• Samita Atul Patil
• Akanksha Tambitkar
• Phadatare Rutuja R
• Pol Vaishnavi S

Autonomous vehicles have been developed to enhance transportation safety by sensing their environment and making decisions without external assistance, ultimately producing an optimal route to reach a destination. They are the envisioned future of smart, efficient, and crash- avoiding urban vehicles. Automakers have begun working in this area to realize the potential and address the current challenges to achieve the expected outcome. However, analyzing the energy consumption, vehicle-specific power, and power consumption poses some difficulties. To overcome these issues, we are creating a big data application called "Vehicles Data Analyzation." This application collects vehicle data several times per second, enabling fine-grained and near-real-time analysis of vehicle status and operating behavior. Our focus is on typical streaming applications, and we present implementations using Power BI. We compare the different architectures of autonomous vehicular systems, including speed, vehicle-specific power, actual power consumption, and energy consumption. We also compare the different databases such as Hadoop and MongoDB. Our ultimate goal is to show the analysis of the fine features integrated into the vehicular system

Energy consumption, Vehicle specific power, Power consumption, Performance Evaluation between Hadoop and MongoDB

"VEHICLE DATA ANALYZATION USING POWER BI", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 7, page no.55-63, July-2024, Available :http://www.jetir.org/papers/JETIRGK06007.pdf

"VEHICLE DATA ANALYZATION USING POWER BI", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 7, page no. pp55-63, July-2024, Available at : http://www.jetir.org/papers/JETIRGK06007.pdf