Innovative Technologies Research Articles

INTEGRATING SOLAR POWER WITH EXISTING GRIDS: STRATEGIES, TECHNOLOGIES, AND CHALLENGES – A REVIEW

Integrating solar power into existing electrical grids is critical to realizing a sustainable and resilient global energy landscape. This review paper offers a thorough overview of solar power's significance and potential for transforming energy systems, emphasizing its benefits for grid stability, fossil fuel reduction, and environmental sustainability. It details essential strategies for successful solar integration, such as adopting both grid-tied and off-grid systems, advancements in energy storage to mitigate solar intermittency, and applying innovative grid technologies for enhanced energy management. Additionally, the paper navigates through the technological breakthroughs aiding solar power's incorporation into grids and confronts the challenges, including technical issues like grid scalability and economic barriers such as investment costs, regulatory complexities, and social-environmental impacts. Drawing on case studies from leading regions in solar integration, it distills lessons learned and identifies strategies and technologies that have surmounted these hurdles. The review also projects future trends and innovations in solar technology and grid management, underscoring the need for ongoing innovation and supportive policies to bolster solar power's role in energy systems. By collating insights into solar power integration's current state and prospects, this paper will guide policymakers, industry players, and researchers toward harnessing solar energy's full potential, highlighting its indispensable contribution to a sustainable energy future.

Exploring opportunities to strengthen rural tuberculosis health service delivery: a qualitative study with health workers in Tibet autonomous region, China

ObjectivesThis qualitative study aimed to explore opportunities to strengthen tuberculosis (TB) health service delivery from the perspectives of health workers providing TB care in Shigatse prefecture of Tibet Autonomous Region,...

Point-of-care testing: a critical analysis of the market and future trends

Point-of-care testing (POCT) involves conducting diagnostic tests outside the laboratory. These tests are utilized for their quick and reliable results in detecting chronic diseases and acute infections. We examined the historical market value trends of the POCT industry and projected its future growth. POCT devices offer several advantages, such as portability, no specific storage requirements, and simplicity of use. However, issues such as inaccurate results can reduce demand for POCT compared to traditional laboratory testing alternatives. While the benefits of POCT are clear, it’s important to acknowledge the challenges. The accuracy of POCT devices can be compromised due to factors such as user error, environmental conditions, and limitations in technology. Furthermore, the cost-effectiveness of these devices is often a concern, particularly in resource-limited settings. The regulatory landscape for POCT is also complex and varies by region, which can pose challenges for manufacturers and end-users. Improvements in POCT devices’ sensitivity, specificity, cost, and turnaround time for test results could enhance their utility. Enhancements to a POCT device should be considered if they are economically viable and lead to a significant increase in demand. Our financial analysis of the POCT market revealed a positive growth trend. We identified potential areas for growth that could help the industry progress and expand in line with its projected growth in the coming years. The industry could focus on integrating intelligent technologies into POCT devices and collaborating with the innovative technology sector to increase revenue. It could also develop more sensitive and accurate POCT devices for non-communicable diseases. Another potential area of growth is in diseases that require continuous patient monitoring but where conventional clinical testing is time-consuming. Enhancing the POCT devices used in these areas could revolutionize medical diagnosis and potentially save many lives, provided they meet clinical standards.

Voltage Optimization on Low Voltage Distribution Transformer Zones Using Batteries in Uganda

In the context of Uganda's rapidly growing energy demands and the need for sustainable solutions, this study explores the implementation of voltage optimization techniques in Low Voltage (LV) distribution transformer zones. The research focuses on the innovative integration of batteries to optimize voltage levels, thereby enhancing the efficiency and reliability of the electrical distribution system. By analyzing real-time data from various LV transformer zones in Uganda, this study investigates the impact of voltage fluctuations on the overall power distribution network. The research methodology involves the design and deployment of battery energy storage systems (BESS) strategically placed within LV distribution transformer zones. These BESS units are utilized to store excess energy during periods of low demand and release it during peak hours, ensuring consistent voltage levels and minimizing losses in the distribution network. The study evaluates the effectiveness of this approach through extensive simulations and on-site experiments, considering factors such as battery capacity, charging/discharging rates, and load variations. A comprehensive cost-benefit analysis is conducted to evaluate the potential financial savings and environmental impact associated with this sustainable energy solution. The findings of this research indicate significant improvements in voltage regulation, reduced system losses, and enhanced reliability in LV distribution transformer zones. Additionally, the study demonstrates the feasibility of integrating batteries into the existing infrastructure, thereby contributing to the optimization of the energy distribution system in Uganda. The outcomes of this research provide valuable insights for policymakers, utility companies, and researchers, emphasizing the importance of embracing innovative technologies to address the energy challenges faced by developing nations like Uganda.

Environmental stewardship in the oil and gas sector: Current practices and future directions

This paper provides an overview of the current practices and future directions in environmental stewardship within the oil and gas industry, focusing on key areas of concern and strategies for improvement. The oil and gas industry has made significant strides in environmental stewardship in recent years, driven by a combination of regulatory requirements, corporate initiatives, and stakeholder pressure. One of the primary areas of focus has been the reduction of greenhouse gas emissions associated with extraction, refining, and transportation processes. Companies have implemented technologies such as carbon capture and storage to minimize their carbon footprint, alongside investments in renewable energy sources and energy efficiency measures to transition towards cleaner energy alternatives. Furthermore, the industry has placed increasing emphasis on the responsible management of water resources, recognizing the potential environmental impacts of water extraction and usage in oil and gas operations. Strategies for water recycling, reuse, and wastewater treatment have been adopted to mitigate pollution and minimize strain on local ecosystems. Biodiversity conservation has also emerged as a critical aspect of environmental stewardship in the oil and gas sector, with companies undertaking environmental impact assessments and collaborating with conservation organizations to minimize habitat disruption and restore ecosystems affected by their operations. Community engagement and social responsibility are integral components of environmental stewardship, with companies seeking to address the social impacts of their operations through employment opportunities, infrastructure development, and social programs benefiting local communities. However, the industry continues to face challenges and limitations in its efforts to minimize environmental impact. Accidental spills, leaks, and other incidents pose significant ecological risks, highlighting the importance of stringent safety regulations and emergency response protocols. Moreover, the transition to renewable energy presents challenges for traditional oil and gas companies, requiring substantial capital investment and strategic planning. To address these challenges and advance environmental stewardship, several future directions are proposed. These include accelerating the transition to renewable energy, enhancing transparency and accountability in reporting environmental performance, strengthening environmental regulations and enforcement, investing in research and development of innovative technologies, and fostering collaboration among industry stakeholders, governments, NGOs, and local communities. Keywords: Stewardship, Oil, Gas, Sustainability, Climate, Mitigation

General characteristics of technologies, innovations in intellectual property law

In this work, we consider technologies, innovations and intellectual property rights. In the context of modern development of all spheres of human life, the concepts of «technology», «innovation» and «innovative technologies» are an integral aspect of the present. They play an important and key role in the competitiveness of not only individual enterprises and organizations, but also in law and economics in general, since innovative technologies are the basis for the positive development of society and the legal relations that arise in this regard, including legal relations in the field of intellectual property rights. Intellectual property is the result of intellectual and creative activity, which is formalized and grants the author or a person who is granted the right of ownership of the result by law, which is acquired, exercised and protected in accordance with the established procedure, rules and legally defined norms. It is the objects of intellectual property rights that are in clear interaction with technology and innovation. Detailed attention is paid to the essence and content of innovations and technologies in the field of intellectual activity, in particular in the production and change of characteristics of the relevant objects of intellectual property rights. The author focuses on the conceptual apparatus of such concepts as «innovation», «technology», «intellectual property», «intellectual property rights», and technology transfer. The modern national and foreign literature is analyzed with a view to defining the basic concepts of the study and their legislative consolidation. The author analyzes the features of technology transfer, in particular, it is established that innovative technologies are endowed with novelty, revolutionary nature, irreplaceability, uniqueness, and inevitability. The author establishes the interconnectedness of the content of «innovations» and «technologies» in relation to intellectual property rights, namely, directly to intellectual property objects, which are manifested by applying know-how or an invention to a specific result of intellectual activity in the production process.

Crop Yield Prediction using Machine Learning

Weather profoundly impacts agricultural outcomes, making accurate crop prediction vital for farmers' decision-making. This abstract presents a comprehensive overview of weather-based crop prediction, emphasizing its significance, key components, and methodologies. The process begins with the collection and analysis of historical weatherdata encompassing variables such as temperature, precipitation, humidity, and sunlight. Utilizing Python programming and data visualization libraries like Pandas and Matplotlib facilitates the exploration and visualization of this data, revealing trends and patterns. Machine learning algorithms, including regression and ensemble methods, are employedto develop predictive models. These models leverage historical weather data to forecast future crop yields accurately. Python's extensive libraries, such as Scikit-learn and TensorFlow, offer robust tools for model development and evaluation. Incorporating advanced technologies like remote sensing and satellite imagery further refines the prediction process. These tools provide real-time insights into crop health and growth, enhancing the precision of forecasts. Ultimately, weather-based crop prediction serves as a valuable decision support tool for farmers, enabling informed choices regarding planting, irrigation, and harvesting practices. By harnessing historical weather data, machine learning algorithms, and innovative technologies, stakeholders can optimize agricultural productivity, mitigate risks, and contribute to global food security

Digital biomarkers: 3PM approach revolutionizing chronic disease management — EPMA 2024 position

AbstractNon-communicable chronic diseases (NCDs) have become a major global health concern. They constitute the leading cause of disabilities, increased morbidity, mortality, and socio-economic disasters worldwide.Medical condition-specific digital biomarker (DB) panels have emerged as valuable tools to manage NCDs. DBs refer to the measurable and quantifiable physiological, behavioral, and environmental parameters collected for an individual through innovative digital health technologies, including wearables, smart devices, and medical sensors. By leveraging digital technologies, healthcare providers can gather real-time data and insights, enabling them to deliver more proactive and tailored interventions to individuals at risk and patients diagnosed with NCDs.Continuous monitoring of relevant health parameters through wearable devices or smartphone applications allows patients and clinicians to track the progression of NCDs in real time. With the introduction of digital biomarker monitoring (DBM), a new quality of primary and secondary healthcare is being offered with promising opportunities for health risk assessment and protection against health-to-disease transitions in vulnerable sub-populations. DBM enables healthcare providers to take the most cost-effective targeted preventive measures, to detect disease developments early, and to introduce personalized interventions. Consequently, they benefit the quality of life (QoL) of affected individuals, healthcare economy, and society at large.DBM is instrumental for the paradigm shift from reactive medical services to 3PM approach promoted by the European Association for Predictive, Preventive, and Personalized Medicine (EPMA) involving 3PM experts from 55 countries worldwide. This position manuscript consolidates multi-professional expertise in the area, demonstrating clinically relevant examples and providing the roadmap for implementing 3PM concepts facilitated through DBs.

Exploring FSO link performance in varied atmospheric conditions to optimize 5G communication with a polarized quasi-diffuse transmitter

Abstract Free space optical (FSO) communication is an innovative technology that holds immense promise for numerous applications thanks to its high data transmission rates, rapid scalability, cost-effectiveness, superior security, and comprehensive capacity access techniques for Gbps data transmission. FSO communication relies on the Earth’s atmosphere as the medium, which introduces atmospheric disturbances that have driven the development of spatial diversity techniques aimed at enhancing the technology’s performance. Our proposed system employs a polarized quasi-diffused system with a fork as a spatial diversity scheme, which eliminates the need for multiple transmitters. We have developed a model that integrates both simulation designs to achieve optimal results. The proposed model has demonstrated excellent performance under various atmospheric turbulences, including rain, fog, and haze, exhibiting a very high maximum quality factor, improved received power, and better bit error rate (BER). Finally, we have obtained, analyzed, and extensively discussed the simulation results to provide a comprehensive understanding of the proposed model’s potential benefits. Our simulations show a maximum quality factor of 23 compared to existing models in much better, a 34 % increase in received power, and a 31 % decrease in BER compared to existing models. These results highlight the potential benefits of the proposed model for FSO communication systems.

The Future of Agriculture in A Carbon Constrained World

In a world grappling with the far-reaching consequences of climate change and a growing imperative to lower emissions of greenhouse gases, agriculture’s potential finds itself at a critical juncture. This paper explores the intricate dynamics of agriculture in a carbon-constrained world, presenting a nuanced analysis of the multifaceted challenges and opportunities that lie ahead. With a focus on sustainable practices, carbon sequestration, and innovative technologies, this study elucidates the pathways through which agriculture can transition towards a low-carbon and climate-resilient future. From precision farming and agroforestry to advanced breeding techniques and digital agriculture, a spectrum of strategies emerges to mitigate the carbon footprint of agriculture while concurrently enhancing productivity and food security. Moreover, the paper underscores the indispensable role of policy frameworks, international cooperation, and public-private partnerships in ushering in a transformative era for agriculture that aligns harmoniously with global climate goals. This review explores carbon foot printing methodologies in agriculture and their implications for sustainable practices. Additionally, it highlights role of carbon foot printing in informing decision-makers, examines emerging trends like precision agriculture, and addresses associated challenges. This review identifies these gaps and offers recommendations for future research. In elucidating these key themes, this paper advances to a thorough comprehensive understanding of the imperative to embrace innovation and sustainability as guiding principles for the future of farming in a carbon-constrained world.

ProQuiz

ProQuiz is an app designed for educational purposes, specifically to help users prepare for multiple-choice exams, especially in the field of computer science. The app aims to make studying enjoyable by incorporating elements of gamification. The primary objective of ProQuiz is to assist users in getting ready for subjective tests used in admissions and recruitment processes, with a focus on the computer science domain. The app is organized into three main modules: computer science, reasoning, and analytical skills. Each of these modules covers various sub-categories to address different subjects. During the quiz, users have access to helpful features such as hints, the ability to skip questions, and a pause/life-lines option. These features can be used only once per user. The app also provides feedback on progress throughout the quiz, and upon completion, it displays the user's results. The overall aim is to provide users with an engaging platform for practicing and enhancing their knowledge in a variety of subjects related to computer science. This research paper examines the development and effectiveness of ProQuiz. Through user testing and analysis, we evaluate its usability and engagement. Additionally, we propose enhancements, including personalized learning paths and social features. This paper contributes insights into innovative educational technology and suggests avenues for future improvement of ProQuiz.

Application of artificial intelligence for the classification of the clinical outcome and therapy in patients with viral infections: The case of COVID-19.

With the end of the coronavirus disease 2019 (COVID-19) pandemic, it becomes intriguing to observe the impact of innovative digital technologies on the diagnosis and management of diseases, in order to improve clinical outcomes for patients. The research aims to enhance diagnostics, prediction, and personalized treatment for patients across three classes of clinical severity (mild, moderate, and severe). What sets this study apart is its innovative approach, wherein classification extends beyond mere disease presence, encompassing the classification of disease severity. This novel perspective lays the foundation for a crucial decision support system during patient triage. An artificial neural network, as a deep learning technique, enabled the development of a complex model based on the analysis of data collected during the process of diagnosing and treating 1000 patients at the Tešanj General Hospital, Bosnia and Herzegovina. The final model achieved a classification accuracy of 82.4% on the validation data set, which testifies to the successful application of the artificial neural network in the classification of clinical outcomes and therapy in patients infected with viral infections. The results obtained show that expert systems are valuable tools for decision support in healthcare in communities with limited resources and increased demands. The research has the potential to improve patient care for future epidemics and pandemics.

Therapies go digital. What drives physicians' acceptance?

National healthcare systems face multiple challenges, including the increasing demand for care and decreasing availability of healthcare professionals. Digital health technologies represent opportunities that offer improved efficiency, accessibility, and patient care. In this scenario, Digital Therapeutics are technological advancements to treat or alleviate a disease and deliver a medical intervention with evidence-based therapeutic impacts and regulatory approval. Digital Therapeutics are a paradigm shift for physicians, who exercise caution in terms of trust and wide usage. Digital Therapeutics represents an opportunity and a challenge in healthcare system integration. The research investigates the factors explaining physicians' acceptance of Digital Therapeutics. A research model that combines organizational mechanisms derived from Institutional Theory and rational factors derived from the Technology Acceptance model was developed. The model was tested through 107 responses from a survey distributed to the members of the leading Italian scientific society in Diabetology. Literature-based hypotheses were empirically tested through Structural Equation Modelling. The analysis confirmed the influence of Perceived Ease of Use on Perceived Usefulness and Perceived Usefulness on the Intention To Use Digital Therapeutics. Rules and norms impact Perceived Usefulness when considering the influence of the scientific society. Culture and mindset towards innovation within the hospital positively affect Perceived Ease of Use. The readiness of hospital facilities enhances the extent to which physicians perceive the ease of employing Digital Therapeutics in their daily practice. Instead, esteemed colleagues' opinions and guidelines from the scientific society reveal to physicians the value of Digital Therapeutics in patients' care pathways. Institutions should prioritize cultural, normative, and regulative aspects to accelerate physicians' endorsement of Digital Therapeutics. Findings advance the theoretical knowledge around clinicians' adoption of innovative digital health technologies, unveiling the interaction between rational and institutional factors. The results highlight practical implications for healthcare institutions and Digital Therapeutics manufacturers willing to promote their adoption.

Artificial intelligence in dance education: Using immersive technologies for teaching dance skills

Artificial intelligence (AI) has led to a shift in modern dance education. Immersive technologies have become increasingly common worldwide, helping educators to improve the quality of dance pedagogy and increase the effectiveness of dance training. The article investigates the ways of using immersive technologies powered by artificial intelligence in dance education. The research explores the theoretical literature on dance education and the use of artificial intelligence in dance education and dance choreography. The scholars examine the impact of innovative technology solutions used in dance pedagogical practice on the development of dance skills in students. The study also discusses the functionality of interactive and multimedia dance teaching systems, including AI-powered virtual mentoring and cognitive simulations of human mind operations. The research analysed the use of virtual reality (VR), augmented reality (AR), and mixed reality (MR) in dance education. This research also focuses on mobile applications used for teaching modern dance. The proposed framework for dance education is based on digital technologies, which help to develop dance skills and improve teaching practices. The scholars conclude that the development and improvement of dance skills are possible only if a teacher combines virtual and real environments in everyday practices. The findings can be used by dance teachers, professional dancers, software developers, and researchers who examine the innovative practices and the application of artificial intelligence in dance education. The ecosystem model reframes thinking about approaches to dance education and can serve as the basis for further development of dance courses and dance style teaching modes.

AiWOM: Artificial Intelligence Word-of-Mouth. Conceptualizing Consumer-to-AI Communication

The advent of innovative technologies with installed artificial intelligence (AI) has raised the need to understand evolutive consumers’ behaviours. The dyadic communicative experience between consumers and technological artifacts with programmed social humanoid features shed the light on the emergence of an adaptative form of word-of-mouth (WOM) and that we label as “AI word-of-mouth” (aiWOM). We argue that there is a need for defining and investigating aiWOM as an emerging phenomenon which derive but diverge from WOM. Our conceptualization suggests that the communication interaction between consumers and AI technologies produce new consumers’ behaviors and psychological reactions.

Application of Digital Twin in Electric Vehicle Powertrain: A Review

Digital Twin (DT) is widely regarded as a highly promising technology with the potential to revolutionize various industries, making it a key trend in the Industry 4.0 era. In a cost-effective and risk-free setting, digital twins facilitate the interaction and merging of the physical and informational realms. The application of digital twins spans across different sectors, including aerospace, healthcare, smart manufacturing, and smart cities. As electric vehicles have experienced rapid growth, there is a growing demand for the development of innovative technologies. One potential area for digital twins application is within the automotive sector. The powertrain system of electric vehicles (EVs) consists of three parts, power source, power electronic system, and electric motor, which are considered as the core components of electric vehicles. The focus of this paper is to conduct a methodical review regarding the use of digital twins in the powertrain of electric vehicles (EVs). While reviewing the development of digital twin technology, its main application scenarios and its use in electric vehicle powertrains are analysed. Finally, the digital twins currently encounter several challenges that need to be addressed, and so the future development of their application to electric vehicles are summarized.

INNOVATIVE TECHNOLOGY FOR THE CONSTRUCTION OF A PYLON STATION OF THE METRO BASED ON THE EXPERIENCE OF USING NATM

Purpose. For quite a long time, the metro station of the pylon type of deep contour interval was considered an underground structure that no longer has development potential. However, after the introduction of innovative technologies during the construction of the Dnipro metro, in particular the New Austrian Tunneling Method (NATM), this design is being used again and has developed further use. The purpose of the scientific article is to analyze innovations in the technology of construction of a three-vaulted pylon metro station from precast reinforced concrete using NATM, which require scientific justification. Methodology. In order to achieve the goal, the traditional technology of constructing a deep contour interval pylon station was revised. An analysis of the features of NATM, which allow it to be used during the construction of a pylon station in strong rock, has been carried out. A step-by-step analysis of the construction of the station was implemented with the involvement of mathematical modeling based on the finite element method. For this purpose, a number of finite-element models of each stage of construction of a pylon-type station have been created. After the numerical analysis, the indicated models were adjusted in accordance with the changes associated with the new construction technology. Findings. The value of the stress-strain state of the pylon station was obtained during the numerical analysis of each stage of construction. Stress analysis proves the possibility of applying innovative construction technology in the case of a pylon station. Originality. On the basis of the performed numerical analysis of the phased construction of a pylon station based on NATM, dependencies were obtained that allow revising the existing concept of the construction of this type of station in strong rocks. The obtained data justify the application of NATM and release the potential of the analyzed underground structure. Practical value. The substantiation of the innovative technology based on NATM allows expanding the scope of its application and successfully carrying out the construction of such complex underground facilities.

Thermal-hydraulic and structural analyses of an additive manufactured panel mock-up for Wendelstein7-X

After the successful short pulse operation phase 1 (OP1) of the stellarator Wendelstein 7-X with maximal plasma energies of 200 MJ, the upcoming long pulse OP2 aims at stepwise higher energies up to 18 GJ. A series of the stainless steel wall protection panels is positioned behind the divertor pumping gaps for average stationary heat loads of 100 kW/m². These panels were produced by electron beam welding of stainless steel parts to build the housing of the cooling channels. This technology was more demanding than foreseen due the complicated 3D weld seams required by the shaping of the panels. An innovative technology which is more adapted to the panel geometry is additive manufacturing. It intends to bring significant advantages by printing the housing as a single piece without welds.The paper introduces the thermal-hydraulic and structural analyses of an additive manufactured panel mock-up performed with ANSYS V2022R2. The purpose of the calculation is to compare the thermal, hydraulic and structural performance of the improved design based on additive manufacturing and the present one. The welding process dictated the design of the cooling channel that induced local recirculation areas, additional local pressure drops, non well cooled areas for weld seams integration. In addition the weld strength assessment required special codes and methods, which cost more time and efforts. Without these constraints, additive manufacturing offers the opportunity of more freedom for the design of the cooling channel to reach better heat transfer performance of the panel.

DEVELOPMENT OF INNOVATIVE TECHNOLOGIES IN CONSTRUCTION AND CIVIL ENGINEERING IN THE CONTEXT OF DIGITALIZATION OF THE UKRAINIAN ECONOMY

Purpose. Construction and civil engineering, traditionally perceived as conservative industries, also feel the need to adapt to the demands of the time and introduce innovative technologies. Ukraine, entering the era of digital transformation, is actively developing and implementing new technologies in the construction industry. Therefore, systematization and coverage of key aspects of the impact of digital Transformation into the construction industry and civil engineering in Ukraine is the main task today. Methodology. The introduction of Internet of Things technologies in the construction industry expands the possibilities of building control and management. Findings. Sensors located in different parts of the structures allow you to monitor the condition of the building in real time, identify possible problems and ensure the safety of objects. Artificial intelligence is becoming an integral part of the digital transformation of construction. Machine learning algorithms help predict and optimize construction processes, which increases Efficiency of planning and resource management. The 3D printing system in construction is one of the promising and revolutionary innovations that is already influencing traditional approaches to construction processes. This digital technique will bring significant changes to the field of construction, accelerating and optimizing a number of stages from design to execution Originality. Analysis of current problems, especially now, in the difficult times of war, industrial construction in Ukraine, as well as around the world, is a promising direction for the development of other industries in general. Industrial construction is an important branch of the construction industry that specializes in the creation and operation of buildings and infrastructure facilities for industrial needs. Practical value. The introduction of innovative technologies in construction and civil engineering in the context of digitalization of the Ukrainian economy has a significant practical impact on various aspects of the industry: Improving Construction Productivity and Quality: Use of digital technologies such as the Internet of Things (IoT), artificial intelligence (AI), virtual reality (VR) and augmented reality (AR), allows you to increase the efficiency of construction processes, reduce the time of work and avoid errors; Cost optimization: Using machine learning algorithms to predict resource needs, such as materials and labor, allows you to rationalize costs and reduce construction costs.

Automated detection and tracking of photovoltaic modules from 3D remote sensing data

This study addresses the growing demand for increased performance and reliability of photovoltaic (PV) installations by developing innovative monitoring technologies. The strategy consists of flying an unmanned aerial vehicle (UAV) equipped with a dual camera (RGB and thermal) over the PV plant of interest, followed by the generation of photogrammetric 3D models derived from the overlapped aerial images. The resulting datasets involve orthoimages and point clouds by processing RGB and thermal imagery. The key contribution of this study is twofold: (1) the thermal image mapping on dense and high-resolution point clouds that represent the status and geometry of PV solar modules, and (2) the automatic identification of individual solar panels in 3D space and their thermal characterization along their oriented surface. Then, the vector layer of each PV panel is projected onto the 3D thermal point cloud to extract the thermal values associated with each panel. To evaluate the capability of the proposed method, it was replicated in different scenarios, considering rural and urban environments with different light conditions and PV structures. The results demonstrate the robustness of our method, which achieves a remarkably high detection rate, around 99.12% of true positives, and a low false positive rate, close to 0.88%. Consequently, this method means an advance over previous work by proposing a comprehensive and automated solution for individual and highly detailed monitoring of each solar panel from 3D remotely sensed data. This study opens up new frontier research related to real-time monitoring of photovoltaic modules, an inspection of solar photovoltaic cells, the simulation of solar resources and forecasting, the development of digital twins, solar radiation modelling, and analysis of modular floating solar farms under wave motion.