Social Distancing Monitoring and Contact Tracing on CCTV Footage

Social distancing is one of the most effective measures to prevent the spread of the COVID-19 disease. Most methods of enforcing this in the Philippines resort to manual methods. As such, a video-based social distancing monitoring tool can help ensure constant enforcement of social distancing due to the availability and up-time of CCTV cameras in various areas. This can be achieved by using object detection and tracking techniques. Object detection can be used to detect people within an area, and tracking can be used to watch people who get into close contact with one another. Contact tracing can also be performed by processing the social distancing measurements and tracking information. This information can be stored to keep a record of who has a high risk of infection based on who they came into contact with and for how long. We introduce a social distancing monitoring and contact tracing framework using the EfficientDet object detector and DeepSORT tracker. This framework is used to monitor social distancing violations and keep a record of violations associated to the tracked people. © 2022 IEEE.

Facial Recognition-Based Attendance and Smart COVID-19 Norms Monitor

Attendance is an important part of the academic environment. The manual method of marking student attendance is time-consuming and also not accurate. So, the use of biometric attendance is a better alternative to the manual method. There are many biometric techniques that can be considered to design an automated system to mark attendance. Facial recognition is one such biometric technique that can be used. In this paper, we propose the implementation of facial recognition where the attendance is marked by recognizing the faces detected in the video feed from the classroom. We are in the midst of the once in a century crisis, ever since the COVID-19 pandemic broke out it has become imperative to accommodate certain behavioral changes in our day to day lives, one such major change which is essential to curb the spread of COVID-19 is to wear a face mask, and thus, the facial recognition-based attendance adds another advantage by recognizing the faces even though students would be wearing the masks. Another important measure that needs to be followed to contain the spread of COVID-19 is to ensure social distancing in all public spaces;hence, there is a need to ensure that social distancing norms are followed by the students. So, we propose implementation of a system to monitor the social distancing among the students. Further, we propose to implement a COVID-19 vaccination status monitoring system using which we can monitor the vaccination status of the individuals through the video feed from the classroom. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

AI Techniques: Combating COVID-19 Pandemic

With COVID-19, more than millions of people from all over the world got infected due to this pandemic disease, has wrought havoc. Due to delay in detection of presence of COVID-19 in human body, it infected large number of people all around the globe. Besides all the available manual methods, Artificial Intelligence (AI) and Machine Learning (ML) can help in detecting, treating and monitoring the sternness of COVID-19. This paper intends to provide a complete overview of the role of AI and ML as one important tool for COVID-19 and associated epidemic screening, prediction, forecasting, contact tracing, and therapeutic development. AI is a game-changer in terms of disease diagnosis speed and accuracy. It's a promising technique for a fully transparent and autonomous monitoring system that can follow and cure patients remotely without transmitting the infection to others. AI Application areas in the field of health care are also identified. This paper examines the role of AI in combating the COVID-19 epidemic. We attempt to present a medical network architecture based on AI. The architecture employs artificial intelligence (AI) to efficiently and effectively carry out patient monitoring, diagnosis, and their cure. © 2022 IEEE.

A Deep Learning Framework for the Classification of Lung Diseases Using Chest X-Ray Images

Automated screening and classification of various lesions in medical images can assist clinicians in the treatment and management of many systemic and localized diseases. Manual inspection of medical images is often expensive and time-consuming. Automatic image-analysis employing computers can alleviate the difficulties of manual methods for screening a large amount of generated images. Inspired by the great success of deep learning, we propose a diagnostic system that can classify various lung diseases from chest X-ray images. In this work, chest X-ray images are applied to a deep-learning algorithm for classifying images into pneumothorax, viral pneumonia, COVID-19 pneumonia and healthy cases. The proposed system is trained with a set of 4731 chest X-ray images, and obtained an overall classification accuracy of 99% in images taken from two publicly available data sets. The promising results demonstrate the proposed system’s effectiveness as a diagnostic tool to assist health care professionals for categorizing images in any of the four classes. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Meter Reading using OCR for Comfort and Cost Optimization

Meter reading and billing are time-consuming activities for power, water and gas providing boards. The existing billing system relies on a manual method of taking meter readings, updating the reading in the server and finally generating the bill amount. In this project, the user simply needs to use an Android application to capture and upload the picture of the meter after performing OCR operation. The processing on the image is performed on the server side using Google Colab and Python. The meter reading obtained from OCR processing is sent to the firebase, which is further pushed to the Android application. And finally the Android application displays the meter reading and the bill amount generated. Our project ensures the safety (from communicable diseases like COVID-19) of both the board staff and the customer as they don't come in contact with each other. This project also helps in cutting down on their expenditure by reducing manpower and travel costs. © 2021 IEEE.