Sitting Plan Identification

Project Title

Sitting Plan Identification

Project Area of Specialization Artificial IntelligenceProject Summary The results of study provide an initial understanding of the level of the public’s risk perception to reduce the spread of SARS-CoV-2. Findings also revealed the role of media use in determining risk perception, attitudes and subjective norms and, in turn, change people’s intention to socially distance. This study may add to the literature of behavioral changes in pandemic and provide a framework for both policymakers and practitioners to formulate effective interventions in the future. Project Objectives In  the era of COVID-19, social distancing has proven to be a very effective measure to slow down the spread of the disease. People are asked to limit their interactions with each other, reducing the chances of the virus being spread with physical or close contact. In past also Artificial Intelligence / Deep Learning has shown promising results on a number of daily life problems. In this proposed System, we will explain how we can use Python, to keep safe distance in a room of similar objects from each other by image processing in real time environment. Monitoring students at classroom we can integrate this tool to camera systems and can monitor whether objects are keeping a safe distance from each other or not.  Project Implementation Method Advancements in the current era of Computer Science where Artificial Intelligence and Machine learning tools are used, currently there is no such software to monitor student exams or class activity online. Our software will eliminate this deficiency. We will optimize our project through the rules and standards of Image Processing. Benefits of the Project We examine the net benefits of social distancing to slow the spread of COVID-19 in USA. Social distancing saves lives but imposes large costs on society due to reduced economic activity. We use epidemiological and economic forecasting to perform a rapid benefit–cost analysis of controlling the COVID-19 outbreak. Before coming of vancination social distancing is only way to control COVID-19.

          

           So we just go with this idea.

Technical Details of Final Deliverable

Explanation of a Module:-

1.Login/registration:-

The User Registration Form module of Ultimate Addons for Beaver Builder helps you to create and design the perfect user registration forms on your website. You also have the option of redirecting the user to Custom URL, auto-login, and sending an email after successful registration using this module.

2.Object detection-

Object detection is an important computer vision task used to detect instances of visual objects of certain classes (for example, humans, animals, cars, or buildings) in digital images such as photos or video frames.

      3.Distance Measurement:-

                                                 As their name suggests, distance sensors are used for determining the distance of an object from another object or obstacle without any physical contact involved (unlike a measuring tape, for example).

       4.Classifier training module:-

Classification is a process of categorizing a given set of data into classes, It can be performed on both structured or unstructured data. The process starts with predicting the class of given data points. The classes are often referred to as target, label or categories.

The classification predictive modeling is the task of approximating the mapping function from input variables to discrete output variables. The main goal is to identify which class/category the new data will fall into.

. Software Methodology:-

Pyhton, Yolo object detection with OpenCV (Image Processing) Pyhton, Flask / TensorFlow (Front End Web Application) Final Deliverable of the Project Software SystemCore Industry ITOther IndustriesCore Technology Artificial Intelligence(AI)Other TechnologiesSustainable Development Goals Partnerships to achieve the GoalRequired Resources