Today, large companies specialized in forestry or park maintenance may own very large machine fleets consisting of hundreds of trimmers, chainsaws and brush cutters. Husqvarna Group, whose core business lies within high-end forestry and gardening products, has noticed that such companies tend to buy cheaper, low quality forestry and gardening products. The reason is thought to be that the companies lack a proper overview of the service status and utilization levels of their machines, leading to insufficient service, causing machines to break prematurely and making it hard to motivate investments in more expensive products. Hence, the companies usually adopt a consumerist approach, and buy cheaper products that are thrown away upon breaking. To make their products more attractive to machine park owners, Husqvarna want to explore the area of Internet of Things and equip their machines with sensing and communication capabilities. Collected data could be used to provide an overview of machine usage and service requirements to the machine parks owners, and could make it easier for machine park owners to dimension their machine fleet. In addition to this, a machine monitoring system where specific operator behavior can be tracked could enable identification of operators who consistently mistreat their machines by, for example, running the machine engine at non-optimal rotation speeds. In this master's thesis, a demonstrator of the working principle of a Bluetooth Low Energy based Fleet Service System is designed and implemented, complete with an evaluation of if received signal strength indicator (RSSI) is a good enough distance estimator to determine which operator operates a certain machine.  Experiments carried out indicate that while RSSI is not a good estimator of distance, it could be used to determine the operator in closest proximity given that operators are not allowed to work closer than within a 10 m radius of each other.

<p>Kommentar till en debatt.</p>

Thesis (doctoral)--Universität Marburg.

Thesis (doctoral)--Universität Erlangen.

El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado. / In recent years the advancement of technologies of information and communication (technology ICTs) have helped to improve the quality of people's lives. The paradigm of internet of things (IoT, Internet of things) presents innovative solutions that are changing the style of life of the people. Because of this proposes the implementation of a smart mirror as part of a system of home automation, with which we intend to optimize the time of people as they prepare to start their day. This device is constructed from a reflective glass, LCD monitor, a Raspberry Pi 3, a camera and a platform IoT oriented cloud computing, where the information is obtained to show in the mirror, through the consumption of web services. The information is customizable thanks to a mobile application, which in turn allows the user photos to access the mirror, using authentication with facial recognition and user information to predict the news to show according to your profile. In addition, as part of the idea of providing the user a personalized experience, the Smart Mirror incorporates a news recommendation algorithm, implemented using a predictive model, which uses the algorithm, naive bayes. / Revisión por pares

Location tracking on mobile devices like smartphones has already begun to revolutionize personal navigation. Unfortunately, these services perform poorly indoors when GPS signals are no longer available. Highly accurate indoor location tracking would enhance a wide variety of applications including: building navigation (malls, factories, airports), augmented reality, location-aware pervasive computing, targeted advertising, social networking, participatory sensing and could even support next generation beam forming MIMO wireless networks. Current indoor localization systems for smartphones often use RF signal strength from WiFi access points or Bluetooth Low Energy (BLE) beacons to fingerprint indoor locations. Such systems are sensitive to environmental changes and obstructions, require extensive training procedures and are limited in both absolute as well as semantic localization accuracy. We propose using audio signals in the ultrasound spectrum, just above the human hearing range, to provide ranging and localization for many off-the-shelf mobile devices that are equipped with microphones. Ultrasonic ranging provides several advantages over RF-based ranging and fingerprinting approaches, which make it attractive for indoor localization. A relatively low propagation speed and carrier frequency allow for precise propagation time measurements in software using commodity hardware. Acoustic signals also have a low penetration depth, which confines them to target areas for accurate semantic localization. In this dissertation we address several challenges related to acoustic localization, including system scalability, ranging and localization accuracy, energy efficiency, robustness to noise, elimination of human perceivable audio artifacts, efficient use of limited acoustic bandwidth and rapid deployment strategies.

In today’s era of the Internet of Things, it is crucial to study the real-time dependencies of the web, its failures and time delays. Today, smart grids, sensible homes, wise water networks, intelligent transportation, infrastructure systems that connect our world over are developing fast. The shared vision of such systems is typically associated with one single conception Internet of Things (IoT), where through the deployment of sensors, the entire physical infrastructure is firmly fastened with information and communication technologies; where intelligent observation and management is achieved via the usage of networked embedded devices. The performance of a real-time control depends not only on the reliability of the hardware and software used but also on the time delay in estimating the output, because of the effects of computing time delay on the control system performance. For a given fixed sampling interval, the delay and loss issues are the consequences of computing time delay. The delay problem occurs when the computing time delay is non-zero but smaller than the sampling interval, while the loss problem occurs when the computing time delay is greater than, or equal to, the sampling interval, i.e., loss of the control output. These two queries are analyzed as a means of evaluating real-time control systems. First, a general analysis of the effects of computing time delay is presented along with necessary conditions for system stability. In this thesis, we will focus on the experimental study of the closed loop control system in the internet of things to determine the cycle time constraints in case of link failure.

Det här arbetet har syftat till att utvärdera möjligheterna till att använda Raspberry Pi 2, som en del av ett identifikationssystem i vårdmiljöer. Rapporten tar upp och utvärderar möjligheterna att använda olika hårdvara och mjukvara tillsammans med Raspberry Pi, så som olika RFID-läsare, operativsystem och styrmjukvara till RFID-läsarna. Rapporten tar även upp tidigare forskning och implementationer av RFID-användning i vårdmiljöer. Från början var målet att använda Snappy Ubuntu Core som operativsystem, men laborativt arbete visade att Snappy Ubuntu Core inte riktigt hade vad som krävdes för att uppfylla syftet. Arbetet har resulterat i konstruerad mjukvara för att styra och läsa av RFID-kort med en av RFID-läsarna som testats, och det har även experimenteras med Node-RED tillsammans med RFID-mjukvaran.

No Abstract was provided. / Thesis / Master of Arts (MA)

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