Submitted by Carmen Torres (carmensct@globo.com) on 2018-02-06T17:40:24Z No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Dissertacao_EstrategiasPlanejamentoOtimizacao.pdf: 6363892 bytes, checksum: 54af44d2043efdd661b641b9c67e1d29 (MD5) / Approved for entry into archive by Edisangela Bastos (edisangela@ufpa.br) on 2018-02-16T13:09:13Z (GMT) No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Dissertacao_EstrategiasPlanejamentoOtimizacao.pdf: 6363892 bytes, checksum: 54af44d2043efdd661b641b9c67e1d29 (MD5) / Made available in DSpace on 2018-02-16T13:09:13Z (GMT). No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Dissertacao_EstrategiasPlanejamentoOtimizacao.pdf: 6363892 bytes, checksum: 54af44d2043efdd661b641b9c67e1d29 (MD5) Previous issue date: 2017-08-04 / O consumo energético residencial vem crescendo de forma contínua ao longo das últimas décadas, em contrapartida, o fornecimento de energia elétrica não acompanha a mesma taxa de crescimento, tornando-se uma dificuldade a ser tratada pelas empresas do setor elétrico, aos consumidores e ao próprio meio ambiente. Os sistemas de distribuição existentes não são suficientes e possuem limitações no fornecimento de informação adequada, em tempo real, sobre o consumo e outras variáveis elétricas. Também não estão preparados para lidar com custos da energia variáveis, num contexto de um mercado que tende a estabelecer preços dinâmicos, que dependem de um conjunto de fatores endógenos e exógenos ao setor elétrico. Nesse contexto, este trabalho tem como objetivo a proposição, implementação e teste de um sistema de monitoramento inteligente, via smartphone, para controle de energia, utilizando-se formas inteligentes de tomada de decisão, com o intuito de fornecer ao usuário formas de manter seu consumo energético, a partir de perfis de consumo, dentro dos padrões de consumo pré-definidos e desejados pelo usuário. Como consequências positivas, ter-se-á a redução da demanda energética, por meio dos perfis de consumo que levam em consideração o grau de dependência do indivíduo em relação aos equipamentos elétricos presente na residência, apresentando um menor impacto no bem-estar e no dia a dia do usuário final do sistema. / Residential energy consumption has grown steadily over the last decades, becoming a problem for companies in the electricity sector, for consumers and for the environment. The traditional measurement systems are not sufficient and have limitations in providing adequate real-time information about consumption. As also, they are not prepared to deal with variable energy costs in the context of a market with dynamic prices that depend on the energy mix. The future of electric grid, called Smart Grid, will not only be designed with measurements based on the residences, but also on the individualized equipment consumption level. From the residential side, consumers generally suffer from a lack of information on the specific equipment energy consumption impact and, consequently, on the required behavior to reduce its consumption. In this context, this work aims on a smartphone monitoring system concept, to control energy using fuzzy logic, in order to provide to the user ways to maintain his energy consumption, through consumption profiles, within the user-defined consumption patterns. The energy reduction demand through the consumption profiles working with habitant dependence degree on the electrical equipment present in the residence, promote a smaller impact on inhabitant well-being and the daily life.

La communication Machine-to-Machine (M2M) est l'un des principaux fondements de l'Internet des Objets (IoT). C'est un phénomène qui a évolué discrètement au cours du temps et vient d’émerger à la surface pour do! nner naissance à une explosion de nouveaux usages et services. Capteurs, actionneurs, tags, véhicules et objets intelligents ont tous la possibilité de communiquer. Le nombre de connexions M2M est en constante augmentation et il est prévu de voir des milliards d’objets connectés dans un futur proche. Les applications M2M offrent des avantages dans divers domaines à savoir les villes intelligentes, les voitures connectées, les usines du futures, l’agriculture de précision, l’environnement, la santé, etc. La croissance rapide de cet écosystème est entrain de conduire le M2M vers un avenir prometteur. Cependant, les opportunités d'expansion des marchés M2M ne sont pas évidentes. En effet, un ensemble de challenges doivent être surmontés afin de permettre un déploiement à grande échelle dans des domaines diverses et variés à savoir les défis d’interopérabilité, de complexité et de scalabilité. Actuellement, le marché du M2M souffre d'une fragmentation verticale importante touchant la majorité des domaines industriels. En effet, diverses solutions propriétaires ont été conçues pour répondre à des applications spécifiques engendrant ainsi un sérieux problème d''interopérabilité. Pour adresser ce challenge, nous avons conçu, développer et expérimenté la plateforme OM2M offrant une architecture opérationnelle, flexible et extensible pour l'interopérabilité M2M conforme à la norme SmartM2M. Pour supporter les environnements contraints, nous avons proposé une nouvelle convention de nommage basée sur une structure de ressources non-hiérarchique permettant d’optimiser la taille des messages échangés. Pour assurer l’interopérabilité sémantique entre les applications et les machines, nous avons proposé l'ontologie IoT-O. Cette dernière est composée de cinq modèles de base représentant les capteurs, les actionneurs, les observations, les actuations et les web ! services pour permettre de converger rapidement vers un vocabulaire commun pour l'IoT. Une plateforme M2M horizontale permet d'interconnecter des machines hétérogènes largement distribués et qui évoluent fréquemment en fonction des changements de l’environnement. Maintenir ces systèmes complexes en vie est coûteux en termes de temps et d'argent. Pour adresser ce challenge, nous avons conçu, développé et intégré le framework FRAMESELF afin d'ajouter des capacités d'autogestion aux systèmes M2M basées sur le paradigme de l'informatique autonome. En étendant le modèle d'architecture de référence MAPE-K, notre solution permet d'adapter dynamiquement le comportement de la plateforme OM2M par en fonctions des changements du contexte et des politiques haut niveaux. Nous avons défini un ensemble de règles sémantiques pour faire du raisonnement sur l'ontologie IoT-O en tant que modèle de connaissance. Notre objectif est de permettre la découverte automatique entre les machines et les applications à travers un appariement sémantique et une reconfiguration dynam! ique de l'architecture des ressources. L’interopérabilité et l’autogestion ouvrent la voie à un déploiement de masse des systèmes M2M. Par contre, ces derniers se basent sur l'infrastructure actuelle d'internet qui n'a jamais été conçu pour ce genre de d'utilisation ce qui pose de nouvelles exigences en termes de scalabilité. Pour adresser ce challenge, nous avons conçu, simulé et validé l'approche OSCL proposant une nouvelle topologie de réseau maillé M2M comme alternative à l'approche centralisée actuelle. OSCL s'appuie sur les techniques de routage centrées sur l'information favorisant les communications à sauts multiples et un cache distribué pour une meilleure dissémination des données. Nous avons développé le simulateur OSCLsim pour valider l'approche proposée.[...] / Machine-to-Machine (M2M) is one of the main features of Internet of Things (IoT). It is a phenomenon that has been proceeding quietly in the background, and it is coming into the surface, where explosion of usage scenarios in businesses will happen. Sensors, actuators, tags, vehicles, and intelligent things all have the ability to communicate. The number of M2M connections is continuously increasing, and it has been predicted to see billions of machines interconnected in a near future. M2M applications provide advantages in various domains from smart cities, factories of the future, connected cars, home automation, e-health to precision agriculture. This fast-growing ecosystem is leading M2M towards a promising future. However, M2M market expansion opportunities are not straightforward. A set of challenges should be overcome to enable M2M mass-scale deployment across various industries including interoperability, complexity, and scalability issues. Currently, the M2M market is suffering from a high vertical fragmentation affecting the majority of business sectors. In fact, various vendor-specific M2M solutions have been designed independently for specific applications, which led to serious interoperability issues. To address this challenge, we designed, implemented, and experimented with the OM2M platform offering a flexible and extensible operational architecture for M2M interoperability compliant with the SmartM2M standard. To support constrained environments, we proposed an efficient naming convention relying on a non-hierarchical resource structure to reduce the payload size. To reduce the semantic gap between applications and machines, we proposed the IoT-O ontology for an effective semantic interoperability. IoT-O consists of five main parts, which are sensor, actuator, observation, actuation and service models and aims to quickly converge to a common IoT vocabulary. An interoperable M2M service platform enables one to interconnect heterogeneous devices that are widely distributed and frequently evolving according to their environment changes. Keeping M2M systems alive is costly in terms of time and money. To address this challenge, we designed, implemented, and integrated the FRAMESELF framework to retrofit self-management capabilities in M2M systems based on the autonomic computing paradigm. Extending the MAPE-K reference architecture model, FRAMESELF enables one to dynamically adapt the OM2M system behavior according to high level policies how the environment changes. We defined a set of semantic rules for reasoning about the IoT-O ontology as a knowledge model. Our goal is to enable automatic discovery of machines and applications through dynamic reconfiguration of resource architectures. Interoperability and self-management pave the way to mass-scale deployment of M2M devices. However, current M2M systems rely on current internet infrastructure, which was never designed to address such requirements, thus raising new requirements in term of scalability. To address this challenge, we designed, simulated and validated the OSCL overlay approach, a new M2M meshed network topology as an alternative to the current centralized approach. OSCL relies on the Named Data Networking (NDN) technique and supports multi-hop communication and distributed caching 5 to optimize networking and enhance data dissemination. We developed the OSCLsim simulator to validate the proposed approach. Finally, a theoretical model based on random graphs is formulated to describe the evolution and robustness of the proposed system.

近年來以物聯網為概念的相關應用已經成為最熱門的議題之一，各國家與企業皆致力於發展其技術以及相關應用。而物聯網的應用範圍十分廣泛，舉凡交通、醫療、電力、物流、家居等都是其應用的範圍。亞洲國家於近十年來也紛紛提出相關發展計畫，由此可看出各國對發展物聯網產品之野心與競爭。而台灣政府於2008年開始積極推展智慧家庭政策，端看目前成果，以技術層面而言並非無法達成，但在實際應用與推廣上明顯仍有許多不足之處。因此本研究欲探討使用者對於物聯網相關應用產品的使用動機為何，以智慧家庭為例，先進行相關文獻探討，並以修正式德菲法做為發展ANP專家問卷的基礎，再利用ANP法施行專家問卷，排序出影響消費者使用動機的各項權重，選擇出最符合消費者需求的產品組合，讓開發者能了解在開發與推展智慧家庭相關應用時，應滿足消費者哪些心理層面之動機因素，提升未來發展相關產品時的成功機率。 / In recent years, applications related to the concept of IoT become one of the most popular issues all over the world. Countries and enterprises devote themselves to developing the technique and application related to IoT. The range of its applications is very wide, including transportation, medical treatment, electricity, logistics, and home, etc. Asian countries set forth some development projects in the past decade, demonstrating the ambition and competition between countries in developing IoT products. Taiwan has started to push the development of smart home related applications since 2008. After development for some years, insufficiency in actual implementation and diffusion remains given our technological advantage. Therefore, this research intends to study the motivation for users to use IoT products taking smart home as an example. First, we study the related literature review and use modified Delphi method to develop the ANP expert questionnaires. Then, we prioritize the weights of consumer’s motives. The result can enable developers of smart home products to understand what kind of consumer motives they should satisfy when developing and promoting smart home applications. This enhances the probability of success for developing related products in the future.

Ultra low power wireless sensors and sensor systems are of increasing interest in a variety of applications ranging from structural health monitoring to industrial process control. Electrochemical batteries have thus far remained the primary energy sources for such systems despite the finite associated lifetimes imposed due to limitations associated with energy density. However, certain applications (such as implantable biomedical electronic devices and tire pressure sensors) require the operation of sensors and sensor systems over significant periods of time, where battery usage may be impractical and add cost due to the requirement for periodic re-charging and/or replacement. In order to address this challenge and extend the operational lifetime of wireless sensors, there has been an emerging research interest on harvesting ambient vibration energy. Vibration energy harvesting is a technology that generates electrical energy from ambient kinetic energy. Despite numerous research publications in this field over the past decade, low power density and variable ambient conditions remain as the key limitations of vibration energy harvesting. In terms of the piezoelectric transducers, the open-circuit voltage is usually low, which limits its power while extracted by a full-bridge rectifier. In terms of the interface circuits, most reported circuits are limited by the power efficiency, suitability to real-world vibration conditions and system volume due to large off-chip components required. The research reported in this thesis is focused on increasing power output of piezoelectric transducers and power extraction efficiency of interface circuits. There are five main chapters describing two new design topologies of piezoelectric transducers and three novel active interface circuits implemented with CMOS technology. In order to improve the power output of a piezoelectric transducer, a series connection configuration scheme is proposed, which splits the electrode of a harvester into multiple equal regions connected in series to inherently increase the open-circuit voltage generated by the harvester. This topology passively increases the rectified power while using a full-bridge rectifier. While most of piezoelectric transducers are designed with piezoelectric layers fully covered by electrodes, this thesis proposes a new electrode design topology, which maximizes the raw AC output power of a piezoelectric harvester by finding an optimal electrode coverage. In order to extract power from a piezoelectric harvester, three active interface circuits are proposed in this thesis. The first one improves the conventional SSHI (synchronized switch harvesting on inductor) by employing a startup circuitry to enable the system to start operating under much lower vibration excitation levels. The second one dynamically configures the connection of the two regions of a piezoelectric transducer to increase the operational range and output power under a variety of excitation levels. The third one is a novel SSH architecture which employs capacitors instead of inductors to perform synchronous voltage flip. This new architecture is named as SSHC (synchronized switch harvesting on capacitors) to distinguish from SSHI rectifiers and indicate its inductorless architecture.

With industry expectations of billions of Internet-connected things, commonly referred to as the IoT, we see a growing demand for high-performance on-chip bus architectures with the following attributes: small scale, low energy, high security, and highly configurable structures for integration, verification, and performance estimation. Our research thus mainly focuses on addressing these key problems and finding the balance among all these requirements that often work against each other. First of all, we proposed a low-cost and low-power System-on-Chips (SoCs) architecture (IBUS) that can frame data transfers differently. The IBUS protocol provides two novel transfer modes – the block and state modes, and is also backward compatible with the conventional linear mode. In order to evaluate the bus performance automatically and accurately, we also proposed an evaluation methodology based on the standard circuit design flow. Experimental results show that the IBUS based design uses the least hardware resource and reduces energy consumption to a half of an AMBA Advanced High-Performance Bus (AHB) and Advanced eXensible Interface (AXI). Additionally, the valid bandwidth of the IBUS based design is 2.3 and 1.6 times, respectively, compared with the AHB and AXI based implementations. As IoT advances, privacy and security issues become top tier concerns in addition to the high performance requirement of embedded chips. To leverage limited resources for tiny size chips and overhead cost for complex security mechanisms, we further proposed an advanced IBUS architecture to provide a structural support for the block-based AES algorithm. Our results show that the IBUS based AES-encrypted design costs less in terms of hardware resource and dynamic energy (60.2%), and achieves higher throughput (x1.6) compared with AXI. Effectively dealing with the automation in design and verification for mixed-signal integrated circuits is a critical problem, particularly when the bus architecture is new. Therefore, we further proposed a configurable and synthesizable IBUS design methodology. The flexible structure, together with bus wrappers, direct memory access (DMA), AES engine, memory controller, several mixed-signal verification intellectual properties (VIPs), and bus performance models (BPMs), forms the basic for integrated circuit design, allowing engineers to integrate application-specific modules and other peripherals to create complex SoCs.

Recent improvements in the area of Internet of Things (IoT) has led to extensive utilization of embedded devices and sensors. Hence, along with utilization the need for safety and security of these devices also increases proportionately. In the last two decades, the side-channel attack (SCA) has become a massive threat to the interrelated embedded devices. Moreover, extensive research has led to the development of many different forms of SCA for extracting the secret key by utilizing the various leakage information. Lately, machine learning (ML) based models have been more effective in breaking complex encryption systems than the other types of SCA models. However, these ML or DL models require a lot of data for training that cannot be collected while attacking a device in a real-world situation. Thus, in this thesis, we try to solve this issue by proposing the new technique of leakage conversion. In this technique, we try to convert the high signal to noise ratio (SNR) power traces to low SNR averaged electromagnetic traces. In addition to that, we also show how artificial neural networks (ANN) can learn various non-linear dependencies of features in leakage information, which cannot be done by adaptive digital signal processing (DSP) algorithms. Initially, we successfully convert traces in the time interval of 80 to 200 as the cryptographic operations occur in that time frame. Next, we show the successful conversion of traces lying in any time frame as well as having a random key and plain text values. Finally, to validate our leakage conversion technique and the generated traces we successfully implement correlation electromagnetic analysis (CEMA) with an approximate minimum traces to disclosure (MTD) of 480.

Récemment, l'intégration entre les environnements informatiques et de réseautage a été largement promu pour fournir des services intelligents à des utilisateurs finaux ainsi que l'utilisation efficace des ressources. Cette convergence a ouvert la voie à l'émergence de l'internet des objets (IdO). Le paradigme de l'IdO repose principalement sur la fabrication d'objets, appelés les choses, disparaître et se tissent dans le tissu de notre vie de tous les jours pour nous soutenir dans l'accomplissement des activités quotidiennes. L'évolutivité et l'hétérogénéité sont parmi les principaux défis qui entravent la réalisation à grande échelle de services de l'IdO dans la vie quotidienne des utilisateurs. Afin de relever les défis de l'IdO, un nouveau volet de recherche est venu en avant dans la littérature comme une classe paradigmatique des Cyber-physiques systèmes sociaux (CSPR), qui est connu comme l'Internet social des choses (Siot). Le SIOT se fonde sur la notion soulignée par phénomène petite-monde où la structure sociale permettant relation sociale fondée sur la confiance entre les personnes et les objets, d'une manière qui ressemble à des services de réseaux sociaux traditionnels (SNS) est suggérée de relever les défis de l'IdO. Cependant, depuis SIOT hérite des caractéristiques de différents informatiques et de réseautage environnements (par exemple, l'IdO et SNS) cela, en fait, augmente la quantité et la variété des données contextuelles qui doit être manipulé pour Adaptive fourniture de services dans Siot, qui agit comme le principal défi adressé dans cette thèse. Autrement dit, dans cette thèse, nous proposons la notion de contexte cognitif lorsque, dans certaine situation spatio-temporelle, le raisonnement sur les aspects objectifs du cadre, ce qui représente l'environnement physique, avec le contexte subjective, qui représente les aspects comportementaux et sociaux, est considéré comme l'amélioration des services SIOT intelligence et la capacité d'adaptation aux besoins conjoncturels des utilisateurs. Nous envisageons technologies du Web sémantique pour déployer notre contexte cognitif proposé dans deux domaines d'application; sensible au contexte recommandation des tâches quotidiennes dans les maisons intelligentes et structure sociale dépendant de la situation des choses. Un prototype de preuve de concept a été développé pour chaque domaine d'application, dans le but de démontrer l'intégration harmonieuse des objets sur le Web pour la réalisation de certaines applications. Nos résultats empiriques montrent un niveau de service amélioré l'adaptabilité et la complexité en temps de fonctionner lors de l'application de notre contexte cognitif suggéré / The paradigm of the Social Internet of Things (SIoT) is being promoted in the literature to boost a new trend wherein the benefits of social network services are exhibited within the network of connected objects i.e., the Internet of Things (IoT). The novel user-friendly interaction framework of the SIoT opens the doors for enhancing the intelligence required to stimulate a shift in the IoT from a heterogeneous network of independently connected objects towards a manageable network of everything. In practice, achieving scalability within the large-scale and the heterogeneous paradigm of the IoT while maintaining on top of its user-friendly and intuitive services to bridge human-to-machine perceptions and encourage the technology’s adaptation is a major challenge which is hindering the realization and deployment of the IoT technologies and applications into people’s daily live. For the goal of handling IoT challenges, as well as improve the level of smart services adaptability to users’ situational needs, in this thesis, novel SIoT-based application architecture is provided. That is, Semantic Web Technologies are envisaged as a means to develop automated, value-added services for SIoT. While, interoperability and automation are essential requirement to seamlessly integrate such services into user life, Ontologies are used to semantically describe Web services with the aim of enabling the automatic invocation and composition of these services as well as support interactions across the cyber, physical and social worlds. On the other hand, handling the variety of contextual data in SIoT for intelligent decision making is another big challenge which is still in very early stages of research. In this thesis we propose a cognitive reasoning approach taking into consideration achieving situational-awareness (SA) in SIoT. This reasoning approach is deployed within two application domains where results show an improved level of services adaptability compared to location-aware services which are previously proposed in the literature

As technology is growing at a fast pace, IoT-based smart home services are increasingly adopted by people. IoT-based smart homes offer numerous unimaginable benefits, including efficiency, safety, effectiveness, scalability of services, devices, and data, among many others. However, there is another side to this technology: security threats. As IoT-based technology is distributed in nature, implementing security measures and policies to protect the infrastructure becomes very difficult. The infrastructure faces threats such as information theft, eavesdropping, distortion, and more. Ensuring the security of smart home IoT devices is a critical concern, and user behavior plays a major role in achieving it. Furthermore, Theory of Planned Behavior (TPB) was utilized throughout the study. This study employed a qualitative research methodology and content analysis technique to investigate the impact of user behavior on the security of smart home IoT devices. The findings revealed several themes, such as the significance of comprehending and resolving security issues, the implementation of security measures, and the impact of user education and awareness. The study offered fresh perspectives on IoT device security and will aid in developing security best practices / I takt med att tekniken växer i snabb takt, anammas IoT-baserade smarta hemtjänster alltmer av människor. IoT-baserade smarta hem erbjuder många ofattbara fördelar, inklusive effektivitet, säkerhet, effektivitet, skalbarhet för tjänster, enheter och data, bland många andra. Däremot är en annan sida av denna teknik: säkerhetshot. Som IoT-baserad teknik distribueras i natur, att implementera säkerhetsåtgärder och policyer för att skydda infrastrukturen blir mycketsvår. Infrastrukturen står inför hot som informationsstöld, avlyssning, förvrängning och Mer. Att säkerställa säkerheten för smarta hem IoT-enheter är en kritisk fråga, och användarnas beteende spelar en stor roll för att uppnå det. Dessutom användes Theory of Planned Behavior (TPB).under hela studien. Denna studie använde en kvalitativ forskningsmetodik och innehållanalysteknik för att undersöka hur användarbeteendet påverkar säkerheten för IoT för smarta hemenheter. Fynden avslöjade flera teman, såsom betydelsen av att förstå och lösa säkerhetsfrågor, implementering av säkerhetsåtgärder och användarens inverkanutbildning och medvetenhet. Studien erbjöd nya perspektiv på IoT-enhetssäkerhet och kommer att hjälpa att utveckla bästa praxis för säkerhet / نظرًا لأن التكنولوجيا تنمو بوتيرة سريعة ، يتم اعتماد خدمات المنزل الذكي القائمة على إنترنت الأشياء بشكل متزايد من قبل الناس. توفر المنازل الذكية القائمة على إنترنت الأشياء العديد من المزايا التي لا يمكن تصورها ، بما في ذلك الكفاءة والأمان والفعالية وقابلية التوسع في الخدمات والأجهزة والبيانات ، من بين أشياء أخرى كثيرة. ومع ذلك ، هناك جانب آخر لهذه التكنولوجيا: التهديدات الأمنية. نظرًا لتوزيع التكنولوجيا القائمة على إنترنت الأشياء بطبيعتها ، يصبح تنفيذ التدابير والسياسات الأمنية لحماية البنية التحتية أمرًا صعبًا للغاية. تواجه البنية التحتية تهديدات مثل سرقة المعلومات والتنصت والتشويه والمزيد. يعد ضمان أمان أجهزة إنترنت الأشياء المنزلية الذكية مصدر قلق بالغ ، ويلعب سلوك المستخدم دورًا رئيسيًا في تحقيق ذلك. علاوة على ذلك ، تم استخدام نظرية السلوك المخطط (TPB) طوال الدراسة. استخدمت هذه الدراسة منهجية البحث النوعي وتقنية تحليل المحتوى للتحقيق في تأثير سلوك المستخدم على أمن أجهزة إنترنت الأشياء المنزلية الذكية. كشفت النتائج عن عدة محاور ، مثل أهمية فهم وحل المشكلات الأمنية ، وتنفيذ التدابير الأمنية ، وتأثير تثقيف المستخدمين وتوعيتهم. قدمت الدراسة وجهات نظر جديدة حول أمن أجهزة إنترنت الأشياء وستساعد في تطوير أفضل الممارسات الأمنية

The use of Internet of Things systems has increased to meet the need for smart systems in various fields, such as smart homes, intelligent industries, medical systems, agriculture, and the military. IoT networks are expanding daily to include hundreds and thousands of IoT devices, which transmit information through other linked devices to reach the network sink or gateway. The information follows different routes to the network sink. Finding an ideal routing solution is a big challenge due to several factors, such as power, computation, storage, and memory limitation for IoT devices. In 2011, A new standardized routing protocol for low-power and lossy networks was released by the Internet Engineering task force (IETF). The IETF adopted a distance vector routing algorithm for the RPL protocol. RPL protocol utilizes the objective functions (OFs) to select the path depending on diffident metrics.These OFs with different metrics must be evaluated and tested to develop the best routing solution.This project aims to test the performance of standardized RPL objective functions in a simulation environment. Afterwards, a new objective function with a new metric will be implemented and tested in the same environmental conditions. The performance results of the standard objective functions and the newly implemented objective function will be analyzed and compared to evaluate whether the standard objective functions or the new objective function is better as a routing solution for the IoT devices network.

The oil and gas industry faces a lack of compact drilling devices capable of performing horizontal drilling maneuvers in depleted or abandoned wells in order to enhance oil recovery. The purpose of this project was to design and develop a smart sensing system that can be later implemented in compact drilling devices used to perform horizontal drilling to enhance oil recovery in wells. A smart sensor is the combination of a sensing element (sensor) and a microprocessor. Hence, a smart sensing system is an arrangement that consists of different sensors, where one or more have smart capabilities. The sensing system was built and tested in a laboratory setting. For this, a test bench was used as a case study to simulate the operation from a micro-drilling device. The smart sensing system integrated the sensors essential for the direct operational measurements required for the robot. The focus was on selecting reliable and sturdy components that can handle the operation Down the Hole (DTH) on the final lateral micro-drilling robot. The sensing system's recorded data was sent to a microcontroller, where it was processed and then presented visually to the operator through a User Interface (UI) developed in a cloud-based framework. The information was filtered, processed, and sent to a controller that executed commands and sent signals to the test bench’s actuators. The smart sensing system included novel modules and sensors suitable for the operation in a harsh environment such as the one faced in the drilling process. Furthermore, it was designed as an independent, flexible module that can be implemented in test benches with different settings and early robotic prototypes. The outcome of this project was a sensing system able to provide robotic drilling devices with flexibility while providing accurate and reliable measurements during their operation.