Charging solution for grid stability and sustainable energy utilization
PIEV offers a bi-directional charging solution enhancing grid stability and sustainable energy use. It integrates smart charging, predictive analytics, Vehicle-to-Grid technology, and secure blockchain transactions for an efficient, resilient, and future-ready energy ecosystem.
Problem
Modern electric vehicle (EV) charging infrastructure struggles with grid demands, efficiency bottlenecks, and security vulnerabilities. This creates a significant challenge in seamlessly integrating sustainable energy sources and maintaining grid stability, hindering the transition towards a more sustainable energy future.
Solution
PIEV introduces a groundbreaking bi-directional charging solution, leveraging smart predictive analytics and robust Vehicle-to-Grid (V2G) technology. It integrates secure blockchain transactions, enhancing grid resilience, optimizing energy utilization, and establishing a secure, efficient, and sustainable ecosystem for EV charging.
PIEV’s Tech Trio: Unbreakable Records, AR, and Voice Command
Tamper-Proof Record
Blockchain technology ensures immutable, transparent records for all charging sessions and transactions, bolstering security and trust.
AR Experience
Augmented reality overlays real-time charging station information, enhancing user interaction and station visibility.
Voice Control
Advanced voice recognition allows intuitive, hands-free operation, streamlining user experience and interaction with the app.
Smart Station Finder
Incorporates GPS and real-time data analytics to locate nearby EV charging stations. Integrated with Google Maps SDK, it offers seamless navigation and up-to-date station information, ensuring convenience and efficiency in finding available charging options.
Vehicle-To-Grid (V2G) Technology
Employs advanced software enabling two-way energy flow between EVs and the grid. Developed using Java for real-time data processing, it optimizes grid stability and energy utilization, enhancing the sustainability of the electrical system.
Technical Architecture
Tools and Technologies Used
Predictive Charging
Utilizes ARIMA and LSTM networks to analyze user data, predicting charging needs. Developed with Python and its robust data analysis libraries, this feature optimizes charging schedules based on user patterns, enhancing efficiency and user experience.
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