IoT-Powered Big Data Processing for Intelligent Transportation: Enhancing Effectiveness and Forecasting

In an era driven by technological innovation, the fusion of big data analytics and the Internet of Things (IoT) has revolutionized various domains. In this realm, we navigate the convergence of big data analytics and the IoT to create a comprehensive framework for processing smart transport data. To build a solid foundation, we collect data from a variety of sources. Using Hadoop MapReduce and Kafka with Apache Spark, our two-tiered processing approach uses Hadoop Distributed File System (HDFS) for storage. In order to provide a thorough approach to data analytics, the Prediction layer incorporates algorithms for path prediction such as Random Forest, LSTM, and Recursive Feature Elimination. Our overall objectives are aligned with Content-Based Filtering, which maximizes energy-conscious resource utilization. IoT and Big Data technologies are seamlessly blended in a comprehensive smart transport data processing framework to enable optimal real-time processing, predictive analytics, and effective decision-making.