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The main goal of control theory is input tracking or system stabilization. Different feedback-
computed controlled systems exist in this area, from deterministic to soft methods. Some examples of
deterministic methods are Proportional (P), Proportional Integral (PI), Proportional Derivative (PD),
Proportional Integral Derivative (PID), Linear Quadr...
Citations
... This library effectively fills a notable void in the realm of open-source resources by seamlessly incorporating these capabilities within a Python-based framework. (Montes Rivera et al., 2023a, 2023b. ...
Brakes are essential for vehicle safety, acting as the primary protection on the road. A malfunction can cause accidents, highlighting the importance of regular checks for issues like unusual noises, abnormal movements, slow response, and warning lights. Often, drivers may not link these symptoms to brake problems, delaying necessary checks. However, identifying these issues as brake-related allows for immediate action. This paper proposes a Fuzzy-Bayesian expert system to aid drivers in maintaining car brakes. This system combines fuzzy logic and Bayesian reasoning to manage uncertainty and make informed decisions. It utilizes UPAFuzzySystems for fuzzy rule description and Twilio for SMS integration, enabling drivers to access brake system information via mobile. Our Python-based tool aims to revolutionize brake system diagnostics and maintenance, ensuring enhanced safety through timely and effective decision-making.
Cycling is a popular recreational activity and mode of transportation that offers numerous health benefits and environmental advantages. Individuals of all skill levels can benefit from cycling, from beginners to seasoned professionals. However, as with any sport or activity, cyclists face inherent risks and challenges, ranging from safety concerns to performance optimization. Maintenance and mechanical fixing are standard activities in cyclists but could become so complex if it is the first time the user will perform them. Moreover, they could also be dangerous for professional or amateur users. However, it could be easier to fix mechanical issues in bikes if the user has the tools information, the repair instructions, and the probability of fixing the problem so that the user better let an expert fix it. Alternatively, Expert systems have exhibited skills assisting in different science fields, allowing users to query knowledge with forward and backward chaining to obtain information and answers to diagnose a problem and how to solve it. Additionally, Bayesian theory and fuzzy logic allow working with conditional probabilities and imprecise knowledge in expert systems. In this research, we propose a Fuzzy-Bayesian expert system that helps amateur and professional cyclists diagnose and decide whether to fix the issue themselves or search for an expert. Our proposal, developed in Python, uses UPAFuzzySystems to describe fuzzy rules and Twilio to allow SMS communication to send the report to the user, enabling him to maintain the information at hand while repairing the bike.
Brakes, one of a vehicle’s most crucial safety systems, are necessary to ensure safety. They are our primary protection mechanism while driving a car on the road. A brake failure can end up causing an accident and putting lives at risk, which is why it is essential to check all its elements periodically. The car must go to service in case of brake issues: unusual noises, abnormal movements or sensations, inability to stop quickly, and warning lights. Sometimes, drivers do not associate them with brake failure and wait to take the car to check service. However, if they could determine that an issue relates to brake problems, they could immediately seek assistance. State of the art shows that expert systems and domain expertise revolutionize maintenance, reshaping diagnostics, decision-making, and predictive strategies by blending advanced AI techniques, data analysis, and real-time monitoring. On the one hand, fuzzy logic is a branch of artificial intelligence and mathematics used to model and manage uncertainty and imprecision in data and expert systems. On the other hand, Bayesian reasoning allows determining beliefs about a hypothesis based on facts. In this work, we propose developing a Fuzzy-Bayesian expert system for assisting the drivers in the maintenance of car brake systems encompassing goal setting, knowledge acquisition, interface design, and testing. Our proposal, programmed in Python, uses UPAFuzzySystems to describe fuzzy rules and Twilio to allow SMS integration in a user interface, empowering users to make informed brake system decisions from their mobile and obtain information about the status of their vehicle’s brake system.
