SUSTUNI - SOFTWARE FOR SMART AND SUSTAINABLE DESIGN OF INDUSTRIAL ELECTRICAL CIRCUITS
The theme of this project is to develop software to facilitate and innovate the design of low-voltage industrial electrical circuits. The goal is to develop a program that makes projects more efficient in terms of time, accuracy, and sustainability, automating dimensions such as calculating conductor cross-sections, protections, single-line diagrams, and analyzing with AI at which points industrial electrical circuits can be more sustainable. The 2023 Electric Energy Yearbook of the Energy Research Company describes that electricity consumption increases 2% per year in Brazil, and industrial installations represent the largest part of the national electrical sector (36.2%). As stated in standard NBR 5410/2004, when developing an installation project, an electrical professional works with several processes, depending on several criteria and calculations to present a reliable electrical installation. Minimal errors in calculations can cause damage to equipment, conductors, and individuals present in the installation. Using software to model these circuits optimizes time and brings more confidence to the project. This work aims to differentiate itself in this field by filling in the gaps in existing solutions for the industry, providing support for Brazilian standards, automatically generating single-line diagrams and presenting suggestions for sustainability in the circuits. The program is developed in Python, based on NBR 5410/2004 and engineering works. The software developed allows the user to size different distribution boards, motors and circuits, calculating the cross-section of the conductors/electrical protections, a particular transformer, and generating a single-line diagram in CAD. The program also presents suggestions aimed at sustainability to reduce material/energy costs. Tests were carried out with electrical engineering companies and students in the technical area, where the software presented high precision and very positive feedback from the interviewees, and it can be said that the work achieved its objectives.
Low-Cost Nickel-based Catalyst for Electrocatalytic Splitting Of Ammonia Towards Clean Hydrogen Production
Increasing energy needs alongside the urgent issues of chemical pollution has prompted the need for developing novel green energy sources. Nitrogen-based fertilizers are of fundamental importance for the ecosystem as their usage has increased eight times in the last fifty years [1]. On the other hand , increased use of nitrogenous fertilizers is followed by higher ammonia emissions, which are dangerous pollutants responsible for deterioration in biodiversity by means of eutrophication, acidification of soil and water, and climate change [2]. Ammonia has the2apacityy to bond with other pollutants including sulfur oxides and nitrogen oxides to create particles that cause smog, which is associated with lung disease. Ammonia also increases frost sensitivities and causes necrosis of many plant species [3.] Therefore, there is a need to properly manage the ammonia-rich nitrogen waste to decrease the environmental threat factors. Of the possible approaches suggested for ammonia waste treatment, the ammonia electro-oxidation reaction (eAOR) has various promising features for application in the energy sector. It is economically appealing because Ammonia can serve as an excellent hydrogen carrier due to its storage capabilities and existing transport infrastructure alongside having no net carbon emissions. Apart from this, it requires 95% less of the theoretical energy [4] to perform the process. But the reaction is kinetically slow [5], which has been a research obstacle during the development of (eAOR), due to factors ofmslow reaction rate and large catalytic overpotential that this process consumes an unnecessary amount of power [6]. Nickel-based catalysts are a promising solution to these problems, they are cheaper , more stable and easier to produce than electrocatalysts for water electrolysis which makes it highly energy efficient for widespread use on the industrial scale. N films deposited on the anodic side also allow the creation of N-containing products such as (NH42SO3) and nitrates, which can be converted into fertilizers or renewed into the nitrogen cycle to make the process more environmentally friendly while enhancing the (eAOR) process [7,8]. Compared to Pt and Ir which are the most used noble metals, they are less poisoned on the potentials less than 0.65V and are more stable [9,10]. However , noble metals are scarce, and their cost is high for industrial applications as well as the energy they waste during (eAOR) [11].
AI-Based Customer Sentiments Dashboard
In this fast-paced digital economy, customers' judgment is based on their experience with a company’s products and services. Customer reviews become a vital source of information for companies because this information can be used to enhance their products, understand customer wants and needs, improve brand reputation, and provide a competitor’s advantage. A company can understand customer needs and wants by going through reviews. Customers are encouraged to leave not only their opinion but also their ideas for the development of the product or service. By understanding these reviews, a company can actively respond and engage with a reviewer or problem. Failure of companies who don't answer customer queries may negatively impact customer loyalty. Customers will feel neglected by these companies and will choose competing companies to handle their needs. Additionally, customers may speak negatively about a company that does not respond to reviews. The AI-based customer sentiment dashboard can help gain a company's competitive advantage by identifying weaknesses in themselves and others. Companies will be enabled to understand where they succeed and where improvement is needed compared to their competitors, leveraging businesses to address strengths and weaknesses before competitors do. Through AI-based customer sentiment dashboards, a company can analyze its competitor’s reviews and use that information as leverage to make improvements to its products and services. Customers are increasingly leaving reviews on popular apps like Google Play, Stamped.io, Yapto, and Judge.me, Loox, Qualaroo, and Yelp. The reviews are rich in customer sentiments offering valuable insights into user satisfaction and pointing out the areas for improvement that are crucial to every company no matter how big or small. Despite their value, manually processing these reviews is a challenging task due to the large volume of unstructured data. Manual processing is also vulnerable to bias and human error, leading to inaccurate information. Traditional methods such as surveys have been proven to be ineffective if the main focus is targeted feedback and have low responses compared to reviews. The advances in artificial intelligence like Natural Language Processing (NLP) help us interpret and analyze human language and generate outputs like predicting what type of sentiments are in reviews. This project proposes developing an AI-based sentiment analysis model to evaluate customer feedback on two widely used taxi applications. Natural Language Processing libraries, such as the Valence Aware Dictionary and Sentiment Reasoner (. The model aims to categorize customer reviews into positive, negative, and neutral sentiments.
EIBraille: An Electromagnetic Field-Powered Braille Training Device with Development of Printed Circuits and Algorithms for Visually Impaired Individuals
Visual impairment ranks among the top three disabilities globally, with affected individuals projected to increase from 39 million in 2015 to 115 million by 2050. Despite this growing prevalence, over 95% of visually impaired individuals face difficulties in learning Braille (AFB, 2022). In Thailand, the issue is compounded by limited resources, with only 48 schools for the blind serving 6.5% of visually impaired children, alongside a shortage of trained teachers and prohibitively expensive Braille displays. To address these challenges, the EIBraille Box was developed as a cost-effective and accessible tool enabling visually impaired individuals to practice Braille independently. The device utilizes electromagnetic field generation based on Lenz's Law and electromagnetic induction, employing copper coils and varying currents to drive a Braille dot display mechanism controlled by a microcontroller. Results show the device achieves an average display rate of 30–120 milliseconds per cell and a Braille dot-changing frequency of 3–20 cycles per second. The production cost is reduced from 11,660 USD to 87 USD—over 130 times more affordable—while maintaining performance comparable to traditional mechanisms. Additionally, the device integrates with a web application aligned with the Ministry of Education's curriculum to enhance learning. The EIBraille Box is planned for deployment across 48 schools affiliated with the Northern School for the Blind. Plans include extending access to individuals unable to attend schools via alternative distribution channels. This project stores high capacity to achieve global reach by partnering with the World Blind Union, extending its services to rural areas and ensuring access for underprivileged communities. This effort seeks to promote literacy among the blind on a worldwide scale. This innovation strives to enhance equity for the visually impaired by enabling blind individuals to participate in inclusive educational environments alongside their peers. It aims to eradicate the challenges of illiteracy and ensure equitable access to quality education.
Project M.I.R.A.S
1.1 Short project summary My project involves the conceptualization and development of an innovative approach to modular self-assembling robotic systems. Through its ability to form any complex configuration, the system is highly adaptable to various scenarios and environments. Before delving deeper into the details of my project, I will provide an overview of my background and motivations. 1.2 Background Ever since I first watched the movie "Big Hero 6", I felt amazed by the applications of the so called “microbots”. From that point on, it made me always wonder what would be possible in the real world. When I did the research, I stumbled upon this field of modular robotics. Initially, I was unsure whether to embark on a project focused on electronics and robotics due to my background in programming. On the other side, this year gave me a chance to see the incredible performances of various projects at different science expos. Besides, I took part in the program of CANSAT LU and learned a lot during it, such as microchips, the control of miniature robotics, and the sensors of it. Finally, at school, I took the option Electronics where we dig into similar topics. With this accumulated knowledge and experience I felt confident enough to start this project.