Sviluppo di un’app mobile con Realtà Aumentata e Machine Learning in contesto di biodiversità

Il volume di tesi ha riguardato lo sviluppo di un'applicazione mobile che sfrutta la Realtà Aumentata e il Machine Learning nel contesto della biodiversità. Nello specifico si è realizzato un modello di AI che permetta la classificazione di immagini di fiori. Tale modello è stato poi integrato in Android, al fine della realizzazione di un'app che riesca a riconoscere specifiche specie di fiori, oltre a individuare gli insetti impollinatori attratti da essi e rappresentarli in Realtà Aumentata.

Design of flywheel generator for a diesel hybrid working machine

The aim of this work is to design a flywheel generator for a diesel hybrid working machine. In this work we perform detailed design of a generator. Mobile machines are commonly used in industry: road building machines, three harvesting machines, boring machines, trucks and other equipment. These machines work with a hydraulic drive system. This system provides good service property and high technical level. Manufacturers of mobile machines tend to satisfy all requirements of customers and modernized drive system. In this work also a description of the frequency inverter is present. Power electronics system is one of the basic parts for structures perform in the project.

Virtual technology and haptic interface solutions for design and control of mobile working machines

Commercially available haptic interfaces are usable for many purposes. However, as generic devices they are not the most suitable for the control of heavy duty mobile working machines like mining machines, container handling equipment and excavators. Alternative mechanical constructions for a haptic controller are presented and analysed. A virtual reality environment (VRE) was built to test the proposed haptic controller mechanisms. Verification of an electric motor emulating a hydraulic pump in the electro-hydraulic system of a mobile working machine is carried out. A real-time simulator using multi-body-dynamics based software with hardware-in-loop (HIL) setup was used for the tests. Recommendations for further development of a haptic controller and emulator electric motor are given.

Liikealustan suunnittelu liikkuvan työkoneen simulaattoriin

Työssä suunniteltiin liikealusta liikkuvan työkoneen koulutussimulaattoriin. Suunnittelu aloitettiin mittaamalla lastauskoneen dynaamisia ominaisuuksia. Mittausdatan ja koneen toiminnan analysoinnin perusteella valittiin liikealustan perusrakenne. Toimilaitteiden mitoitus tapahtui simulointimallin avulla, jossa käytettiin mitattuja kiihtyvyyksiä, signaalin suodatusta, käänteiskinematiikkaa ja käänteisdynamiikkaa. Simulointimallia käytettiin myös mekaanisen rakenteen mitoituksessa. Lisäksi visualisoinnin ja ohjauksen toteutusta tutkittiin. Työn tavoitteena oli kehittää mahdollisimman realistisen liiketuntuman toteuttava ja kustannustehokas liikealusta. Lisäksi pyrittiin matalaan ja helposti siirrettävissä olevaan rakenteeseen. Liikealustan liikkeet pyrittiin toteuttamaan sähkökäytöillä. Suunnittelun tuloksena saatiin kolmen vapausasteen liikealusta, joka on toteutettu servomoottoreilla. Työssä suunnitellusta liikealustasta on tarkoitus rakentaa fyysinen prototyyppi ja liittää se lastauskoneen reaaliaikasimulaattoriin.

Tulevaisuuden työkonepuomin globaali optimointi -esiselvitys

Monitavoiteoptimointia käytetään laajasti auto- ja lentokoneteollisuudessa suunnittelun apu-välineenä, mutta muuten sen käyttö ei ole vielä yleistynyt laajemmin. Tässä työssä on tarkoi-tus tehdä laaja esiselvitys monitavoiteoptimoinnista ja sen hyödyntämisestä työkonepuomien suunnittelun apuvälineenä. Työ tehtiin yhteistyössä Lappeenrannan teknillisen yliopiston ja projektiin osallistuvien FIMA ry:n jäsenten kanssa. Tulosten ja johtopäätösten perusteella tutkimusta tullaan mahdollisesti jatkamaan Tampereen teknillisen yliopiston tohtorikoulussa. Työssä selvitettiin mitä monitavoiteoptimoinnilla tarkoitetaan ja esitellään sen etenemisvai-heet. Lisäksi työssä esitellään lyhyesti kuusi monitavoiteoptimointiohjelmistoa pääominai-suuksineen sekä selvitetään ohjelmistolisenssien hintoja. Työssä optimointiin perehdyttiin teleskooppipuomin jatkoksen case -tutkimuksen avulla. Ni-velpuomit ja nivel- ja teleskooppipuomien yhdistelmät rajattiin työn ulkopuolelle. Työssä muodostettiin teleskooppipuomin jatkoksen poikkileikkauksen optimointityökalu. Sen avulla voidaan laskea luotettavasti optimit mitat painon suhteen niin, että lommahdusrajoitteet, tai-vutusvastus sekä taipuma otetaan huomioon ja samalla voitiin arvioida optimointiprosessin etuja ja haittoja. Optimoinnin tuloksia voidaan käyttää edelleen monitavoiteoptimoinnin lähtö-arvoina. Optimointi tehtiin Matlabin avulla ja tulokset verifioitiin AGIFAP -elementtimenetelmäohjelmistolla. Optimoituja tuloksia tutkittiin edelleen Femap -elementtimenetelmäohjelmistolla, jolla haettiin vuorovaikutussuhteita monitavoiteoptimoinnin tueksi. FE -analyysien avulla muodostettiin kaksi apuohjelmaa optimoinnin tueksi. Työssä havaittiin, että teleskooppipuomin jatkoksen optimointi vaatii FE -analyysiohjelmiston rinnalleen, jotta voidaan varmistua rakenteen kestävyydestä ja optimoida väsymiskestävyyt-tä. Liukupalojen vaikutus teleskooppipuomin käytökseen sekä väsymiskestävyyden optimoin-ti vaatii jatkotutkimusta.

Evaluation of Machine Learning Classifiers for Mobile Network Intrusion Detection Systems

Mobile malwares are increasing with the growing number of Mobile users. Mobile malwares can perform several operations which lead to cybersecurity threats such as, stealing financial or personal information, installing malicious applications, sending premium SMS, creating backdoors, keylogging and crypto-ransomware attacks. Knowing the fact that there are many illegitimate Applications available on the App stores, most of the mobile users remain careless about the security of their Mobile devices and become the potential victim of these threats. Previous studies have shown that not every antivirus is capable of detecting all the threats; due to the fact that Mobile malwares use advance techniques to avoid detection. A Network-based IDS at the operator side will bring an extra layer of security to the subscribers and can detect many advanced threats by analyzing their traffic patterns. Machine Learning(ML) will provide the ability to these systems to detect unknown threats for which signatures are not yet known. This research is focused on the evaluation of Machine Learning classifiers in Network-based Intrusion detection systems for Mobile Networks. In this study, different techniques of Network-based intrusion detection with their advantages, disadvantages and state of the art in Hybrid solutions are discussed. Finally, a ML based NIDS is proposed which will work as a subsystem, to Network-based IDS deployed by Mobile Operators, that can help in detecting unknown threats and reducing false positives. In this research, several ML classifiers were implemented and evaluated. This study is focused on Android-based malwares, as Android is the most popular OS among users, hence most targeted by cyber criminals. Supervised ML algorithms based classifiers were built using the dataset which contained the labeled instances of relevant features. These features were extracted from the traffic generated by samples of several malware families and benign applications. These classifiers were able to detect malicious traffic patterns with the TPR upto 99.6% during Cross-validation test. Also, several experiments were conducted to detect unknown malware traffic and to detect false positives. These classifiers were able to detect unknown threats with the Accuracy of 97.5%. These classifiers could be integrated with current NIDS', which use signatures, statistical or knowledge-based techniques to detect malicious traffic. Technique to integrate the output from ML classifier with traditional NIDS is discussed and proposed for future work.

Design and implementation of machine vision system for the mobile assembly robot

The review of intelligent machines shows that the demand for new ways of helping people in perception of the real world is becoming higher and higher every year. This thesis provides information about design and implementation of machine vision for mobile assembly robot. The work has been done as a part of LUT project in Laboratory of Intelligent Machines. The aim of this work is to create a working vision system. The qualitative and quantitative research were done to complete this task. In the first part, the author presents the theoretical background of such things as digital camera work principles, wireless transmission basics, creation of live stream, methods used for pattern recognition. Formulas, dependencies and previous research related to the topic are shown. In the second part, the equipment used for the project is described. There is information about the brands, models, capabilities and also requirements needed for implementation. Although, the author gives a description of LabVIEW software, its add-ons and OpenCV which are used in the project. Furthermore, one can find results in further section of considered thesis. They mainly represented by screenshots from cameras, working station and photos of the system. The key result of this thesis is vision system created for the needs of mobile assembly robot. Therefore, it is possible to see graphically what was done on examples. Future research in this field includes optimization of the pattern recognition algorithm. This will give less response time for recognizing objects. Presented by author system can be used also for further activities which include artificial intelligence usage.

Development of a support vector machine-based navigation system for driving a mobile robot through paths in plantations

The use of mobile robots turns out to be interesting in activities where the action of human specialist is difficult or dangerous. Mobile robots are often used for the exploration in areas of difficult access, such as rescue operations and space missions, to avoid human experts exposition to risky situations. Mobile robots are also used in agriculture for planting tasks as well as for keeping the application of pesticides within minimal amounts to mitigate environmental pollution. In this paper we present the development of a system to control the navigation of an autonomous mobile robot through tracks in plantations. Track images are used to control robot direction by preprocessing them to extract image features. Such features are then submitted to a support vector machine in order to find out the most appropriate route. The overall goal of the project to which this work is connected is to develop a real time robot control system to be embedded into a hardware platform. In this paper we report the software implementation of a support vector machine, which so far presented around 93% accuracy in predicting the appropriate route. © 2012 IEEE.

Machine learning techniques for implicit interaction using mobile sensors

Interactions in mobile devices normally happen in an explicit manner, which means that they are initiated by the users. Yet, users are typically unaware that they also interact implicitly with their devices. For instance, our hand pose changes naturally when we type text messages. Whilst the touchscreen captures finger touches, hand movements during this interaction however are unused. If this implicit hand movement is observed, it can be used as additional information to support or to enhance the users’ text entry experience. This thesis investigates how implicit sensing can be used to improve existing, standard interaction technique qualities. In particular, this thesis looks into enhancing front-of-device interaction through back-of-device and hand movement implicit sensing. We propose the investigation through machine learning techniques. We look into problems on how sensor data via implicit sensing can be used to predict a certain aspect of an interaction. For instance, one of the questions that this thesis attempts to answer is whether hand movement during a touch targeting task correlates with the touch position. This is a complex relationship to understand but can be best explained through machine learning. Using machine learning as a tool, such correlation can be measured, quantified, understood and used to make predictions on future touch position. Furthermore, this thesis also evaluates the predictive power of the sensor data. We show this through a number of studies. In Chapter 5 we show that probabilistic modelling of sensor inputs and recorded touch locations can be used to predict the general area of future touches on touchscreen. In Chapter 7, using SVM classifiers, we show that data from implicit sensing from general mobile interactions is user-specific. This can be used to identify users implicitly. In Chapter 6, we also show that touch interaction errors can be detected from sensor data. In our experiment, we show that there are sufficient distinguishable patterns between normal interaction signals and signals that are strongly correlated with interaction error. In all studies, we show that performance gain can be achieved by combining sensor inputs.

Novopca mobile

A constante evolução da tecnologia obriga a que o mundo empresarial tenha que alocar esforços para se manter actualizado. Os equipamentos tecnológicos que se encontram actualmente na vanguarda da tecnologia são os dispositivos móveis, que cada vez mais nos rodeiam e acompanham com o intuito de nos facilitar a execução de tarefas rotineiras. O ramo de construção e obras públicas em particular é um sector que obriga a que os seus trabalhadores estejam constantemente em movimento, e que muito têm a ganhar com a utilização de ferramentas de trabalho em equipamentos móveis. Neste projecto pretendeu-se identificar qual o sistema operativo para dispositivos móveis que melhor se enquadra com as necessidades empresariais, assim como quais os mecanismos de comunicação inter-máquinas que melhor se enquadram com o cenário em estudo. Foi então desenvolvida uma plataforma para dispositivos móveis que permite agilizar a execução de processos que normalmente são morosos ou que obrigam à utilização do computador em locais menos próprios, nomeadamente o ambiente de obra. A solução proposta e implementada envolve uma aplicação modular quer permita a fácil inserção e remoção de módulos. Foram também realizados os estudos e implementações de quatro módulos, designadamente: auto-afectação, conferência documental, fornecedores e presenças em obra. Concluído este projecto, ficam reunidas as condições para o fácil desenvolvimento de novos módulos, visando inovação e optimização dos processos de trabalho da empresa.

Context-aware personalization environment for mobile computing

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

PRIM an Open Mobile Robot Platform. Motivation, Present and Future Trends

This paper is focused on the robot mobile platform PRIM (platform robot information multimedia). This robot has been made in order to cover two main needs of our group, on one hand the need for a full open mobile robotic platform that is very useful in fulfilling the teaching and research activity of our school community, and on the other hand with the idea of introducing an ethical product which would be useful as mobile multimedia information point as a service tool. This paper introduces exactly how the system is made up and explains just what the philosophy is behind this work. The navigation strategies and sensor fusion, where machine vision system is the most important one, are oriented towards goal achievement and are the key to the behaviour of the robot

Error Modeling and Accuracy Analysis of a Novel Mobile Hybrid Parallel Robot

Over the last decades, calibration techniques have been widely used to improve the accuracy of robots and machine tools since they only involve software modification instead of changing the design and manufacture of the hardware. Traditionally, there are four steps are required for a calibration, i.e. error modeling, measurement, parameter identification and compensation. The objective of this thesis is to propose a method for the kinematics analysis and error modeling of a newly developed hybrid redundant robot IWR (Intersector Welding Robot), which possesses ten degrees of freedom (DOF) where 6-DOF in parallel and additional 4-DOF in serial. In this article, the problem of kinematics modeling and error modeling of the proposed IWR robot are discussed. Based on the vector arithmetic method, the kinematics model and the sensitivity model of the end-effector subject to the structure parameters is derived and analyzed. The relations between the pose (position and orientation) accuracy and manufacturing tolerances, actuation errors, and connection errors are formulated. Computer simulation is performed to examine the validity and effectiveness of the proposed method.

Real-Time Simulation of Mobile and Industrial Machines Using the Multibody Simulation Approach

This thesis introduces a real-time simulation environment based on the multibody simulation approach. The environment consists of components that are used in conventional product development, including computer aided drawing, visualization, dynamic simulation and finite element software architecture, data transfer and haptics. These components are combined to perform as a coupled system on one platform. The environment is used to simulate mobile and industrial machines at different stages of a product life time. Consequently, the demands of the simulated scenarios vary. In this thesis, a real-time simulation environment based on the multibody approach is used to study a reel mechanism of a paper machine and a gantry crane. These case systems are used to demonstrate the usability of the real-time simulation environment for fault detection purposes and in the context of a training simulator. In order to describe the dynamical performance of a mobile or industrial machine, the nonlinear equations of motion must be defined. In this thesis, the dynamical behaviour of machines is modelled using the multibody simulation approach. A multibody system may consist of rigid and flexible bodies which are joined using kinematic joint constraints while force components are used to describe the actuators. The strength of multibody dynamics relies upon its ability to describe nonlinearities arising from wearing of the components, friction, large rotations or contact forces in a systematic manner. For this reason, the interfaces between subsystems such as mechanics, hydraulics and control systems of the mechatronic machine can be defined and analyzed in a straightforward manner.