Transportation plays a important role in our everyday life, but increasing vehicle numbers worsen traffic congestion and hence requires to focus the security issues. Safety is a key concern, especially in India, which faces significant road safety challenges. Analyzing driving styles can aid authorities in identifying errors and enhancing security measures. This study investigates integrated sensor and computing systems for assessing driving behaviors and provide security to the system. It evaluates driver performance across speed, acceleration, deceleration, and rpm scenarios using OBD II sensors linked to the Electronic Control Unit (ECU). Torque Pro analyzes raw data from OBD II readers to assess driving styles, categorizing results as safe, normal, aggressive, or dangerous. A t-test, conducted using IBM SPSS, assesses differences between GPS and OBD II speeds to select appropriate datasets. The driving dataset is stored in Firebase cloud for analysis. Securing OBD II dataset in Firebase Cloud involves ensuring data integrity, confidentiality, and availability.