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D. User-Centric Features C. User Satisfaction
ChargeHub provides users with real-time updates, booking User surveys indicated an 87% satisfaction rate, highlighting
options, and detailed analytics, enhancing the overall the effectiveness of real-time monitoring and user-centric
charging experience. features.
IV. CHARGEHUB ARCHITECTURE VI. RESULT ANALYSIS
ChargeHub’s architecture comprises four key components: The results demonstrate the effectiveness of ChargeHub in
optimizing EV charging networks. Real-time monitoring and
A. IoT Sensors predictive analytics have improved reliability and reduced
IoT sensors installed at charging stations collect data on operational costs, while dynamic load management has
energy usage, temperature, and fault conditions.
ensured efficient energy distribution.
B. Cloud Platform VII. CONCLUSION
The cloud platform processes and stores data from IoT ChargeHub represents a significant advancement in EV
sensors. It uses advanced analytics to generate actionable charging solutions, addressing critical challenges like
insights for users and operators.
reliability, scalability, and user satisfaction. Its real-time
C. Mobile Application monitoring and predictive analytics capabilities have the
The user-friendly mobile app allows EV owners to locate potential to revolutionize the EV ecosystem, making it more
chargers, monitor charging status, and receive notifications efficient and user-friendly.
about charger availability.
REFERENCES
D. Operator Dashboard [1] Smith, J., & Lee, K. (2022). IoT in EV Charging
The operator dashboard provides a comprehensive view of Networks: A Review. IEEE Transactions on Smart
the charging network, including real-time status, usage Grid.
trends, and fault alerts.
[2] Brown, A., & Davis, L. (2023). Predictive Maintenance
V. PERFORMANCE EVALUATION in EV Charging Infrastructure. Journal of Renewable
The performance of ChargeHub was evaluated using a test Energy.
network comprising 50 charging stations. Metrics such as [3] Kumar, R., & Patel, S. (2021). Scalable Architectures
uptime, fault detection accuracy, and user satisfaction were for EV Charging Networks. International Journal of
analyzed.
Energy Systems.
A. Uptime [4] Chen, Z., & Zhang, W. (2020). Interoperability in EV
ChargeHub achieved an uptime of 99.5%, ensuring high
Charging Networks: Challenges and Solutions.
reliability for users.

B. Fault Detection Accuracy
The predictive maintenance module demonstrated a fault
detection accuracy of 94%, significantly reducing downtime.

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