Abstract-The cost of commuting to and from school is a burden for many people, especially in urban areas. While ride-hailing services are popular worldwide, most students face issues with accessibility and convenience. The aim of this work is to create and use fairShare. A web platform that allows students to connect and share rides, thereby reducing transportation costs and reducing the environment around them. Users can register, post trips,and compete with other students using the same route. Early tests of the platform have shown that it reduces student travel costs and provides a good user experience. The platform also promotes sustainable practices for students. fairShare demonstrates the potential of student-friendly carsharing to reduce transportation costs and improve social interaction. The platform has the ability to measure a broader and more effective way for students to take action.

Abstract-Employing generative adversarial networks, specifically with regard to cycle consistency loss and mask vectors, mainly concentrates on the colorization of Synthetic Aperture Radar (SAR). Most SAR imagery is devoid of chromatic information. Contemporary deep learning techniques are the predominant approach for SAR colorization. The methodology proposed herein employs a multidomain cycle-consistency generative adversarial network (MC-GAN). It enhances performance through the integration of a mask vector and cycle-consistency loss. The approach does not necessitate the availability of paired SAR-optical imagery. The multidomain classification loss contributes to the precision of the color output. The methodology has been evaluated using the SEN1-2 dataset for urban and terrain areas.

Abstract-This study focuses on the design and analysis of a hollow shaft for an EV go-kart, optimizing weight reduction and structural integrity. Using SolidWorks for design and ANSYS for Finite Element Analysis (FEA), the shaft’s performance under mechanical stresses and cyclic loads was evaluated. Results demonstrated significant weight savings while maintaining strength, rigidity, and durability, enhancing the go-kart’s efficiency and reliability. This work highlights the potential of hollow shafts in improving EV performance through lightweight design.

Abstract-The challenges of urban areas with ever-increasing traffic congestion, emergency response, and maintaining road safety are the basis of this paper. The ITMS proposed in this paper treats optimization of timings at the traffic signals based on real-time vehicle counts, along with the detection of emergency vehicles and accidents, as its prime mandate. To achieve these objectives of optimal traffic management, advanced technologies, such as sensor detectors, algorithms for processing data, and communicating networks, were adopted. With simulations and evaluations, the ITMS holds great promise in enhancing traffic flow efficiency as well as reducing congestion while shortening emergency vehicle response times vis-a-vis fixed-time signal control. The research performed here addresses the development of more sustainable and resilient urban transportation systems.

Abstract-Artificial Intelligence (AI) has become a pivotal technology for automating complex processes, while Soft Computing provides innovative ways to manage imprecise and uncertain data. By combining the two, hybrid systems leverage the strengths of AI’s precision and Soft Computing’s adaptability. This paper delves into the principles behind these hybrid models, emphasizing their use in healthcare, autonomous systems, finance, and smart cities. It also highlights the challenges of scalability and interpretability and outlines potential research directions, including integrating quantum computing and promoting explainable models.

Abstract-Chatbots function as software that enables users to ask questions and receive assistance through appropriate responses. This paper explores an AI-based chatbot designed to serve as an online ticketing system, streamlining the process of issue reporting, resolution, and user assistance across various domain. It also includes features like customer support, IT helpdesks, and event management. Natural language processing (NLP) is used by this proposed chatbot to understand user queries, categorize tickets, and provide instant responses. The aim of this chatbot is to enhance efficiency, reduce response times, and improve user satisfaction.

DOI: 10.61137/ijsret.vol.10.issue6.329
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