IoT integrated COVID-19 SOPs Monitoring and Detection using Machine Learning

Project Title

IoT integrated COVID-19 SOPs Monitoring and Detection using Machine Learning

Project Area of Specialization Artificial IntelligenceProject Summary

In the pandemic of CPVID-19 the implementation of Standard Operating Procedures (SOPs) is a critical task. Many countries in the world use different methods to restrict movements and impellent the desired rules. The purpose of this project is to implement the SOPs using computer vision, IoT and machine learning. The problem is to check in a video (camera) whethe people in a gathering are following SOPs or not. Our goal is to detect the people in the video that are not following the main SOPs which are social distancing and face mask. Secondly we generate dataset to train the machine learning model to monitor every individual and detect only those who are not following SOPs like social distancing and face mask. The whole project is divided into parts. Firstly we detect those people who are on a very close distance from each other; secondly we detect the people who are not wearing the face mask by detecting the face first and then check for mask. Thirdly we detect those people who handshakes with each other. In this project we detect 2 meter distance between every person with respect to other individuals by using Neural Network (NN) to monitor crowd in different social places using surveillance cameras. Our goal is to make an efficient system by using artificial intelligence and image processing to ensure that every individual following SOPs or not

Project Objectives

1. Our objective is creating an efficient system that brings betterment in the field of computer vision that detects human activities for safety purpose.

 2. Goals of the project are to ensure that in every community, SOPs for COVID-19 are followed by people. This project is not only usable for SOPs, but can also be used for security purpose in social gathering places.

 4. Another important goal is to analyses crowed by using video processing with the help of surveillance security cameras.

Project Implementation Method

The setup assumes a crowded area like markets, hospitals, schools etc.  The distance between people, face mask and handshake are detected using camera. The system is first trained with different videos using machine learning. The model is then used for real time detection of violations. If two persons come closer than the distance of 2 meters, the system detects violations. similarly, handshaking is also considered as violation. If any person in the crowed in not using face mask, a violation is detected.

Benefits of the Project

The project can be useful in places where the organization needs to ensure SOPs implementation.   In addition to SOPs, detection the project can also be extended to other domains including security etc.

Technical Details of Final Deliverable

The tested system can be installed at any office or location where the videos of the monitored places are available. The system will detect any violations and generate alarm accordingly. Initially the system will be tested on recorded videos after which real time tests will be conducted.  

Final Deliverable of the Project HW/SW integrated systemCore Industry ITOther Industries Education , Medical Core Technology Artificial Intelligence(AI)Other Technologies Internet of Things (IoT)Sustainable Development Goals Good Health and Well-Being for PeopleRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	78600
HikVision IP Camera model DS-2CD2H85FWD-IZS	Equipment	1	46000	46000
HikVision Turbo HD DVR model DS-7104HQHI Channel DVR	Equipment	1	7500	7500
Copper Wire	Equipment	30	70	2100
Power Supply	Equipment	1	3000	3000
Print and Photocopy	Miscellaneous	500	10	5000
Binding	Miscellaneous	3	500	1500
Travelling	Miscellaneous	2	1250	2500
Circuit/components	Equipment	3	2000	6000
Hard Drive for storage	Equipment	1	5000	5000