Sirvi Autor "Pourmoradnasseri, Mozhgan, juhendaja" järgi

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Alighting Estimation in Entry-Only AFC Systems; a Case Study of Tartu City
(Tartu Ülikool, 2023) Keshi, Erald; Pourmoradnasseri, Mozhgan, juhendaja; Hadachi, Amnir, juhendaja; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Arvutiteaduse instituut
Tõhusa ja ökoloogilise ühistranspordivõrgu kavandamiseks on oluline kodanike liikumismustrite täpne mõistmine. Nende ühistranspordi liikumisharjumuste põhjalik mõistmine on võimalik ainult sisenemise ja väljumise andmete analüüsi abil. Automaatsed piletihindade kogumise süsteemid on muutunud populaarseks andmeallikaks ühistranspordi uurimisel, kuid ainult sisenemisega seotud automaatsed piletihindade kogumise süsteemid, nagu näiteks Tartus kasutatav süsteem, ei hõlma selliseid kriitilisi andmeid nagu reisijate sihtkohad või ühistranspordist väljumiste ajad. See piirab lähteja sihtkohtade maatriksite koostamist ja selliste andmete saamist nagu busside täituvus ja tipptunnid. Üks võimalus selle piirangu kõrvaldamiseks on kasutada tõenäosuslikke hindamismeetodeid. Käesoleva lõputöö eesmärk on uurida, arendada ja võrrelda erinevaid meetodeid, mille abil saab hinnata ainult sisenemisega seotud AFC-süsteemidest pärit väljumise andmeid. Neid meetodeid saab kasutada andmete puudujääkide täitmiseks ja ulatuslikuma ülevaate andmiseks ühistranspordi kasutusmustritest, mis aitab paremini otsustada marsruutide ja sõiduplaanide planeerimise üle.
Analysis of Bicycle Sharing Data for Decision Support to Expanding Tartu Cycling Infrastructure
(Tartu Ülikool, 2024) Tarro, Martti; Pourmoradnasseri, Mozhgan, juhendaja; Tera, Helen, juhendaja; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Arvutiteaduse instituut
Public bicycle sharing systems have seen an increase in use across many cities in the world, and their expansion is partially dependent on the state of the infrastructure. Traditional road planning procedures rely on empirical evidence and surveys. The widespread availability of GPS data from micromobility sharing systems have seen the approaches enhanced by the analysis of movement patterns. Tartu has strategic plans for expansion of its cycling network to make the city as well as its surroundings more accessible by cycling. This thesis examines the patterns of Tartu Bike Share users using their geolocation data, and compares the planned networks to proposed paths from four strategies for prioritisation of new road sections. The strategies focus on evaluating current cycling patterns, estimating optimal paths, finding ways to make the current network more cohesive, and a combination of these strategies through MULTIMOORA modelling. The prioritised gaps from the model include multiple potential cycling paths, that had not been included in the planning of the main and auxiliary networks. The cycling network in Tartu is already expansive, but identifying significant gaps in the current and planned networks has the chance to improve it yet more.
Analytics and Decision Support for Public Bicycle Sharing in Tartu
(Tartu Ülikool, 2022) Tera, Helen; Hadachi, Amnir, juhendaja; Pourmoradnasseri, Mozhgan, juhendaja; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Arvutiteaduse instituut
A public bicycle sharing system is a short-term rental service in which bicycles are made available for shared use. Due to the environmental, social, and health benefits of cycling, significant motivation exists for promoting cycling in a city, and public bicycle sharing is a promising approach for increasing the number of cyclists. In 2019 a public bicycle sharing program was launched in Tartu. Since then, it has experienced intense usage, but no thorough analysis has been conducted based on its novel data. This thesis aims to use this little-explored data in order to understand the mobility patterns of Tartu Smart Bike users and provide justified suggestions for improving both the existing bicycle sharing network and the cycling infrastructure of Tartu in general. As a result, a detailed analysis of the usage patterns of Tartu Smart Bike is carried out, giving a better understanding of the cyclists’ behavior and motivation in the city of Tartu. A reproducible method for locating new bicycle share stations is presented, and its results based on the case of Tartu Smart Bike are discussed and assessed. Additionally, the road usage intensity of Tartu Smart Bike users is analyzed in order to identify areas that demonstrate a lack of designated cycling infrastructure. This thesis presents both findings specific to Tartu Smart Bike and methods that can easily be adjusted for use in other cities in the hope of contributing to the development of a more bicycle-friendly society.
Data Mart for Photovoltaic Parks SCADA Systems
(Tartu Ülikool, 2024) Suitslepp, Siim; Pourmoradnasseri, Mozhgan, juhendaja; Sarnet, Taavi, juhendaja; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Arvutiteaduse instituut
Estonia and Europe have set ambitious goals to achieve climate neutrality by 2050. Achieving these goals requires a significant push toward renewable energy sources, particularly wind and solar power. This transition is crucial to ensure that future generations inherit a stable climate and environment, similar to what we experience today. Solar energy has made remarkable progress, with a 40% growth rate in 2023 alone. To meet these climate targets, the pace of renewable energy development in Europe and Estonia must accelerate, making it essential to attract more investment into the sector. As the renewable electricity market has rapidly evolved in recent years, traditional passive renewable energy projects have become less financially viable. The focus has shifted toward controllable renewable projects that require extensive data manipulation and analysis. This thesis addresses this need by exploring the data generated by solar parks, identifying key challenges, and proposing a new approach to managing and utilizing solar park data through the creation of a data mart. The research begins with an examination of the initial issues related to device data, followed by the development of a data pipeline designed to feed into the data mart. The thesis concludes with a discussion on the usage of data mart with a demonstration of a first feature to fill gaps in production data.
Exploring the Impact of COVID-19 on Tartu Smart Bike Usage
(Tartu Ülikool, 2023) Loog, Karl Gustav; Pourmoradnasseri, Mozhgan, juhendaja; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Arvutiteaduse instituut
COVID-19 pandeemial oli oluline mõju meie igapäeva elule, märgatavalt oli ka mõjutatud transpordisektor. Tartus võrdlemisi uus rattaringlus süsteem Tartu Smart Bike pakkus alternatiivseid transpordi võimalusi pandeemia ja liikumispiirangute vältel. Siiski on vähe uuritud, kuidas pandeemia mõjutas nende rataste kasutamist. Antud uuringu eesmärk on täita see lünk, analüüsides Tartu Smart Bike süsteemi avalikke andmeid perioodil 2020 kuni 2022, et teha kindlaks kas ja kuidas on rattaringlus muutunud. Uurimustöö tulemused näitavad teostatud sõitude omaduste muutuseid liikumispiirangute vältel. Rattasõidud on muutunud pikemaks nii vahemaa kui ka aja arvelt, kuid keskmine sõidukiirus on vähenenud, mis võib viidata, et rattaid kasutati rohkem vaba aja veetmiseks ja treeninguteks. Uuring tõstatab esile ka võimaluse kasutada Tartu Smart Bike andmeid jätkusuutlikuma ja tõhusama infrastruktuuri ja transpordisüsteemi arendamiseks.