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Academics and the health community are paying much attention to developing smart remote patient monitoring, sensors, and healthcare technology. For the analysis of medical scans, various studies integrate sophisticated deep learning strategies. A smart monitoring system is needed as a proactive diagnostic solution that may be employed in an epidemiological scenario such as COVID-19. Consequently, this work offers an intelligent medicare system that is an IoT-empowered, deep learning-based decision support system (DSS) for the automated detection and categorization of infectious diseases (COVID-19 and pneumothorax). The proposed DSS system was evaluated using three independent standard-based chest X-ray scans. The suggested DSS predictor has been used to identify and classify areas on whole X-ray scans with abnormalities thought to be attributable to COVID-19, reaching an identification and classification accuracy rate of 89.58% for normal images and 89.13% for COVID-19 and pneumothorax. With the suggested DSS system, a judgment depending on individual chest X-ray scans may be made in approximately 0.01 s. As a result, the DSS system described in this study can forecast at a pace of 95 frames per second (FPS) for both models, which is near to real-time.

Rapid advancements have been made in the field of artificial intelligence in recent years. This has resulted in its adoption in various technologies from medicine to search engines. Existing media management systems have however not yet fully leveraged the power of artificial intelligence (AI) to give users enhanced information apart from basic media metadata. This chapter proposes a smart movie management system which works majorly offline and uses AI to deliver optimum information to the users on four vital tasks. These tasks are multilevel phrase level review polarity, plot and review keywords, a content-based recommendation system, and an emotion recognition system. The complete system works in near-real time with a user-friendly presentation to maximize a user's information gain.

Mobile learning is the technology which makes many people around the world to learn by sitting at their home. So by considering the importance of the mobile learning the aim of this research is to build a system which makes the dumb people to learn and communicate with other people in the language which they know (hand sign language) and also the people who want to communicate with others without touching the keyboard or the mobile they can use their hand movements for such purpose. To achieve this, the research will implement the hand gesture recognition in mobile device which includes laptops, mobile phones, tablet pc. The methodology of this research involves the capturing video through camera, segmentation of the hand information from captured video, real time tracking and recognition of hand gesture, and store the gestures in database along with the text, when dumb people or the other people wants to communicate with each other the camera will capture their hand movements and match these movements in database, if match occurs then it will send the corresponding text to the people either in speech or text. If it does not match then the user can add this new gesture of the hand in database along with the text which will be enter by the user. This text will corresponds to the text form of that particular gesture of the hand.

We share the design for a simple apparatus that, when paired with an Arduino processor and a computer, can be used in a wide range of laboratory measurements: observing linear kinematics, confirming Faraday's and Lenz's laws, measuring magnetic moments, and observing the effects of eddy currents. The setup is simple, inexpensive, easy to replicate, and can even be fabricated and used by students working at home.

Our hospital management system in our project includes registering patients, storing information in the system and scheduling appointments with doctors. Our software has the ability to assign a unique ID to each patient and automatically store the details of each patient and staff. Users can search patient details using availability and doctor name. The hospital administration can be accessed with a username and password. It can be accessed by administrator or host. It can only add information to the database. Information is easily available. The interface is user friendly. Data is well protected for personal use and speed up data processing. There are mainly two modules. One at the Management level and the other for patient users and doctors. the program that validates the software for access. Administrative duties include managing physician information and patient information. To achieve this goal, a database has been created, one for patients and another for doctors that can be accessed by the administrator. Complaints filed by users will be answered by the authorities. The patient module includes appointments, prescription checks. Users can also pay doctor bills online.

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