infrastructures, named ResiDI and ImPeRIum. ResiDI was developed based on a neural network to act in the decision-making process within the network, as well as a temporal correlation mechanism to maximize the energy consumption in the networks nodes. ImPeRIum was based on a heterogeneous set of smart objects to form a fog computational environment, which manages the applications of the residence through a neural network. The solutions were evaluated extensively in different scenarios and compared with an approach in the literature. The real and simulated results, evaluated through parametric and non-parametric tests, show that solutions make four key contributions: (i) increased decisionmaking; (ii) reduction in node energy consumption; (iii) reduction in action response time with low overload; and (iv) efficiency in the transmission of information.

Nos últimos anos, um dos principais desafios globais está relacionado com a eficiência energética, sendo o desperdício de energia um dos fatores a ser destacado. Tal desperdício pode ser superado com o uso do Sistema de Automação Residencial (SAR). Vale frisar que os SARs são fortemente dependentes da sua infraestrutura interna, visto que esta é a base de uma casa inteligente. A Rede de Sensores e Atuadores sem Fio (RSASF) é uma solução promissora e de fácil implantação para ser utilizada como infraestrutura em um SAR. Entretanto, o uso das RSASFs como infraestrutura para monitorar e atuar (isto é, processo de tomada de decisão) no contexto de um SAR traz um novo problema. Tal problema remete não apenas a falta de um método para realizar a decisão dentro do próprio nó da RSASF, mas também a ausência em investigar um trade-off entre a precisão nas tomadas de decisões e o consumo de energia dos nós da rede. Além disso, a falta de uma infraestrutura distribuída, com baixo overhead e que reduza a latência do serviço são algumas das novas problemáticas para serem exploradas. Com isso, tem-se como desafio embarcar uma maior inteligência em dispositivos com recursos escassos, característica presente em uma RSASF. Para superar tais limitações, esta tese apresenta duas soluções de decisões inteligentes para uma infraestrutura residencial, nomeadas como ResiDI e ImPeRIum. O ResiDI é baseado em uma rede neural para atuar no processo de tomada de decisão dentro da RSASF, bem como em um mecanismo de correlação temporal para maximizar a eficiência energética da infraestrutura de comunicação. Já o ImPeRIum é baseado em um conjunto heterogêneo de dispositivos inteligentes para formar um ambiente computacional de fog, o qual gerencia as aplicações da residência por meio de uma rede neural. As soluções foram avaliadas extensivamente em diferentes cenários e comparadas com um trabalho da literatura. Os resultados reais e simulados, avaliados mediante uma análise estatística paramétrica e não-paramétrica, mostrou atingir o objetivo desta tese, sendo quatro deles notáveis: (i) aumento da precisão nas tomadas de decisões; (ii) redução no consumo de energia dos nós da rede; (iii) redução no tempo de resposta da atuação com baixa sobrecarrega; e (iv) eficiência na disseminação das informações. / In recent years, energy efficiency has become a major global challenge, and energy waste is a factor that needs to be highlighted. Such waste can be overcome with the use of Home Automation System (HAS). It should be stressed that the HASs are strongly dependent on its internal network, since this is the basis of a smart home. Wireless Sensor and Actuator Networks (WSANs) provide a modern and ubiquitous infrastructure for a smart home. However, the use of WSANs to monitor and act (i.e. decision-making process) as a control infrastructure within the context of HAS poses a new problem. Such problem refers not only to the lack of a method to execute the decision-making process within the WSAN, but also to the lack of investigating a trade-off between the decision-making accuracy and the extension of the WSAN nodes life-time. In addition, the lack of a distributed infrastructure, with low overhead in processing and that reduces service latency are some of the new problems to be addressed in the literature. With this, one has as a challenge to embark on greater intelligence in devices with scarce resources, a feature present in a WSAN. To overcome such limitations, this thesis presents two intelligent decision-making solutions for residential infrastructures, named ResiDI and ImPeRIum. ResiDI was developed based on a neural network to act in the decision-making process within the network, as well as a temporal correlation mechanism to maximize the energy consumption in the networks nodes. ImPeRIum was based on a heterogeneous set of smart objects to form a fog computational environment, which manages the applications of the residence through a neural network. The solutions were evaluated extensively in different scenarios and compared with an approach in the literature. The real and simulated results, evaluated through parametric and non-parametric tests, show that solutions make four key contributions: (i) increased decisionmaking; (ii) reduction in node energy consumption; (iii) reduction in action response time with low overload; and (iv) efficiency in the transmission of information.

I detta examensarbete har tidsstämplar extraherats ur ett forensiskt perspektiv från ett hemautomationssystem med styrenheten Homey från Athom. Först konstruerades ett fiktivt händelsescenario gällande ett inbrott i en lägenhet med ett hemautomationssystem. Hemautomationssystemet bestod av flera perifera enheter som använde olika trådlösa nätverksprotokoll. Enheterna triggades under händelsescenariot. Därefter testades olika metoder för att få ut data i form av tidsstämplar. De metoder som testades var rest-API, UART och chip-off på flashminnet medan JTAG inte hanns med på grund av tidsbrist. Den metod som gav bäst resultat var rest-API:t som möjliggjorde extrahering av alla tidsstämplar samt information om alla enheter. I flashminnet hittades alla tidsstämplar, men det var inte möjligt att koppla ihop dessa tidsstämplar med en specifik enhet utan att använda information från rest-API:t. Trots att rest-API:t gav bäst resultat så var det den metod som krävde en mängd förutsättningar i form av bland annat inloggningsuppgifter eller en rootad mobil. Med hjälp av de extraherade tidsstämplarna rekonstruerades sedan händelsescenariot för inbrottet. / The purpose of this bachelor thesis was to extract timestamps from a home automation system with a control unit named Homey in a forensic perspective. The first step was to create a course of event regarding a burglar breaking into an apartment with home automation. The home automation system consisted of some peripheral units using different types of wireless network protocols. All these units were triggered during the break in. Thereafter different types of methods were tested in an attempt to extract the timestamps for each unit. These methods included rest-API, UART and chip-off on a flash memory. The method using JTAG were not tested due to lack of time. Rest-API was the method that provided most information about the units and time stamps. The flash memory also contained every timestamp, however it did not provide any information about which timestamp belonged to which unit. Even though the rest-API was the best method to extract data, it was also the method with most requirements such as credentials or a rooted smartphone. With the extracted timestamps it was possible to reconstruct the course of events of the break-in.