crime invetigation using big data analytic
- 1. Crime Investigation UMANG RAVAL - 21012011131 YASH PRAJAPATI - 21012011125 Class – CE-C3
- 2. Introduction to the Crime Investigation Overview Criminal investigations are systematic processes of gathering, analyzing, and interpreting evidence to solve crimes. Modern investigations integrate advanced technological tools, forensic techniques, and multidisciplinary approaches to reconstruct criminal activities and identify perpetrators. The process involves comprehensive evidence collection, rigorous analysis, and strategic methodological techniques to uncover truth and support legal proceedings. Goals • Identify the criminals responsible for the crime. • Uncover motives and methods used in the crime. • Leverage technology for efficient data analysis. • Ensure justice and prevent future crimes through insights gained.
- 3. Working Process of Crime Investigation 1 Data Collection • Gather diverse digital and physical evidence • Collect data from multiple sources • Ensure comprehensive and systematic evidence accumulation 2 Data Processing • Apply advanced analytical algorithms • Clean and organize collected data • Perform initial pattern identification 3 Evidence Analysis • Conduct deep forensic examination • Correlate data points and evidence • Identify potential connections and insights 4 Intelligence Generation • Transform analyzed data into actionable insights • Develop investigative reports • Support legal proceedings with empirical evidence
- 4. The 5V’s Characteristics of the Crime Investigation Volume The case generates large amounts of data, such as surveillance footage, phone records, and digital evidence, which must be managed and analyzed efficiently. Velocity Data needs to be processed quickly, enabling real-time analysis and fast decision- making during the investigation. Variety Different types of data, like structured records, unstructured witness statements, and multimedia evidence, are collected and analyzed. Value Big data provides valuable insights that help uncover hidden patterns and solve the case more effectively. Veracity Ensuring the data's reliability and authenticity is critical to avoid false conclusions or misleading evidence.
- 5. Data Collection and Pre-processing Sources of Data Collection Data is collected from various sources such as crime scene evidence, surveillance footage, digital records (e.g., phone and social media), and witness statements, combining both traditional and modern methods. Cleaning and Organizing Data Pre-processing involves removing irrelevant, duplicate, or noisy data, correcting errors, and organizing it into a consistent, structured format suitable for analysis. Data Integration Data from multiple sources is integrated, ensuring consistency and alignment between physical evidence and digital data (e.g., matching GPS data with crime locations). Ensuring Accuracy and Reliability Proper data pre-processing ensures that the analysis is based on accurate, error-free information, enabling investigators to draw reliable conclusions and make informed decisions.
- 6. Benefits of Big Data Analytics in Crime Investigation 1 Strategic Decision-Making Informed decisions regarding crime prevention, resource allocation, and law enforcement strategies. 2 Cost-Effectiveness Reducing the resources needed for manual investigation. 3 Improved Risk Management Preventing future crimes by using predictive models to identify threats. 4 Enhanced Efficiency Speeding up crime-solving by processing large datasets quickly.
- 7. Role of Big Data in Crime Investigation Data Integration How different types of data are integrated, such as criminal records, social media activity, and surveillance footage. Pattern Identification Using big data analytics to identify hidden patterns, such as linking crimes and detecting criminal networks. Predictive Analytics Predicting future criminal activities based on past crime patterns (e.g., predicting hotspots for future crimes). Real-time Analysis How big data helps investigators in real-time decision-making and tracking suspects.
- 8. Challenges Faced in the Crime Investigation 1 Limited Information You may encounter limited information about the crime, potentially incomplete evidence, or conflicting witness testimonies. 2 Missing Evidence Some critical pieces of evidence might be missing or tampered with, requiring you to make deductions based on circumstantial evidence. 3 Conflicting Accounts Witnesses may provide conflicting accounts of the events, making it challenging to piece together a coherent timeline and determine the truth. 4 Unreliable Evidence Certain types of evidence may be unreliable or inconclusive, requiring further investigation and analysis to establish their validity.
- 9. Tools for Big Data Analytics in Crime Investigation 1 Forensic Tools EnCase and FTK for collecting, preserving, and analyzing digital evidence. 2 Big Data Platforms Apache Hadoop and Apache Spark for processing large datasets efficiently. 3 Machine Learning IBM Watson and Google AI for identifying patterns in crime data. 4 Geospatial Tools GIS (Geographical Information Systems) for mapping crime scenes and tracking movements.
- 10. Crime Investigation: Challenges and Future Trends Technological Evolution: •Digital evidence complexity increasing •AI and machine learning transforming investigation techniques •Cybercrime becoming more sophisticated Key Investigative Trends: •Advanced forensic technologies •Data-driven predictive models •Enhanced cross-border law enforcement collaboration Future Focus: •Automation of evidence processing •Continuous technological skill upgrades •Integrated multidisciplinary investigation approaches
- 11. Conclusion 1 Summary of Key Points Big data was essential in solving the case by analyzing large datasets to find patterns. Tools like digital forensics, predictive analytics, and machine learning helped process data, while challenges such as data security and technological limitations were encountered. 2 Key Takeaways • Big data can uncover hidden insights that traditional methods may miss. • Advanced tools like predictive analytics and digital forensics are essential in modern investigations. • Data security and real-time analysis remain key challenges. 3 Future Implications As technology advances, big data will continue to transform crime investigations, offering enhanced predictive capabilities and real-time insights for more efficient law enforcement.
- 12. Thank You for Attending We appreciate you taking the time to learn about the fascinating world of crime investigations. Today, we covered a range of topics including evidence collection, forensics, and investigative techniques. We hope this presentation has provided you with valuable insights and sparked your interest in the field. Feel free to reach out if you have any questions.
- 13. References Images • https://www.microsoft.com/en-us/industry/blog/government/2015/10/23/fighting-crime-with-big-data- analytics/ • https://magazine.indianatech.edu/summer-2020/wp-content/uploads/sites/6/2020/09/dom_cj_crime_scen e_3.jpg • https://www.shutterstock.com/shutterstock/videos/1027236944/thumb/1.jpg?ip=x480 • https://us.idyllic.app/gen/neon-futurism-194095 • https://www.freepik.com/free-photo/social-media-marketing-concept-marketing-with-applications_362 95049.htm#fromView=keyword&page=1&position=20&uuid=1ae67c69-1313-4b72-9aeb-a8bdf715a4ad • https://www.freepik.com/premium-ai-image/finger-print-design_341517908.htm Sources • https://www.linkedin.com/pulse/rising-demand-crime-scene-investigators-next-five-terri-armenta-mn gsc/ • https://aithor.co.in/essay-examples/the-evolution-of-criminal-investigation-techniques • https://pmc.ncbi.nlm.nih.gov/articles/PMC10605839/