CCTV Cameras Surveillance, Data Protection & Privacy Under International Human Rights Laws

The study aims to find out and suggest that how equilibrium among surveillance through CCTVs, right of privacy and personal data protection regime can be maintained. With the objective in mind, it discusses the CCTVs’ surveillance, its purposes, and scope of privacy in public or private domains under International Human Rights Law. It also focuses on General Data Protection Regulations, 2018 and its amplifications on CCTV surveillance.

SUSPICIOUS ACTIVITY DETECTION USING CCTV SURVEILLANCE VIDEO

Security has recently been given the highest priority with the rise in the number of antisocial activations taking place. To continuously track individuals and their interactions, CCTVs have been built in several ways. Every person is recorded on an image on average 30 times a day in a developed world with a community of 1.6 billion. The resolution of 710*570 captured at knitting will approximate 20 GB per day. Constant monitoring of human data makes it hard to judge whether the incident is an irregular one, and it is an almost uphill struggle when a population and its full support are needed. In this paper, we make a system for the detection of suspicious activity using CCTV surveillance video. There seems to be a need to demonstrate in which frame the behavior is located as well as which section of it allows the faster judgment of the suspicious activity is unusual. This is done by converting the video into frames and analyzing the persons and their activates from the processed frames. We have accepted wide support from Machine learning and Deep Learning Algorithms to make it possible. To automate that process, first, we need to build a training model using a large number of images (all possible images which describe features of suspicious activities) and a “Convolution Neural Network‟ using the Tensor Flow Python module. We can then upload any video into the application, and it will extract frames from the uploaded video and then that frame will be applied on a training model to predict its class such as suspicious or normal.

Automatic Detection of Crimes Captured in CCTV Images for Safety of Senior Citizens

Closed circuit television systems (CCTV) are getting widely popular and are being deployed in many workspaces, housing estates and in most public spaces. Efficiency of CCTV surveillance can be improved by incorporation of image processing and object detection algorithm into monitoring process. In this project, we specialize in the task of automated detection and recognition of dangerous incidents for CCTV systems. We propose solutions that are able to alert the human operator when a weapon is visible in the image through e-mail. We have shown that it's possible to make a system that's capable of an early warning during a dangerous situation, which can cause faster and more effective response times and reduce in the number of potential victims. Face Detection and Face recognition of individuals is an intricate problem which has garnered much attention during recent years because of its ever-increasing applications in numerous fields. In this project the facial detection has been carried out using Viola Jones algorithm.

COVID-19 Social Distance Violation and Face Mask Detection in Workplaces

Social distancing is a suggested arrangement by the World Health Organization (WHO) to limit the spread of COVID-19 in broad daylight places. Most of governments and public wellbeing specialists have set the 2-meter physical removing as a compulsory security measure in retail outlets, schools, and other covered regions. In this exploration, we foster a conventional Deep Neural Network-Based model for mechanized individuals’ identification, following, and between individuals’ distances assessment in the group, utilizing basic CCTV surveillance cameras. The proposed model incorporates a YOLOv4-based system and opposite viewpoint planning for exact individuals’ identification and social removing checking in testing conditions, including individual’s impediment, incomplete perceivability, and lighting varieties. We additionally give an online danger appraisal conspire by factual examination of the Spatio-transient information from the moving directions and the pace of social removing infringement. We distinguish high-hazard zones with the most noteworthy chance of infection spread and diseases. This may assist specialists with updating the design of a public spot or to play it safe activities to relieve high-hazard zones. The effectiveness of the proposed approach is assessed on the Oxford Town Center dataset, with prevalent execution as far as precision and speed contrasted with three bests in class techniques.

Face Mask Detection and Alert System

In today’s era, as we all know how the year 2020 has brought an alarming pandemic with it and day by day, we are reaching a new peak of COVID cases. And due to which a main contribution asked from all the citizens is to follow all the safety norms to soothe the condition. One of the norms states to wear facemask all the time immediately after stepping out of their home. This paper proposes one of the methods to ensure that at least all people coming under any Closed-Circuit Television (CCTV) surveillance wears masks and that too properly. In this system we are using locally linear embedding (LLE) algorithm for face detection and convolutional neural network (CNNs) to reconfigure the image to fit into the network. And the neural network is trained with the help of image dataset. The method attains training accuracy and validation accuracy up to 99.87% and 93.41% respectively on two different datasets. If the system found out a person with no mask or not wearing it properly an alarm buzz outs to alter.

Integrated CCTV Surveillance System for Public Transportation

The urban center residential district Railway is one in every of the busiest railway stations in Bharat and carries over seven.5 million commuters daily.The railways spreads over 123.78 km (76.91 mi).The Railways encompass thirty-nine stations.Trains typically begin from and terminate at necessary stations. in line with a survey ,the total stats given by the RPF(Railway Police Force) & GRP(GOVERNMENT RAILWAY POLICE), 2,700 railway commuters killed, over 1,400 whereas crossing tracks up until last and this variety has been increasing daily. This is creating railways a dangerous possibility for travel and transportation.The video closed-circuit television used is irving to be not useful and not updated.To overcome this drawback we tend to area unit creating associate integrated video closed-circuit television for detection of crimes and missed objects and explains during this paper.We area unit exploitation high resolution cameras which might focus and might be simply accustomed establish someone and can also be helpful in dark

Design of Detection System with Motion Sensor and Notification on Android Based on Arduino Microcontroller

The rapid development of technology nowadays makes people want to always be creative and triggers to create something that is needed to create a security system, because the difficulty of today's economy makes many people act criminally by robbery or theft. An alternative security system that is often used today is to use CCTV (Closed Circuit Television), but the limitations in conducting CCTV surveillance include that it still has to be monitored directly at the monitoring location. From the problems that occur, the authors developed a thesis that is capable of monitoring and monitoring by sending realtime alerts in the form of notifications to the user on an Android Smartphone device by building an IoT (Internet of Thing) based detection system using a PIR (Passive Infrared) motion sensor which entitled "Design of Detection System with Motion Sensor and Notification on Android Based on Arduino Microcontroller".