Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Machine Learning Based Crime Identification System using Data Analytics Subject The topic of the resource Convolutional Neural Network; Crime Identification; Data Analytics; Data mining; Deep Learning; Machine Learning; Support Vendor Machine Description An account of the resource Poverty is known to be the mother of all crimes, and a vast percentage of people in India live below the poverty line. In India, the crime rate is rapidly rising. The police officers must spend a significant amount of time and personnel to identify suspects and criminals using current crime investigation. In this research, the method presented for designing and implementing crime identification and criminal recognition systems for Indian metropolitans is utilizing techniques of data mining. These occurrences are represented by 35 predefined crime attributes. Access to the crime database is protected by safeguards. The pending four subjects are important for crime unmasking, identification and estimation of criminals, and crime authentication, in that order. The detection of crime is investigated with the help of K-Means clustering, which iteratively builds two crime batches based on congruent criminal features. Google Maps is to enhance the k-means visualization. K-Nearest Neighbor classification is used to examine criminal identification and forecasting. This is used for the authentication of the results. The technique benefits society by helping investigative authorities in crime solving and criminal recognition, resulting in lower crime rates. This research study describes a way for creating and deploying crime solving and criminal recognition systems for Indian metro's using data mining tools in this study. The method consists of data evulsion, data pre- processing, clustering, Google map delegation and classification. The first module, data evulsion, retrieves unformed or unrecorded crime datasets from several criminal sources online from 2000 to 2012. In the second module, Data pre-processing cleans, assimilates, and reduces the obtained criminal data into organized 5,038 crime occurrences. Several predefined criminal traits represent these instances. Safeguards are in place to prevent unauthorized access to the crime index. The remaining components are critical for detecting crimes, criminal identity and prediction, and crime verification, in that sequence. The investigation of crimes is investigated using k-means clustering, which gives results repeatedly. 2023 IEEE. Creator An entity primarily responsible for making the resource Rajesh S.M.; Chiranmai I.; Jayapandian N. Source A related resource from which the described resource is derived International Conference on Sustainable Communication Networks and Application, ICSCNA 2023 - Proceedings, pp. 951-956. Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICSCNA58489.2023.10370717" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICSCNA58489.2023.10370717</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85183008795&amp;doi=10.1109%2FICSCNA58489.2023.10370717&amp;partnerID=40&amp;md5=acba52f0395d9f598651777c03b261e6" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85183008795&amp;doi=10.1109%2fICSCNA58489.2023.10370717&amp;partnerID=40&amp;md5=acba52f0395d9f598651777c03b261e6</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835031398-7 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Rajesh S.M., Department of Cse, Christ (Deemed to Be University), India; Chiranmai I., Department of Cse, Christ (Deemed to Be University), India; Jayapandian N., Department of Cse, Christ (Deemed to Be University), India