International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 10 Issue: 04 | Apr 2023
p-ISSN: 2395-0072
www.irjet.net
Women's Maltreatment Redressal System based on Machine Learning Techniques Hemanth adhi sekhar obulasetty, Preetha Sivakumar, Shalini L Student, Senior Assistant Professor, Vellore Institute of Technology, Vellore (Tamil Nadu), INDIA ---------------------------------------------------------------------***--------------------------------------------------------------------cleaning and feature selection to give the most accurate Abstract - A significant and expanding concern on a global
prediction. A centralized platform with all related information and services, as well as a forum for users, administrators, and government officials, is required. To address this issue, we developed our project.
scale is violence against women. Various issues like difference in maintenance, proper maintenance of records in different countries, even parts of a country are present in the current system. Through our project, we shall be addressing these issues by development of a portal to register and assign complaints according to the classification based on ML program. The main focus on the portal would be ease the communication between the involved victim and government officials. In addition to which, new features like real –time communication through WEBRTC protocol, victim services and SOS alert are included. We have extensively analyzed and classified the case based on the selected algorithm having highest accuracy namely deep feed forward algorithm. The implemented algorithm is the simplest form of artificial neural network having no loops and carries the data only in a single direction. Known as the multiple layer perceptron, it inputs enter the layer and are multiplied by the weights in this model comprising of multiple hidden layers which are summed together to form a total. With the accurate and immediate classification of the cases, the efficiency and execution will be immensely improved through the use of our application.
1.1 Methodology:
1. INTRODUCTION Misuse or violent behaviour is as old as humanity, but it takes many forms and levels as time passes. Women's violence, in particular, is a major issue that must be addressed. We discovered that there is no link between cases involving the same person in different regions, and that following up on details and the overall process is difficult for police authorities due to the lack of interconnection between different regions and communication between involved officials. People of different cultures, background and education levels even to illiteracy levels require some mode to register their complaint. With several cases being filed every day, knowing the priorities of the cases is essential. Assigning the importance of the case was employed using machine learning algorithms from classical approaches like K-nearest neighbours, support vector machine, decision trees, random forest and gradient boosting algorithms to deep feedforward neural network, a deep learning method. The model was intensively trained after data processing,
Impact Factor value: 8.226
Deep learning based classification of case records which is to assigned to the government officers
The project intends to create a universal portal as a friendly and convenient space for the victims to communicate and register their complaint and experiences officially. Upon proper authentication and sign up, the users would gain access to the resources like blood bank information, laws and policies up to date and global statistics in addition to SOS alert, tracking case and real-time communication through WebRTC. The main feature, registration, involves filing a form consisting of name of accuses, identification marks, details of incident and its location which can be either verbal or through video call. Depending on the severity of cases, it will be immediately assigned to a police officer of the concerned rank. All information stored (using Mysql) and maintained is secured and private to ensure no data is erroneously used and exploited.
Algorithms, WebRTC, Deep learning
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Web applications for complaint register and other services
2. Overview of Application
Key Words: Web application, Deep Feed Forward, ML
© 2023, IRJET
Government officials have a separate login gateway and with authentication would be given access to the homepage containing all case records. They also have the option to view victim’s details and laws and order information and export database of complaint records as a pdf. Their history of cases can also be seen inclusive of complaint, status and solved by. Video call option is given to communicate to those that feel more comfortable or unable to fill the digital form to file an official complaint. The admin gains to responsibility to store and maintain the database and portal with accurate information including the static records of global statistics, law and policies and blood bank. The admin insures the complaints are being accurately classified and solved immediately. Contact forms which may
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