[kand] Sähkötekniikan korkeakoulu / ELEC

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  • Exploring user similarity metrics: A review across interaction, text, and user profile domains
    (2025-12-08) Määttä, Thuy
    School of Electrical Engineering | Bachelor's thesis
    The rapid growth of online communities attracts variety of research especially user similarity metrics, a key component for understanding the relationships between users in online environments. A number of metrics exist to determine user similarity, from traditional metrics, such as Jaccard coefficient or cosine similarity, to more complex metrics. However, in the modern online platforms, the relationships between users have become increasingly complex, which reveals the limitations in the traditional metrics. This thesis studies on different existing user similarity metrics through an overall literature review. The metrics are grouped into three categories based on interaction, text, and profile information of the users. Each category is examined in terms of its definitions, strengths, and limitations. The study concludes that each of these categories is suitable for analyzing the similarity relationships between users on certain platforms. Furthermore, it finds that combining metrics from different categories can benefit the user similarity results. Finally, the thesis highlights the needs of an application of the metrics on an unified platform, such as Reddit, and an evaluation of their computational efficiencies in order to conclude a better comparison. Additionally, it calls for more research and a proposal of a new hybrid metric which can yield a more accurate similarity score and perform well in a sparse dataset.
  • Implementation of federated learning on microcontrollers
    (2025-12-12) Halttunen, Kauri
    School of Electrical Engineering | Bachelor's thesis
    Federated learning is a decentralised method of machine learning. It enables ML where data movement and aggregation are infeasible due to sensitive content or data transmission limitations. The advantages of distributed learning vary based on the specifics of the implementation, hardware, design goals, and other details. Thus, the inherent decentralisation of the IoT creates a suitable opportunity for FL. This thesis aims combine the disciplines of microcontroller programming and machine learning to produce a working example of FL and evaluate the associated challenges. The study utilised a freely available human activity recognition dataset gathered from eight subjects to train multiple independent neural networks. To resemble a practical deployment of microcontrollers, every worker received and trained on data from one subject. The neural networks were merged to create a global model using a simplified variant of FedAvg. The training loss and accuracies of the independent models are compared with the global model, which is also tested with new subject data to simulate new entrants to the FL system.
  • LLM-based multi-agent architecture for transport network automation using MCP and A2A protocols
    (2025-12-11) Dinh, Tue
    School of Electrical Engineering | Bachelor's thesis
    Large language models (LLMs) have recently been used as the brains behind many AI agents, which can reason and act in natural language. While single-agent systems have demonstrated their potential in automating tasks, their robustness is bounded in fields with complicated behaviors. In this case, multi-agent systems (MASs) provide a natural extension. They enable agents to collaborate in groups to achieve the goal. Transport network management is a suitable domain for application. It includes coordinated workflows such as network monitoring, fault localizing, and trouble ticketing. However, current MAS implementations often rely on custom frameworks and manual connections. This limits the interoperability and modularity. To address this challenge, this thesis proposes an MAS architecture that leverages two recent open standards: the Model Context Protocol (MCP) and the Agent-to-Agent (A2A) protocol. The former protocol standardizes agent-to-tool interactions and the latter one supports agent-to-agent communication. Together, these protocols enable a framework-neutral plug-and-play approach to integrate agents, tools, and services. A prototype of this architecture was designed and implemented on a representative transport network automation controller. Its effectiveness was evaluated on key performance indicators such as task success rate, error isolation, modularity, and LLM token cost. The results demonstrate that an open standard-based MAS architecture can improve the interoperability and scalability of autonomous network operations. Beyond the prototype, the thesis aims to contribute a reference design pattern to use such LLM-based MAS in high-stakes automation domains.
  • LLM agent for autonomous CoAP-based IoT systems
    (2025-12-12) Nguyen, Duc Tung
    School of Electrical Engineering | Bachelor's thesis
    IoT is one of the core technologies that enables "Industry 4.0" and facilitates people's work in various domains. Due to their software implementation with statically defined functions, traditional IoT systems can solve tasks that developers have previously anticipated, implemented, and deployed. However, IoT systems require complex processes to extend their capabilities, and they struggle with context-aware decision-making. Recent advances in large language models and agentic AI frameworks have created opportunities for developing autonomous AI agents that emerge as a possible solution to the problem. Therefore, this thesis investigates the architecture, implementation, and performance of an LLM agent in a CoAP-based IoT system. The architecture consists of an LLM agent developed with the SmolAgents library, with GPT-4o as the brain of the agent, CoAP-specific tools to enable interaction with the IoT environment, and memory components to enhance the performance of the agent. Experiments with a simulated smart home CoAP-based IoT system are conducted to evaluate the performance of the agent in response to user requests. The results demonstrate the potential of the LLM agent architecture in consistently and accurately solving both explicit and implicit user requests. Although there are several limitations remaining, such as the range of LLMs used, the lack of experiments with real-world IoT systems, and the absence of advanced AI-related methods, this research lays a foundation for applying an LLM agent in CoAP-based IoT systems.
  • Vision-language-action models for humanoid robots in elderly care applications
    (2025-12-05) Saarinen, Jaakko
    School of Electrical Engineering | Bachelor's thesis
    This thesis explores Vision-Language-Action models and their potential applications in humanoid robots designed for elderly care. The study reviews how multimodal learning, large language models, and embodied AI contribute to natural and adaptive human-robot interaction. The research is based on a comprehensive literature review focusing on integration methods, training approaches such as imitation and reinforcement learning, and ethical considerations. The findings highlight that VLA-based humanoids can enable more personalized and intuitive interaction, potentially alleviating future labor shortages in elderly care. However, challenges remain regarding data requirements, computational costs, and societal acceptance.
  • Avoimen lähdekoodin ohjelmistoprojektien käyttö tieteellisessä tutkimuksessa
    (2025-12-19) Jääskeläinen, Veikko
    School of Electrical Engineering | Bachelor's thesis
    Avoimen lähdekoodin ohjelmistojen käyttö ja kehitys tutkimuskäytössä on yleistynyt. Yli 70 prosenttia tutkijoista sanoo, ettei heidän tutkimuksensa tekeminen olisi mahdollista ilman heidän käyttämiään ohjelmistoja. Ohjelmistoprojekteissa viitataan yhä useammin julkaistuun tutkimukseen, ja vastaavasti tutkimuksissa viitataan entistä useammin ohjelmistoprojekteihin. Tässä kandidaatintyössä selvitetään, miten avoimen lähdekoodin ohjelmistoprojektit sopivat tutkimuskäyttöön. Työ on toteutettu kirjallisuuskatsauksena. Työssä on esitelty, mitä ominaisuuksia avoimen lähdekoodin ohjelmistoprojekteilla on, kuten ohjelmiston lisenssi sekä projektin versionhallintaohjelma ja dokumentaatio. Työhön on koottu, mitä lisäpiirteitä avoimen lähdekoodin ohjelmistoprojekteilta vaaditaan tutkimuskäytössä. Esimerkiksi arkistointi- ja viitetiedot ovat vaadittuja lisäpiirteitä. Näiden lisäksi työssä on tarkasteltu tutkimuskäytön erityisvaatimuksia. Tutkimuskäytössä on tärkeää, että ohjelmiston lisenssi sallii käytön tutkimuksessa ja että projektin dokumentoinnissa on huomioitu projektin taustalla oleva tieteellinen tutkimus.
  • From pilot to profit: A conceptual framework for AI-driven design automation
    (2025-12-12) Peltonen, Rudolf
    School of Electrical Engineering | Bachelor's thesis
    The rapid advancement of artificial intelligence (AI) technology has compelled enterprises and organizations to reconfigure their operational models. Despite substantial resource allocation toward AI implementation, a significant proportion of projects lack the anticipated results. Recent reports indicate that AI solutions fail at a rate nearly double that of IT projects from a decade ago. However, different factors have been identified between failed pilot initiatives and solutions that successfully scale to production. The reasons for failure are mainly strategic, including ambiguous objectives, poor data quality, and friction in workflow integration. While general-purpose solutions for AI implementation exist, frameworks in the context of design automation are scarce. The objective of this thesis is to address this research gap by developing a conceptual framework for AI development within the context of design automation. The study is a literature review that synthesizes causes of failure, critical success factors, and theoretical aspects key to success, such as requirements engineering and data management. The literature review revealed that in addition to technical capabilities, success depends on the ability to integrate solutions into existing workflows. Based on the analysis, the resulting Pilot-to-Profit framework is structured around four primary concepts: Goal Granularity, Data Maturity, Task-Technology Fit, and Human-AI Collaboration. The framework provides a systematic model for bridging the so-called GenAI Divide and developing productive solutions. This model can be utilized to evaluate the automation potential of design work and the viability of implementing AI solutions.
  • Analys av LED-drivdon med effektfaktorkorrigering
    (2025-12-08) von Knorring, Casimir
    School of Electrical Engineering | Bachelor's thesis
    I takt med att LED-belysning ersätter konventionella ljuskällor såsom glödlampor och fluorescerande lysrör, ökar även behovet av effektiva och tillförlitliga drivdon. Dessa är anpassade för att garantera en jämn strömtillförsel till LED-armaturer och på så sätt förbättra livslängden, effektiviteten samt styrbarheten hos lysdioder. Detta arbete analyserar funktionen och strukturen hos LED-drivdon som är baserade på switch-mode-omvandlare, med särskilt fokus på hur de upprätthåller en stabil och effektiv strömtillförsel till lysdioder. Inledningsvis presenteras den teori som anknyter till drivdonets funktion, vilket utgör grunden för den efterföljande, mer fördjupade analysen. Genom att analysera olika switch-mode-omvandlare och deras roll vid strömreglering belyses hur drivdonen formar och anpassar den inkommande spänningen efter lysdiodens behov. Arbetet redogör även för effektfaktorkorrigeringens betydelse, särskilt med avseende på hur ett integrerat effektfaktorkorrigeringssteg kan minska harmonisk distorsion och därigenom förbättra effektfaktorn. Vidare behandlas drivdonets övergripande struktur samt olika omvandlartopologiers inverkan på drivdonets prestanda, kostnad och komplexitet. Arbetet innefattar en produktanalys av en utvald produkt som innehåller ett LED-drivdon. Analysen ger en konkret och tillämpbar förståelse för hur de behandlade principerna realiseras i en faktisk utformning av ett LED-drivdon. Genom denna helhetsöversikt klargörs de centrala principerna bakom moderna LED-drivdon samt de avvägningar som krävs för att uppnå hög energieffektivitet och lång livslängd.
  • Generatiiviset tekoälymallit uusien syöpälääkkeiden kehittämisessä
    (2025-12-10) Tirri, Miranda
    School of Electrical Engineering | Bachelor's thesis
    This bachelor's thesis is a literature review that examines how artificial intelligence can be used to accelerate the development and implementation of cancer drugs. The study investigates what types of AI models can be used to evaluate potential cancer drug candidates, as well as how these models have already been applied in practice. In this work, we review several generative AI models that have been used in pharmaceutical research. We also examine which stages of the drug development process these generative models support. These stages include molecular design, target molecule identification, and optimization of drug candidates. Furthermore, this thesis compares the advantages of AI-assisted cancer drug research with traditional pharmaceutical research. These advantages include speed and cost-efficiency.
  • Puolijohdekvanttipisteitä käyttävät virusten tunnistusmenetelmät
    (2025-12-18) Huotari, Rebekka
    School of Electrical Engineering | Bachelor's thesis
    Virus detection, especially of pathogenic viruses, is important for individuals and for societies. For individuals, it is important to get precise treatment at the right time. Getting the right treatment also prevents the virus from spreading. The prevention of spreading and the right treatment cuts the indirect costs caused by viruses. Traditional virus detection usually requires a laboratory and trained personnel to do the detection. There is still room for improvements of the detection methods. One possibility would be to use semiconducting quantum dots as part of virus detection methods. Quantum dots are semiconducting nanoparticles with excellent optical properties. Electrical conductivity can also be used as an advantage. Several studies have shown that virus detection can be enhanced using quantum dots. In these studies, precision, specificity, cost efficiency and usage outside laboratories have been enhanced. This bachelor’s thesis makes an introduction to the structure of quantum dots and manufacturing them. Virus detection in general and with quantum dots are also addressed in this literature research.
  • Optical properties of nanostructured glass
    (2025-12-12) Hurnanen, Santeri
    School of Electrical Engineering | Bachelor's thesis
    This bachelor's thesis focuses on nanostructured glass solar concentrators. The technology is based on a nanoscale layer manufactured on the glass surface with a femtosecond laser, which aims to direct part of the incident light hitting the device to solar panels installed at the edges of the glass. In particular, this thesis examines the effect of laser parameters on these properties. In this study, spectrometry measurements were performed on eight samples. Based on the measurement results, the work presents the absorption, reflection, and transmission spectra of nanostructured glass at wavelengths of 300–1800 nm. Additionally, the work compares nanostructured glass to other key transparent solar concentrators. Based on the comparison, nanostructured glass has several promising features. Unlike luminescent solar concentrators (LSC), nanostructured glass has very stable properties, and its performance does not deteriorate over time. The manufacturing of devices is also inexpensive, as no materials other than glass are needed for production, and adding laser processing to current building glass manufacturing processes does not cause major difficulties. Furthermore, nanostructured glass is non-flammable, which is important for materials used in construction. However, the measurement results of this study show that the implementation of nanostructured glass also involves significant challenges. The device's absorption spectrum, on which the device's efficiency depends, decreases very rapidly as the laser power used to process the glass decreases. On the other hand, the transmittance of glass manufactured with higher laser power decreases, while the glass reflectance increases. In addition, nanostructures manufactured with higher laser power also make the glass hazy. It follows that the technology's biggest challenge is low efficiency, particularly compared to other similar technologies. Nanostructured glass has useful properties, but weak efficiency and haziness limit the technology's use in its current form.
  • Mobiilisovelluksilla toimiva valaistuksen ohjaus
    (2025-12-12) Roos, Jussi
    School of Electrical Engineering | Bachelor's thesis
    Lighting systems controlled by mobile applications are becoming increasingly common in day-to-day use due to the developing technology in the fields of lighting and internet of things (IoT). This bachelor’s thesis looks at lighting systems controlled by mobile applications, as well as how these systems can be applied to different settings such as homes and offices. The thesis focuses on protocols used in IoT systems such as Zig-Bee, Z-Wave, Thread, and Wi-Fi. The role of cloud services and bridges in a functional lighting system is also discussed. The thesis concludes that mobile-controlled lighting, with the existing technological solutions, is well-suited to small and medium sized sites. The complexity of added lighting fixtures and other devices is seen as the main challenge with the current technology.
  • Impact of coronal mass ejections on high frequency radio communication in high latitudes
    (2025-12-12) Kuusimäki, Myrsky
    School of Electrical Engineering | Bachelor's thesis
    This thesis examines the impact of coronal mass ejections (CME) and other solar activity– driven disturbances on the ionosphere and radio communication. High-latitude regions are particularly vulnerable to solar source disturbances, as the structure of Earth’s magnetic field directs charged particles toward the polar areas. For this reason, these regions must be treated separately from other latitudes. High-frequency (HF) radio communication relies on the ionosphere’s ability to reflect radio waves, and the properties of the ionosphere depend strongly on solar activity. Solar activity varies in an approximately 11-year solar cycle, and the occurrence of solar eruptions is linked to this cycle. Nevertheless, the majority of individual events cannot be predicted. CMEs can trigger geomagnetic storms that shape the ionospheric structure, causing significant disruptions to radio communication. This study analyzes an example event using ionospheric data from the Sodankylä Geophysical Observatory together with globally used geomagnetic indices. The St. Patrick’s Day geomagnetic superstorm of March 2015 serves as a case study of a global space-weather phenomenon driven by a CME, which produced wide disturbances in HF radio communication worldwide. The findings highlight the importance of real-time space-weather monitoring and advanced forecasting models in improving the reliability of HF radio communication, particularly for aviation, maritime, and communication systems in polar regions.
  • Reducing the impact of non-specific binding on biosensor performance
    (2025-12-12) Kalliola, Ella
    School of Electrical Engineering | Bachelor's thesis
    Biosensors have been developed for diagnostics and other medical applications for decades due to their many beneficial qualities such as cost-effectiveness, ease of use and high selectivity. Biosensors are used to detect disease biomarkers in blood in low concentrations. This allows for early diagnosis of diseases and real-time monitoring of disease evolution to enable more effective treatment. To achieve these goals, it is important for biosensors to reach low limits of detection (LOD) to be able to accurately sense low concentrations. A current critical bottleneck for reaching this goal in diagnostic biosensors is non-specific binding (NSB) due to the presence of a large amount of background molecules in biological samples. The aim of this thesis is to describe the negative impact that NSB has on the performance of a biosensor and present ways to reduce this impact. The thesis describes the basic function of biosensors and how their performance is evaluated. Ways to characterize NSB and differentiate it from desirable specific binding (SB) are presented. For this, the concept of affinity, the Langmuir Model of molecular adsorption and the energy landscape theory are used. The direct effect NSB has on the LOD is also explained. Based on these, methods for reducing the impact of NSB on the biosensor performance are presented. Force- and time-based discrimination between SB and NSB were found to be promising state of the art methods. In addition, referencing is an attractive method, but there are currently still challenges to its implementation. These methods still need further development but could potentially enable for biosensors to reach significantly lower LODs. Consequently, this could lead to much wider use of biosensors in diagnostic applications.
  • Datakeskusten rooli energiajärjestelmissä: Haasteet ja mahdollisuudet
    (2025-12-12) Sainio, Lauri
    School of Electrical Engineering | Bachelor's thesis
    Digitalisaation peruspalveluiden kehityksen myötä datakeskukset ovat nousseet keskeiseksi osaksi maailmanlaajuista digi-infrastruktuuria. Datakeskustalous kehittyy nopeasti, mikä näkyy niiden lisääntyvässä sähkönkulutuksessa. Tämän kandidaatintyön tavoitteena on tutkia datakeskusten roolia osana energiajärjestelmää, erityisesti sähköjärjestelmän ja hukkalämmön hyödyntämisen näkökulmasta. Tarkemmin työssä tarkastellaan datakeskusten teknistä rakennetta, niiden kuormituksen vaikutusta sähköverkkoon sekä mahdollisuuksia tuoda joustavuutta sähköjärjestelmälle. Lisäksi työssä tutkitaan uusiutuvan energian ja datakeskusten suhdetta sekä miten niiden synnyttämää hukkalämpöä voidaan hyödyntää. Suomen roolia analysoidaan myös kasvavan datakeskustalouden ohella. Työ pohjautuu aiheelle relevantteihin tieteellisiin artikkeleihin ja muuhun kirjallisuuteen. Tulosten perusteella voidaan todeta, että datakeskuksilla on merkittävästi mahdollisuuksia toimia energian kuluttajan rinnalla myös tuottajana energiajärjestelmässä. Tämä voi tapahtua joko joustojen tuomisella sähköverkolle tai hukkalämmön hyödyntämisellä eri prosesseissa, kuten kaukolämpöverkoissa. Uusiutuvan energian integrointi ja tehokas hukkalämmön hyötykäyttö on erittäin tärkeää, jos datakeskukset halutaan kestäväksi osaksi moderneja energiajärjestelmiä. Ratkaisut tähän tosin eroavat jokaisella datakeskuksella maantieteellisen sijainnin ja energiainfrastruktuurin mukaan, minkä takia aihetta on erityisen oleellista tutkia tulevaisuudessakin.
  • Risk-sensitive reinforcement learning — A survey of risk-sensitive reinforcement Llarning: Risk measures and representative algorithms
    (2025-12-12) Chea, Naryroat
    School of Electrical Engineering | Bachelor's thesis
    Reinforcement learning (RL) solves complex decision-making problems efficiently. However, this machine learning method has concerns related to risk and safety. Risk control in RL is more important than ever as the application is transitioning to practical domains. Fields such as healthcare and finance require a risk-sensitive approach to avoid negative outcomes. This literature review examines the incorporation of variance and Conditional Value-at-Risk (CVaR) into risk-sensitive objectives. We compare the respective algorithms of the two risk measures with baseline algorithms. In particular, we examine the optimization structure and workflow of the risk-sensitive algorithms, and analyze the performance against the risk-neutral algorithms. The empirical experiments under review exhibit that the selected algorithms successfully steer away from risk without notable decrease in return. The CVaR-based algorithms avoided tail-risk events while variance-based algorithms maintained low variability in returns. However, there are still open challenges concerning risk-sensitivity but this survey demonstrates that research is progressing well.
  • Process variation in Fin Field-Effect transistor technology
    (2025-12-12) Nenonen, Suvi
    School of Electrical Engineering | Bachelor's thesis
    The growing demand for computational power has led to an increase in the number of transistors in integrated circuits and as a result to their reduction. MOSFET transistors have been widely used in integrated circuits, but the ability to downsize MOSFET transistors poses challenges. To address these issues, a new type of three-dimensional FinFET transistors was developed. FinFET transistors enable smaller sizes and address the challenges of MOSFETs. In real applications, however, the FinFET transistor’s electrical properties vary as a result of process variations. The physical factors of´process variations include geometric differences and variations in transistors structure arising from the fabrication of transistors. The aim of the work is to provide a comprehensive overview of FinFET technology and its differences compared to traditional planar MOSFET transistors. The central theme of this work is the process variations arising from the physical factors of FinFET transistors and their effects on transistor performance. The work has been carried out as a literature review, complemented by a simulation section. In the examination of process variations, the line edge roughness of structures caused by manufacturing (LER), the metal gate granularity (MGG), and the variation of randomly implanted impurities in the transistor channel region (RDF) were emphasized. LER causes variations in the geometric dimensions of the transistor, which have significant effects on the transistor’s functional parameters such as on-current, leakage current, and threshold voltage. Variability in the work function caused by MGG results in threshold voltage differences between transistors. The study also revealed that RDF affects variations in the transistor’s threshold voltages. In the simulation section, a ring oscillator was simulated, and changes in the oscillation frequency as well as rise and fall times were examined at different process corners. The simulation section demonstrates that process variations affect circuit operation, and their manifestations are also supported by the literature review. Process variations in FinFET technology indeed cause variations in circuit operation, which is why it is essential to consider their impact in both device and circuit level design to ensure reliable and predictable performance.
  • Prostataspesifisen antigeenin havaitseminen hiilinanomateriaaleja hyödyntävillä sähkökemiallisilla aptameeriantureilla, joissa redox-reportteri on vapaana liuoksessa
    (2025-12-12) Neuvonen, Heta
    School of Electrical Engineering | Bachelor's thesis
    Tässä kandidaatintyössä käsitellään hiilinanomateriaaleja hyödyntäviä sähkökemiallisia aptameeriantureita, joissa redox-reportteri on vapaana liuoksessa, sekä niiden soveltamista prostataspesifisen antigeenin (PSA) havaitsemiseen. PSA on eturauhassyövän tärkein biomarkkeri. Aptameerien on havaittu olevan perinteisesti käytettyjä vasta-aineita parempia bioreseptorimolekyylejä. Hiilinanomateriaalit taas ovat hyvin sähköä johtavia ja omaavat suuren pinta-alan, minkä takia niiden käyttö elektrodin pinnalla osana nanokomposiittia vahvistaa anturin signaalia. Työn tavoitteena oli selvittää, millaisia edellä kuvatun kaltaisia aptameeriantureita PSA:n havaitsemiseen on kehitetty, ja miten niiden suorituskyky vertautuu perinteisiin PSA-testeihin ja testin kliinisiin vaatimuksiin. Työ on kirjallisuustutkimus, jonka tärkeimpänä aineistona on yksitoista artikkelia, joissa edellä kuvatun kaltainen aptameerianturi oli valmistettu PSA:n havaitsemiseen. Sähkökemiallisilla hiilinanomateriaaleja hyödyntävillä aptameeriantureilla, joissa redox-reportteri on vapaana liuoksessa, pystytään kirjallisuustutkimuksen perusteella mittaamaan prostataspesifisen antigeenin pitoisuutta näytteessä jopa perinteisesti kliinisessä käytössä olevia testejä herkemmin ja pienemmällä toteamisrajalla. Raportoidut anturit olivat myös hyvin selektiivisiä ja niiden toistettavuus, uusittavuus ja stabiilius olivat hyvällä tasolla. Joidenkin antureiden rakenne oli kuitenkin monimutkainen ja inkubointiaika turhan pitkä. PSA-aptameerianturit voisivat olla kohtuuhintaisia ja helppokäyttöisiä sekä mahdollistaa potilaan luona tapahtuvan vieritestauksen, minkä takia niillä on potentiaalia nousta myös kliiniseen käyttöön soveltuvaksi analyysimenetelmäksi.
  • Applications of smart thermal imaging in intelligent building systems
    (2025-12-13) Laine, Harri
    School of Electrical Engineering | Bachelor's thesis
    Infrared thermography is a highly useful technology with many applications such as occupancy detection, comfort analysis, energy optimization, and fault detection and diagnostics. Using the newest smart thermal cameras as a part of intelligent building sensor infrastructure, these buildings can experience many useful advancements. With the ability to analyze and compress data independently, these thermal sensors can further the goals of automation in the built environment. The necessity of these improvements is also clear, as there exists a great need for more comfortable and energy-efficient buildings, which will only increase as populations grow, and urbanization keeps escalating further. The research in this literature review combines both older and more recent sources to provide a holistic view of thermal imaging and its uses in buildings. This paper contains plenty of example use cases, well tested methods, and newer, more experimental ideas. Generally, the future of thermal imaging is promising, though there are some issues and technical challenges due to the recency of these smart thermal sensors. Especially since much of the data analysis part relies on recent AI developments, which, due to their black box nature, can cause problems when trying to understand these systems. Privacy and ethics are also significant concerns, as well as the reliability of untested automation systems. This, however, only means that there are many more research possibilities which are yet to be tackled.
  • Electrochemical aptasensors employing graphene and carbon nanotubes for medical diagnostics
    (2025-12-12) Nyman, Elsa
    School of Electrical Engineering | Bachelor's thesis
    Electrochemical aptamer-based (EAB) sensors represent a promising technology for the rapid and accurate detection of diverse biomolecules. These sensors translate target binding events into measurable electrical signals, enabling real-time monitoring and digital analysis of current or potential changes. Such properties make EAB sensors particularly suitable for portable diagnostic platforms and point-of-care testing, where analyses are performed near the patient. Aptamers, the recognition elements of these sensors, are short single-stranded nucleic acids engineered to bind specific target molecules with high selectivity. Their small size, strong binding affinity and thermal stability support dense and stable immobilization on electrode surfaces. However, aptamers also face limitations: their structure is sensitive to environmental conditions, and unmodified aptamers degrade readily in biological fluids. These factors can compromise their long-term stability and reliability in clinical use. This thesis presents a literature review on the use of graphene and carbon nanotubes (CNTs) as electrode materials in EAB sensors, examining sensor structure, operating principles and medical applications. Both graphene and CNTs provide excellent electrical conductivity and large surface area, enabling stable aptamer immobilization and enhancing signal output. Their nanostructures facilitate rapid electron transfer, contributing to lower detection limits and faster response times. When combined with metals or polymers, these carbon nanomaterials can further increase electrode stability, making measurements more resistant to background noise and long-term degradation. The focus of this work is on medical diagnostic applications, particularly the detection of antibiotics, cancer biomarkers, viruses and bacteria. Recent studies demonstrate that EAB sensors employing carbon nanomaterials can detect extremely low concentrations of target analytes and maintain reliable performance even in complex biological fluids. Furthermore, their compatibility with compact and portable device designs supports the growing demand for point-of-care diagnostic tools. Despite their significant potential, several challenges must still be addressed before large-scale clinical adoption is possible. Key issues include ensuring long-term operational stability, achieving controlled and reproducible aptamer immobilization, and minimizing nonspecific binding that can interfere with measurements. Strategies such as advanced surface modification, antifouling coatings and improved sensor architectures are being actively investigated to overcome these limitations. In conclusion, integrating graphene and CNTs into EAB sensor electrodes can substantially improve their analytical performance. Continued research in this field is likely to accelerate the development of faster, more reliable and more patient-centered diagnostic technologies.