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This medical technological advance is based on artificial intelligence to regulate the heat distribution of patients during surgical procedures These new methods increase the patient's comfort and regulate his temperature during surgery. Currently, proper maintenance of the patient's temperature during medical procedures requires the development of the following intelligent systems. This project addresses this problem through the use of artificial intelligence for thermoregulation, a distribution that provides precise organizational solutions to increase patient comfort. The goal is to innovate and test Thermoregulation systems based on artificial intelligence. This process includes the integration of sensors, the use of artificial intelligence and Artificial intelligence algorithms for data analysis and the use of actuators to control the patient's prosthesis. Anna. The main purpose of the method is to improve the patient's temperature control during surgery, which helps to optimize medical treatment. The result. The method involves the addition of sensors for instant temperature monitoring, data collection, artificial temperature formulation, intelligence algorithms, starting the engine, creating feedback loops and developing an intuitive and comprehensive interface Testing and verification. In summary, adopting AI-based thermoregulation systems looks promising in improving healthcare outcomes. Through an intelligent combination of sensors, AI algorithms, and actuators, the system is designed to provide an advanced and customizable approach to temperature regulation, ensuring a more comfortable and controlled environment for patients receiving medical care. Continuous experimentation, improvement and continuous collaboration with healthcare professionals will be key to realizing the full potential of this innovative medical solution. [ABSTRACT FROM AUTHOR]

A Chatbot is an artificial intelligence-based software system that imitates human communication with Artificial Intelligence. It is formulated to be the eventual personal assistant for amusement, assisting with tasks like respond to queries, obtaining driving instructions, augmenting the sensors in a smart house and playing preferred music among others. Chatbots are becoming increasingly common among companies due to their ability to minimize consumer care costs and manage various users at once. However, to perform these many tasks we need the chatbot to be as efficient as possible. To provide a solution to this, we develop Chatbot incorporated with Artificial Intelligence Markup Language (AIML) and Latent Semantic Analysis (LSA). AIML is utilized to response for standard and common queries namely, such welcoming and greetings. Although LSA can be used to answer at any time for service-related questions, ensuring user satisfaction. Any college (or) academy may utilize this chatbot to answer the questions. Due to the advent of deep learning technology, this study provides research opportunity in Chatbots. [ABSTRACT FROM AUTHOR]

A lot many indoor localization and mapping process has been introduced during the modern computing era, however the localization techniques has been applied in Artificial intelligence since few years in different environments as a robotic services,. The comparative study on various indoor localization algorithms like Dead Reckoning and smart SLAM are examined and data collection process with various sensors on smart devices and robots are examined for future POS Model building with effective customer services at the huge Shopping malls and predictions for the customer based on his history. Machine learning algorithms implementation into POS(Point of sale) at Large Shopping mall will help the users in identifying and pointing needed product will make the POS system faster service to Customers. This makes the user assistance and sales process as quick as we like E-commerce applications. [ABSTRACT FROM AUTHOR]

The production efficiency is among the most important for the success of the companies. The more efficient production lines are in the companies, the more products with higher quantity and quality would come out of them. When Lean approach is applied even during the design and development phase of the assembly line, this will lead to less need for subsequent optimizations of this line when it is in serial production. And in this way time and money will be saved, i.e. cost will be minimized. The combination of Lean practices and Industry 4.0 technologies could be called Lean 4.0. The productivity would be even higher when using Lean 4.0. The main goal of this paper is to analyze how semi-automated automotive industry assembly line to be designed implementing Lean 4.0 approach. In order to achieve it, Lean analysis was performed for the elements of the most important KPI of the assembly lines – the overall equipment effectiveness. Based on it, Lean 4.0 technologies which would eliminate the negative impact over each element were selected. In the conclusion, few assembly line design recommendations for the automotive industry were given, such as incorporating smart sensors, adjustable actuators, internet connection, Internet of Things and Artificial Intelligence. [ABSTRACT FROM AUTHOR]