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Data analysis, prediction and visualization of crimes in India | |
Author | Thirnathi, Sricharan Yedu |
Call Number | AIT RSPR no.CS-23-03 |
Subject(s) | Crime forecasting--India--Data processing Crime prevention--India--Data processing |
Note | A research study submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Computer Science |
Publisher | Asian Institute of Technology |
Abstract | The goal of crime prediction is to reduce crime and criminal activity in society. This study focuses on analyzing data from 2001 to 2021 in order to track crime trends in India. This approach employs visualization and machine learning methods in analyzing crime that took place in India. India's heat map visualization is used to highlight particular crime kinds across all states. In India, there are so many crimes that in only one hour, 187 offenses of indian penal code, 443 offenses under special and local laws are committed. Each year , with the number of instances registering each increasing by 1.6%. According to the survey, India's high rate of illiteracy, high population density, and lack of employment prospects have contributed to the country's high crime rate. Criminal activity climbed from 383.5 per 100,000 people in 2018 to 385.5 in 2019. If preventive actions are implemented following thorough analysis and forecasting of crime data, these statistics can be decreased. Machine Learning models are trained and tested, as they may learn from their past experiences and advance on their own.Crime prediction is one of the most well-liked study fields where geography information is significant. Early detection of regions with a high risk of criminal activity can aid in the implementation of preventative measures. The main goal of crime analysis is to determine the likelihood that any accident will occur in the nation. The visualization dashboard prototypes were developed by Tableau Public software and presented to Mr. Sri Venkata Ramana, the state of Andhra Pradesh's deputy superintendent of police, and Mr. P. Krishna Kumar, the latter's subordinate, for their feedback. I worked to apply the prediction model in terms of Linear Regression and Random Forest algorithms and find the suitable models by conducting the evaluation of performance metrics from sklearn library in python. |
Year | 2023 |
Type | Research Study Project Report (RSPR) |
School | School of Engineering and Technology |
Department | Department of Information and Communications Technologies (DICT) |
Academic Program/FoS | Computer Science (CS) |
Chairperson(s) | Chutiporn Anutariya |
Examination Committee(s) | Vatcharaporn Esichaikul;Mozumder, Chitrini |
Scholarship Donor(s) | AIT Scholarships |
Degree | Research Studies Project Report (M. Eng.) - Asian Institute of Technology, 2023 |