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Leveraging Big Data and ETL for Border and Immigration Security

Author(s) Manohar Reddy Sokkula
Country United States
Abstract As means of communication and transportation have improved, boundaries have been progressively dismantled. Large audiences are feeling the effects of events that are happening in various nations. Complex security issues have arisen in recent years as a result of responses to an upsurge in attacks and domestic unrest. A lot of nations are having a hard time keeping their borders secure and figuring out how to stop people from crossing illegally. It is reasonable to look at data that comes in at various times from various directions and kinds in real time while thinking about the breadth of border security. Furthermore, a logical approach to developing a pipeline employing Big Data technology would be to include large-scale unstructured analysis of data into the overall solution. The goal of this research is to develop a system that can address border security issues while being affordable, reliable, scalable, and adaptable. Applications related to border security were studied in relation to the usage of Lambda Architecture, which offers batch processing capabilities and real-time data processing. We covered the fundamentals of system development and gave the rundown on how it works.
Keywords Border and Immigration Security; Big Data and ETL; Multi-Aspect Integrated Migration Indicators (MIMI), v2.0, Apache Spark, Lambda Architecture, Apache Kafka, Cassandra, Real-time Data Processing, Batch Data Processing , Artificial-Intelligence
Field Computer > Data / Information
Published In Volume 6, Issue 6, June 2025
Published On 2025-06-25
Cite This Leveraging Big Data and ETL for Border and Immigration Security - Manohar Reddy Sokkula - IJLRP Volume 6, Issue 6, June 2025.
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