Revista Ingenieria Solidaria

Introduction: The smart city paradigm is made up of a set of actors who must operate jointly to guarantee road flow. However, sometimes there are accidents, and they affect productive apparatus, cause minor or temporary injuries and sometimes death of the individuals involved. Problem: Events occur for multiple reasons and the authorities have difficulties in implementing controls that minimize their occurrence since they do not have the necessary tools to capture and analyze timely information on the claims that have been presented. Objective: The objective is to increase road safety control and safeguard mobility in Bucaramanga. For this, a mobile application is designed to capture accident data by implementing the Flutter framework and the Model-View design pattern methodology. Controller (MVC). Methodology: The development of software to analyze the large amount of information on road events. A database is developed where said information is stored and processed using programming languages, coding and data hosting. Design and process factors are also considered according to the user’s needs, which will determine the interface and expected performance. Results: A structured system for data capture with the ability to integrate the general community, streamline the availability of information and facilitate decision making that deals with the problem in real time. Conclusion: It is concluded that its implementation in the city fosters self-care for pedestrians and drivers, facilitating the design of effective control measures by territorial entities, bringing the city of Bucaramanga closer to sustainability. Originality: This methodology for integrating events is unique in the country and is developed based on the city’s own characteristics. Limitations: The lack of information provided by the government actors.

Introduction: This paper describes the results of the exploratory research developed by the SciBas investigation group of Francisco José de Caldas Distrital University within the low power-Pico hydraulic Hydroelectric Generation Systems (0,5 Kw to 5Kw) framework, that uses the minimum water reservoirs or Ultra Low Head (ULH) or Very Low Head (VLH) - such as drainage channels – and provides energy to IoT devices or its applications. Problem: About 80% of the world’s population lives in places where energy depends on fossil fuels; thus, it is necessary to generate electric power with renewable sources. Nevertheless, Low Power Generation Systems are an under-researched field, so the applied experiences have not been categorized and documented enough. Objective: Formulate a baseline to provide a detailed understanding of the structure of Low Power Hydroelectric Systems (LPHS) and establish a perspective for future Colombian context research. Methodology: Construct conceptualizations, categorizations and sub-categorizations based on vertebrate diagrams oriented to conceptual maps that show documentary references included between the years 2019 and 2023. Results: A review of papers related to Hydroelectric Energy Generation was made, of which 30% consisted of research about LPHS and its advantages and disadvantages; 35% about the generators, batteries and converters that complement this kind of system; and, finally, IoT device applications and sensor networks comprise 35% of the investigation. Conclusion: It was established that, in addition to the fact that LPHS generation is propitious for IoT devices and its applications, the idea of designing and implementing systems that power sensors and devices through clean energy is an advantage over other forms of generation with resources that, although exhaustible, are easily found within the national geography and are therefore viable for their implementation in non-interconnected zones of the electric system. Originality: This research is made in drainage channels terms, confirming its unprecedented nature; as well as considering energizing of IoT sensors and sensors networks by LPHS. Limitations: The review is limited to academic records; therefore, a deepening fieldwork is required for local, regional and national experience documentation in order to expand the applied research baseline.

Introduction: Blockchain technology is one of the emerging technologies that implements the concept of decentralization. The first application of this technology was with Bitcoin, which is a decentralized application. However, the decentralization of Bitcoin has become problematic due to the formation of mining pools. In this work, decentralization is intended to be maximized. Problem: Decentralization is the main concept of blockchain technologies. However, decentralization suffers mainly from mining pools in the Bitcoin network. Objective: In this work, the proposed solution to maximize upon the decentralized nature of Bitcoin is to revise the consensus protocol of Bitcoin. The proposed novel consensus protocol called Signature Proof-of-Work uses signatures instead of hashes. The proposed method aims to minimize the number of mining pools and maximize the number of solo miners by arguing that no one can share their private keys with others, which would ensure greater decentralization of the network. Methodology: The consensus algorithm in Bitcoin is Proof-of-Work. Proof-of-Work allows for the formation of mining pools. Mining pools control the Bitcoin network and reduce decentralization. Therefore, a novel Proof-of-Work consensus algorithm is proposed to empower decentralization. Results: The proposed consensus algorithm called Signature Proof-of-Work uses signatures instead of hashes. The proposed method aims to minimize the number of mining pools and maximize the number of solo miners by arguing that no one can share their private keys with others, which would ensure greater decentralization of the network. Conclusion: The proposed consensus algorithm minimizes mining pools by enforcing non-shareable private keys. Originality: The proposed consensus algorithm is an enhancement of the default Proof-of-Work algorithm of Bitcoin. The proposed algorithm uses signatures instead of hashes, which differentiates it from the default algorithm. Limitations: In the proposed algorithm, the main argument is that no one shares their private keys. In other words, miners cannot share their private keys with others. If they share their private keys, others can control their own money. Therefore, each miner does not want to collaborate with other miners to mine new blocks. As a result, the mining pools will not be formed.

This article is the product of the research “Mathematics as a basis for the generation of cryptographic tools”, developed at the Universidad de Cundinamarca, sectional Ubaté in the year 2021. Problem: Improve the security of code with differential calculus, plane and spatial geometry, polar coordinates, and functions; the resulting encryption should improve on the standards of current encryption systems. Objective: Explain the algorithm’s operation with fundamental issues that use and generate a modification proposal to make the algorithm more robust when subjected to an attack by unethical hackers. Methodology: A bibliographic review, encryption codes, history of algorithms, and operation of SHA-256 in the Ethereum platform and Bitcoin explains how it works and gives an idea of how to improve security. Result: The algorithm’s operation is explained step by step using subject topics such as precalculus and calculus. Also, topics such as functions, truth tables, logical operators, programming functions, and a way to complicate the algorithm were proposed by applying issues of plane geometry, space, polar coordinates, ceiling function, and absolute values. Conclusion: It is possible to assimilate the operation of SHA-256 (256-bit secure hash algorithm) and the mathematical basis for generating codes in hexadecimal, depending on the message to be encrypted. Algebraic models allow taking different points of the figures generated in the Cartesian and polar planes to use them as a means of encryption. Originality: Explaining an algorithm widely used in encryption issues; however, according to a survey conducted, only a few understood the code that explains the mathematics, all the aspects behind its operation, and why it is so secure. In addition, the project proposes a way to improve its security. Limitations: The algorithm used was a hyperbolic and linear function combined. In this sense, common random points between the two functions are selected for encryption, and it is not aligned with the encryption systems used in blockchains; it is a restriction for the implementation. Currently, several updates are aligned with the SHA-256 system, involving limiting the inclusion of updated models.

Introduction: This article, developed between 2022 and 2023 within the framework of Applied Stochastic Processes by the SciBas group at the Universidad Distrital Francisco José de Caldas, focuses on the role of Hidden Markov Models (HMM) in predicting cardiovascular diseases. Problem: The addressed issue is the need to enhance the early detection of heart diseases, emphasizing how HMM can address uncertainty in clinical data and detect complex patterns. Objective: To evaluate the use of Hidden Markov Models (HMM) in the analysis of electrocardiograms (ECG) for the early detection of cardiovascular diseases. Methodology: The methodology comprises a literature review concerning the relationship between HMM and cardiovascular diseases, followed by the application of HMM to prevent heart attacks and address uncertainty in clinical data. Results: The findings indicate that HMM is effective in preventing heart diseases, yet its effectiveness is contingent upon data quality. These results are promising but not universally applicable. Conclusions: In summary, this study underscores the utility of HMM in early infarction detection and its statistical approach in medicine. It is emphasized that HMM is not infallible and should be complemented with other clinical options and assessment methods in real-world situations. Originality: This work stands out for its statistical and probabilistic approach in the application of Hidden Markov Models (HMM) in medical analysis, offering an innovative perspective and enhancing the understanding of their utility in the field of medicine. Limitations: It is recognized that there are limitations, such as dependence on data quality and variable applicability in clinical cases. These limitations should be considered in the context of their implementation in medical practice.