The goal of this thesis was to develop, deploy and evaluate a lightweight portable intrusion detection system (LPIDS) over wireless networks. The LPIDS was developed by adopting two different string matching algorithms: Aho-Corasick algorithm and Knuth–Morris–Pratt algorithm (KMP). The LPIDS was implemented and tested on the hardware platforms Wi-Fi Pineapple and Raspberry Pi. To evaluate and test the LPIDS as well as the algorithms, performance metrics such as throughput, response time and power consumption are considered. The experimental results reveal that Aho-Corasick performed better than KMP throughout the majority of the process, but KMP was typically faster in the beginning with fewer rules. Similarly, Raspberry Pi shows remarkably higher performance than Wi-Fi Pineapple in all of the measurements. Moreover, we compared the throughput between LPIDS and Snort. It was concluded that the throughput was significantly higher for LPIDS when most of the rules do not include content parameters. This thesis concludes that due to computational complexity and slow hardware processing capabilities of Wi-Fi Pineapple, it could not become suitable IDS in the presence of different pattern matching strategies. Finally, we propose a modification of Snort to increase the throughput of the system.

Nowadays, a growing number of startups, who used to produce non- intelligent devices, are seeking transformation and hope to achieve their Internet of Things (IoT) deployment. In other words, they begin to focus on producing smarter devices to meet user’s needs. At present, various IoT cloud platforms are emerging one after another, but using these resources can be costly for small companies. Since the entire IoT system is complex, it involves many links, the purpose of this project is to create a suitable IoT platform for small companies. The system applies JavaWeb technology with the framework of Spring MVC + Spring + Hibernate (SSH), uses open source User Interface (UI) solution and MySQL database management system (DBMS). At the same time, the system adopts Hypertext Transfer Protocol (HTTP) as the communication protocol to complete the data transmission between devices and the platform. Finally, the system is deployed in the server built on the Raspberry Pi. The system is measured from multiple aspects on the established scenario. The results show that companies and users can use the platform as expected, and companies can expand the system to further realize their IoT deployment in the future.

Raspberry production in Utah is concentrated to a large extent in Utah county. According to the 1940 census, Utah county contains 62 percent of the state acreage of 611 acres. Average raspberry acreage in Utah is only about one-half acre per farm on farms reported as growing raspberries. With such small acreage the average producer cannot afford to devote very much time and effort to the production and marketing of raspberries. In the majority of cases raspberry production is carried on by the farmer's wife, as a means of gaining “pin” money for use in the household. Proceeds from raspberries are one of the first cash incomes of the year received from fruit production. The harvesting of raspberries begins about the 25th of June and lasts until the end of July in Utah county. Because of the small acreage per grower, short production season, and high perishability of raspberries, a problem of marketing arises. Previous to 1939, the Salt Lake Public Market was over-supplied with raspberries during peaks of production. This resulted in low prices. Peddlers and truckers dictated the price received by producers. Thus, low prices often resulted and caused the berries to be left on the vines as the prices would not pay the cost of picking and packing. In order to provide better market outlets, establish satisfactory grades and standards, and provide for more orderly marketing, the producers in Utah county organized a Cooperative Marketing Association in 1939. This association was organized for the purpose of marketing raspberries grown by producers in Utah county from Mapleton to Pleasant Grove. The purpose of this study is: (1) to show the problems relating to the marketing of raspberries in Utah, (2) to analyze data made available by the Utah Berry Growers' Association order to show market areas, methods of marketing, price received by method of sale, marketing expenses and to determine sales and prices received on week days and holidays, (3) to analyze the possibility of extending the markets for Utah raspberries.

Unlike other rosaceous fruit crops such as apple and cherry, commercial raspberry cultivars are largely self-fertile and can set fruit in the absence of pollinators. However, their floral morphology often prevents complete self-pollaintion. Incomplete pollination yields unmarketable small or crumbly fruits. Insect visitation is therefore essential to maximizing raspberry yield. Honey bees are typically used to pollinate commercial raspberry; however, escalating prices for hive rentals coupled with increasing acreage encourage evaluation of other manageable pollinators. Bumble bees (Bombus spp.) and several mason bees (Osmia spp.) are promising raspberry pollinators. Five bee species were evaluated and compared for their single-visit pollination efficacies on raspberry. From this a pollinator effectiveness index was created and an estimation of the minimum number of visits required to maximize fruit set was calculated. This estimation was then experimentally verified. Finally, in an attempt to synchronize their brief activity period with raspberry bloom, winter management options aimed at delaying the emergence of the mason bee, O. lignaria, were investigated. All five bee species proved excellent pollinators of raspberry. None of the alternative manageable species greatly outperformed honey bees. For this reason honey bees remain the most economical and practical option for open-field raspberry pollination. The adoption of alternative manageable bees could still be justified in other production systems, such as high-tunnel or greenhouse grown raspberry, which hamper honey bees’ ability to forage effectively. The pollinator effectiveness score for honey bees suggested that as few as two visits can achieve maximum fruit set. This estimate was confirmed through experimentation on three different red raspberry cultivars. For two of these cultivars, just one visit yielded drupelet counts similar to openly-pollinated flowers. This information can be used to help refine stocking density estimates for honey bees on raspberry. Wintering bees at 0° or -3° C rather than 4° C effectively delayed emergence of O. lignaria by more than a month without any impact on post-winter performance. These results suggest winter storage at near freezing temperatures is a viable management option for the use of O. lignaria with later-blooming crops.

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This thesis is concerned with the usability of Raspberry Pi as the access point in the mobilebroadband network environment. The first part of the thesis is dedicated to Raspberry Pi itself;hardware required to set up WLAN and WAN; and to the analysis of suitable solutions forbandwidth aggregation, particularly the load balancing of mobile broadband connections andtheir aggregation into one logical link. The second part deals with the implementation of thesesolutions and subsequently with their testing and verification. The evaluation of results gives aninteresting outcome. Load balancing has proven to be resilient and feasible solution forbandwidth aggregation in the mobile broadband network environment where the speed, packetloss and jitter are of main concern. The second scenario, where the connections are bundled intoone logical link, has turned out to give variable results. Its performance is susceptible to thechanges in the mobile broadband network as the packets across the links in the bundle alternatein the round-robin fashion.

The main goal of this thesis is to highlight the various limitations that the LPWAN LoRa and by proxy other similar technologies currently suffers from to give further insight into how these limitations can affect implementations and products using such a network. The thesis will be supported by experiments that test how a LoRa network gets affected by different environmental attributes such as distance, height and surrounding area by measuring the signal strength, signal to noise ratio and any resulting packet loss. The experiments are conducted using a fully deployed LoRa network made up of a gateway and sensor available to the public. To successfully deploy a LoRa network one needs to have concrete information about how to set it up depending on different use cases as battery lifetime and a solid connection has to be kept in mind. We test the various performance aspects of a LoRa network including signal quality and packet loss at different communication ranges. In addition to that we also test different environments and investigate how these can impact the performance. The conclusions made in this thesis are that a LoRa network is limited in its use cases for smaller scale projects with low gateway elevation that still require a large distance. This is due to the obstruction of the signal quickly making it reach unusable levels at roughly 300m in a city and 600m in a forest. Making the line of sight free either by elevation of the hardware or by adapting to the terrain makes the network perform very well making the possibility for packet loss lower which in combination with the low duty cycle of the transmissions is needed as every packet lost is going to be very noticeable.

The Internet of Things (IoT) plays an important role in the coming era of the Internet development. In addition to the convenience and opportunities it brings to us, there comes with the security issues, which could lead to the privacy leakage, it’s a threaten to the whole IoT system. To deal with the potential dangerous element hidden behind this technology, monitoring on the network would be indispensable. To develop and implements the digital network watchdog system that monitors the local network and the connected device, firstly, I surveyed the area related to the IoT attacks. The network monitor system provides basic network monitoring function, connected device tracking and monitoring function, reliable device operating function. I used the packages provided by Raspberry Pi to realize the general monitoring and transferred the captured result for further analysis. Also, I made use of SNMP and drawing tool to create graphs of different parameters in the monitoring of both network and connected devices. Then I implemented database with web service on Raspberry Pi to realize device operating. In evaluation, the system works well in general monitoring with all information provided and low lost package percentage, the graphs can provide situation of different parameters, and the respond time in the operation time of database is short. I discussed the ethical thinking and proposed the ethical thinking and future work.

The area of computer vision has been making big improvements in the latest decades, equally so has the area of electronics and small computers improved. These areas together have made it more available to build small, standalone systems for object detection in live video. This project's main objective is to examine whether a small device, e.g. Raspberry Pi 3, can manage an implementation of an object detection algorithm, called Viola-Jones, to count the occupancy of sitting people in a room with a camera. This study is done by creating an application with the library OpenCV, together with the language C+ +, and then test if the application can run on the small device. Whether or not the application will detect people depends on the models used, therefore three are tested: Haar Face, Haar Upper body and Haar Upper body MCS. The library's object detection function takes some parameters that works like settings for the detection algorithm. With that, the parameters needs to be tailored for each model and use case, for an optimal performance. A function was created to find the accuracy of different parameters by brute-force. The test showed that the Haar Face model was the most accurate. All the models, with their most optimal parameters, are then speed-tested with a FPS test on the raspberry pi. The result shows whether or not the raspberry pi can manage the application with the models. All models could be run and the Haar face model was fastest. As the system uses cameras, some ethical aspects are discussed about what people might think of top-corner cameras.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / This paper presents the obtaining of electric power consumption curves, from the responses generated by an embedded low-cost Raspberry Pi 2 Model B system running the Linux operating system Raspbian working as a remote access server SSH, which is assessed through different types of access and brute force attacks dictionaries through specialized tools Medusa and Hydra, as well as the tool Metasploit unspecialized. The energy behavior is interpreted by a current consumption measurement system developed by low embedded platform cost Arduino Uno that runs a current sensor based on ACS721ELC-5A Hall effect chip, which has the ability to collect the variations generated by the platform test in response to events produced by the proposed test scenarios, the data is processed by the framework Matlab that collects, parses and normalizes using the Welch method, the current signal which is interpreted by Arduino Uno subsequently presents a standard curve It features a particular event based on scenarios of evidence. The results show the different curves standard patterns, and contextualized on the types of scenarios evaluated subsequently presents a theoretical mathematical model of the proposed power consumption, as well as rules or signatures proposed to identify an attack using the detection method of standards used IDS Snort. These current curves facilitate understanding and obtaining a pattern of current consumption for each access and attack the embedded platform. / Este trabalho apresenta a obtenção de curvas de consumo de corrente elétrica, a partir das respostas geradas por um sistema embarcado de baixo custo Raspberry Pi 2 Model B executando o sistema operacional Linux Raspbian trabalhando como um servidor de acesso remoto SSH, que é avaliado através de diferentes tipos de acessos e ataques de força bruta com dicionários através das ferramentas especializadas Medusa e Hydra, como também a ferramenta não especializada Metasploit. O comportamento energético é interpretado por um sistema de medição de consumo de corrente desenvolvido pela plataforma embarcada de baixo custo Arduino Uno que administra um sensor de corrente baseado no chip ACS721ELC- 5A de efeito Hall, que possui a capacidade de coletar as variações geradas pela plataforma de teste em resposta aos eventos produzidos pelos cenários de provas propostos, os dados são processados pelo Framework Matlab que coleta, analisa e normaliza por meio do método de Welch o sinal de corrente que é interpretado pelo Arduino Uno, posteriormente apresentase uma curva padrão que caracteriza um determinado evento baseado nos cenários de provas. Os resultados apresentam as diferentes curvas padrões normalizadas, e contextualizadas nos tipos de cenários avaliados, seguidamente apresenta-se um modelo matemático teórico do consumo de corrente proposto, como também as regras ou assinaturas propostas para identificar um ataque através do método de detecção por padrões que utilizada o IDS Snort. Essas curvas de corrente facilitam o entendimento e obtenção de um padrão de consumo de corrente para cada acesso e ataque na plataforma embarcada.