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 Book Chapter Book Chapter Faculty Publications- Book Chapter 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 AI in Forensics A Data Analytics Perspective Description An account of the resource Artificial intelligence (AI) is rapidly becoming the most significant science in all areas of life, and forensic science is one of the fields benefiting from it. Forensics can be defined as a study of crime via the use of scientific methods and techniques. Around the globe, governments invest a large amount of money in developing forensics techniques to prove criminal activities and track criminals effectively. It is now becoming a practice to involve artificial intelligence in supporting the forensic application. It involves a smart and intelligent examination of massive volumes of very complicated data. As a result, AI is becoming an excellent solution for addressing many of the complicated issues that now exist in forensics. For example, AI proves more effective in skeleton-based human identification compared to the traditional skull/skeleton superimposition method. AI can be used to pool meta-data generated from multiple sources connected to forensic science and do a meta-analysis on it to simplify complex data. AI finds patterns and uses them to identify/recognize/predict something that is required in crime tracking or criminal/victim recognition. Complex analytics and probabilistic reasoning are used to recognize patterns. Among the most crucial things to forensic science is the identification of specific sorts of patterns in enormous amounts of data. This could include image pattern recognition, in which the program attempts to distinguish between distinct components of an image or a person. Other types of pattern recognition, such as finding patterns in text, may also exist. Artificial intelligence aids in the more accurate recognition of such patterns in complex data. This chapter introduces the reader to several aspects of artificial intelligence that can be used in forensics. 2024 selection and editorial matter, S. Vijayalakshmi, P. Durgadevi, Lija Jacob, Balamurugan Balusamy, and Parma Nand; individual chapters, the contributors. Creator An entity primarily responsible for making the resource Jacob L.; Thomas K.T.; Savithri M. Source A related resource from which the described resource is derived Artificial Intelligence for Cyber Defense and Smart Policing, pp. 41-60. Publisher An entity responsible for making the resource available CRC Press Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1201/9781003251781-4" target="_blank" rel="noreferrer noopener">https://doi.org/10.1201/9781003251781-4</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190200382&amp;doi=10.1201%2F9781003251781-4&amp;partnerID=40&amp;md5=34447409c53aefcf0d5cf795879736de" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190200382&amp;doi=10.1201%2f9781003251781-4&amp;partnerID=40&amp;md5=34447409c53aefcf0d5cf795879736de</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-100381553-2; 978-103217093-0 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 Book chapter Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Jacob L., Department of Data Science, Christ University, Pune, Lavasa, India; Thomas K.T., Department of Data Science, Christ University, Pune, Lavasa, India; Savithri M., Department of Data Science, Christ University, Pune, Lavasa, India