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Jitendra Kumar

Bio: Jitendra Kumar is an academic researcher from Amity University. The author has contributed to research in topics: Law enforcement. The author has an hindex of 1, co-authored 1 publications receiving 5 citations.

Papers
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Proceedings ArticleDOI
01 May 2017
TL;DR: The presented work provides an extremely efficient output of criminal hotspots in the state of Haryana which helps to explore the areas for raising the people's awareness regarding the dangerous locations and help police force for using their resources efficiently for the avoidance of criminal activities.
Abstract: In India, there is a strong need of Crime Surveillance system. In the current era, there are many traditional Hotspot analysis techniquesare used but still improvements are needed for getting efficient output as crime hotspot (area with high intensity of crimes). The strongest pillar of a perfect surveillance system is data related to different cognizable crimes. After collecting the data, the next step is transformation of data into meaningful information. This paper aims to throw light on the areas having high intensity of crimes that is spoiling an environment of particular places. Criminal hotspots are detected using statistical analysis tool (SaTScan) and visualize the result with the help of GIS (Google Earth) for pointing the location of district-wise crime hotspots. Hence, the presented work provides an extremely efficient output of criminal hotspots in the state of Haryana which helps to explore the areas for raising the people's awareness regarding the dangerous locations and help police force for using their resources efficiently for the avoidance of criminal activities.

9 citations


Cited by
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Proceedings ArticleDOI
23 Apr 2019
TL;DR: This system proposes to extract data from crime data record, on which it intend to perform clustering, and by using data live streaming the data are streamed according to the sources and the final end product could thus be a project where future predictions made by primary crime data sets, and the output is simple to understand to the user.
Abstract: Data mining is a technology accustomed solve model crime issues. Crimes are a social burden or nuisance and worth lots to our public in various ways. This can be approached by using clustering algorithm. K-means clustering is one such method is that advancement to support in the procedure of detecting crime patterns[1]. The dimension of this calculation is better-quality with ordinary two-level bunch techniques like Affinity Propagation (AP) and RBF system and Affinity Propagation (AP) utilizing abnormal state standpoint and RBF network[8]. Our system proposes to extract data from crime data record, on which we intend to perform clustering. Data is obtained and the data are clustered and by using data live streaming the data are are streamed according to the sources. The final end product could thus be a project where future predictions made by primary crime data sets, and the output is in order to be simple to understand to the user.

9 citations

Journal ArticleDOI
TL;DR: A novel geo-visualization method of dynamic spatiotemporal data that allows mobility and concentration of criminal activity to be study that contributes to a better situational awareness and improves the future projection, agility, efficiency and decision-making processes of police officers, which are all essential for fulfillment of police missions against crime.
Abstract: This work was co-funded by the European Commission as part of H2020 call SEC-12-FCT-2016-thrtopic3 under the project VICTORIA (No. 740754). This publication reflects the views only of the authors, and the Commission cannot be held responsible for any use which may be made of the information contained therein. The authors would like to thank Colombian National Police and its Office of Telematics for their support on development of this project.

5 citations

Proceedings ArticleDOI
01 Jan 2020
TL;DR: Regression analysis is conducted to identify the correlation of parameters associated with Rape to determine the significant variables which helps the police authorities in preventing crime more efficiently.
Abstract: Crime is an uncertain event and a social damage to the society. In India, Rape crime is an alarming concern for the police organization. The crime rate is escalating with increase in the residents of Haryana and impacting the community incurably in various aspects. Therefore, crime analysis becomes important for the better understanding of the factors which affects crime in both positive and negative way. This study conducted Regression analysis to identify the correlation of parameters associated with Rape to determine the significant variables which helps the police authorities in preventing crime more efficiently. The data related to the Rape crime is collected from the website of National Crime Record Bureau (NCRB). Then the Multiple Linear Regression Model is trained on the dataset. These results helps in gaining new insights for improving the strategies of crime prevention.

1 citations

Proceedings ArticleDOI
01 May 2019
TL;DR: This project focuses on a large scale approach on the problem that deals with ambiguity of real life scenarios and also additional features like pinpointing its location.
Abstract: SLAM(Simultaneous Localisation And Mobilisation) is a problem in robotics that revolves around the idea of a robot which can map a location by moving around in a sequential manner. Robot has to move and as well as recognize the path its traversing through by stitching the images into a map. Most models that have been created till now only focuses on small scale indoor applications and do not have a scope for real time usage outside an experimental area. Our project focuses on a large scale approach on the problem that deals with ambiguity of real life scenarios and also additional features like pinpointing its location. Neural networks is used for image processing and mapping and various robotics algorithms are used for the mobilisation of the robot.