Företaget Hi5 är i behov av en lösning som kan övervaka bandbreddsanvändningen till ochfrån deras verksamhet. Denna lösning ska kunna mäta använd trafik per IP över tid.Företaget vill ha denna lösning för att i framtiden kunna ha möjligheten att, med data somunderlag, debitera kunder som passerar en avtalad gräns för bandbreddsanvändning.Lösningen ska även ge Hi5 en överblick över all trafik till och från företaget.Denna rapport beskriver sammansättningen av en sådan lösning med hjälp av färdigatjänster och verktyg. Lösningen består av fyra moduler: pmacct, pmacct-to-elasticsearch,Elasticsearch och Grafana. ● Pmacct agerar insamlingsdel som fångar och aggregerar trafikdata.● Pmacct-to-elasticsearch fungerar som en brygga och flyttar data från pmacct till Elasticsearch.● Elasticsearch är backend-delen i lösningen som lagrar och organiserar data iindexfiler.● Grafana, frontend-delen, hämtar data från Elasticsearch och visualiserar denna iform av grafer och tabeller. Resultatet av arbetet är att Hi5 fick en lösning som uppfyllde deras önskemål, där kundersbandbreddsanvändning kan mätas och presenteras i ett användarvänligt gränssnitt. / The company Hi5 is in need of a solution that can monitor the bandwidth usage to and from their operations. This solution should be able to measure used traffic per IP over time. The company wants this solution in order to be able to, in the future, have the data needed available to charge customers who exceeds an agreed upon bandwidth limit. The solution should also give Hi5 an overview of all traffic from and to the company.This report describes the composition of such a solution using completed services and tools. The solution consists of four modules: pmacct, pmacct-to-elasticsearch, Elasticsearch and Grafana. ● Pmacct acts as the collector that catches and aggregates traffic data.● Pmacct-to-elasticsearch works as a bridge and moves the data from pmacct to Elasticsearch.● Elasticsearch is the backend part of the solution that stores and organizes the data in index files.● Grafana, the frontend, collects the data from Elasticsearch and visualizes it in the form of graphs and tables. The result of the project is that Hi5 got a solution that fulfilled their wishes, where customer’s bandwidth usage can be measured and presented in a user-friendly interface.

This thesis deals with transformation of network data reporting process in a Telecom company. The current process is MS Excel based and is inadequate and inefficient. The goal is to find the right tools and to implement them. The thesis is divided into three parts. First part is focused on theoretical background of reporting, i.e. Business Intelligence and other approaches. Second part explains general Network reporting principles and trends. In contrast with these theoretical recommendations, the actual level of the company's process is depicted. The last part of this thesis covers a practical implementation of selected applications. First, a choice is made within a variety of tools based on department's needs then the architecture is proposed and applications are implemented. The final part of the thesis provides an assessment of the benefits attained by this project.

The thesis concerns mainly the construction of a pipeline that enables the analyzing,visualizing, and forecasting of time-series data in an intuitive and streamlined process.The main data set consists of four measurements: purchased heating, purchasedelectricity, and purchased cold water from select buildings at the Lule ̊a Universityof Technology campus as well as the outside temperature of the campus. This isused to establish a proof of concept, demonstrating the validity of this pipeline andits subsystems. Using this pipeline you are able to upload data, visualize data andanalyze data online and also create future forecasts of these measurements which arealso displayed online.As the global demand for energy efficiency increases, tools, like this one, is moreimportant than ever in order to give the decision-makers more insight. In the caseof the campus buildings, you might be able to more easily identify anomalous valueswhich point to some oversight that can then be amended. For instance, if two identicalbuildings exist and one of them consumes 50% more heating, you can conclude thata problem exists and now you know where the problem lies so you can amend theissue.Forecasting future consumption is also helpful since it would allow you to reducethe purchasing of fossil fuels, such as gas, which is the case at La Trobe Universityin Melbourne. Using forecasting they can better predict how much gas they need topurchase and when the peak consumption hours are so that they can adjust their solarproduction accordingly. Thus, forecasting future consumption can further reduce theglobal need and impact of fossil fuels.To conclude, this pipeline can be used as a tool to reduce the environmental impactof the Lule ̊a University of Technology campus buildings. The pipeline can then beapplied to other areas to help them solve their problems. Some of the findings ofthis thesis include comparisons of common forecasting algorithms and the benefits ofusing weekday/weekend models.In the future, this might also inspire others to make similar projects, just like LaTrobe University inspired us at the Lule ̊a University of Technology.

The goal of this individual assignment work has been to implement a experimental environment to load and stress test a virtualized LoRaWAN network together with a LoRa simulation tool through the use of open source software. By researching theory and open source software connected to IoT, LoRa, LoRaWAN, virtualization, simulation and monitoring a experimental environment was implemented for launching test scenarios to stress and load test the virtualized LoRaWAN network. The experimental environment is built on the researched and chosen software Proxmox, Chirpstack, Lorhammer, Prometheus, Grafana and Wireshark. The resulting implementation rendered measurable results in regards to system load, incoming network traffic and UDP errors handled by the Chirpstack Network server through simulated LoRa network scenarios configured for the Lorhammer simulation tool.

Managing and analyzing large volumes of logs can be challenging, and a log management solution can effectively address this issue. However, selecting the right log management solution can be a daunting task, considering various factors such as desired features and the solution's efficiency in terms of storage and resource usage. This thesis addressed the problem of choosing between two log management solutions: ELK and PLG. We compared their tailing agents, log storage and visualization capabilities to provide an analysis of their pros and cons. To compare the two log management solutions we conducted two types of evaluations: performance and functional evaluation. Together these two evaluations provide a comprehensive picture of each tool's capabilities. The study found that PLG is more resource-efficient in terms of CPU and memory compared to ELK, and requires less disk space to store logs. ELK, however, performs better in terms of query request time. ELK has a more user-friendly interface and requires minimal configuration, while PLG requires more configuration but provides more control for experienced users. With this study, we hope to provide organizations and individuals with a summary of the pros and cons of ELK and PLG that can help when choosing a log management solution.

This thesis presents an evaluation of various graphical user interface (GUI) technologies for use in the supervision software of CERN’s Beam Interlock System (BIS). The evaluation is necessary because the current GUItechnology used by the supervision software, JavaFX, is no longer supported by Oracle. It also relies on aninternal library that is no longer maintained. Furthermore, a second version of the BIS is being developed, anda GUI is needed that works with BIS and BIS2 in parallel.Which technology is most suitable for the next version of the BIS supervision GUI?This question was answered by gathering user stories from users and experts. Simple proof of concepts weredeveloped for each technology, in order to identify technical limitations and register the development time. Theuser stories relevant to the choice of technology were listed, and each technology received points depending onwhether they were able to fulfill the requirement or not.Furthermore, in order to evaluate the ease of use, wireframes were created based on some of the user stories.These were qualitatively evaluated with stakeholders, which produced feedback that may be used for furtherdevelopment.Out of the four technologies evaluated, PyQt scored 6, ACW scored 4, WRAP scored 6 and Grafana scored3. WRAP and Grafana were discarded as viable options, since they were not able to fulfill hard requirements.ACW scored lower because it is web based and comes with a bigger maintenance overhead. / <p>This thesis was done as a part of a technical studentship at CERN.</p>

The master thesis focuses on the design and implementation of data collection from production using a PLC into an SQL database located in the cloud and subsequent visualization. The work describes the applicable communication protocols MQTT and OPC UA with the fact that the protocol MQTT was selected. It deals with securing data transfer from the line to the cloud using the TLS protocol. The individual cloud services and their possibilities for data collection are described here. The work deals with the possibilities of data visualization using existing open source solutions and the differences between them. I describe the possibilities of modifying the open source environment of the Grafany project. Real dashboards from production are presented. The data collection system was deployed in two plants for testing.

The diploma thesis deals with automated measurement of humidity and CO2 concentration inside buildings. Results of this measurement form the input parameters for the effective management of technologies reducing the energy performance of buildings. In the introduction, the issue of indoor air quality of buildings and indicators characterizing this quality are approached. The technical part of the thesis consists of making a measuring device which contains two prototype sensors provided by Teco Inc. with online access to measured data. The measurement of relative humidity, CO2 concentration and temperature in the interior of the building with the made device is compared with commercially available devices for measuring selected parameters. For unambiguous interpretation of online data, the virtual machine with an online database is configured for the created measuring device. The possibilities of using the prepared measuring device to achieve a reduction in the energy performance of buildings are discussed in the final part.

The aim of this work is to create a unified control and supervision system, SCADA, for controlling the heating and cooling of the company. The system is controlled by UniPi PLC units. Node-RED is used as control software. The user interface is created by an extension "dashboard". For communication between elements using the MQTT protocol. The InfluxDB database is used for data storage. The Grafana tool is used to visualize historical data. The majority of the created system consists of open software. The system is universal, expandable and it is possible to connect it with another system. The system can be used or adapted to similar problems of advanced heating control.

The goal of this diploma thesis is to design and develop a system for collecting, processing and storing data from large IoT networks. The developed system introduces a complex solution able to process data from various IoT networks using Apache Hadoop ecosystem. The data are real-time processed and stored in a NoSQL database, but the data are also stored  in the file system for a potential later processing. The system is optimized and tested using data from IQRF network. The data stored in the NoSQL database are visualized and the system periodically generates derived predictions. Users are connected to this system via an information system, which is able to automatically generate notifications when monitored values are out of range.