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Edge Impact: Optimizing Power Usage in Underserved Areas


Introduction
Context: Underserved areas face significant challenges in telecommunications due to limited infrastructure and high operational costs.
Objective: To implement a simulation-based solution that dynamically optimizes power consumption based on network parameters.


Current Challenges
Inadequate Connectivity: Poor network coverage and service quality hinder economic growth.
High Energy Costs: Inefficient power usage leads to increased operational expenses.
Lack of Real-Time Data: Insufficient monitoring and analytics for effective power management.


Problem Statement
Main Problem: Telecommunications in underserved areas struggle with power inefficiency, impacting service reliability and operational costs.
Key Issues:
Fluctuating energy demands due to varying user activity.
Inefficient power usage resulting in high costs and environmental impact.
Limited ability to predict and adjust power requirements dynamically.


Proposed Solution
Simulation-Based Optimization: Developed a simulation model that dynamically adjusts power consumption based on real-time network parameters (traffic volume, user count, latency, etc.).
Adaptive Algorithms: Utilized adaptive algorithms to predict energy needs and optimize power usage effectively.


Implementation Details
Key Parameters Monitored:
Traffic Volume
User Count
Latency
Signal Strength
Simulation Results: Showcase results demonstrating improved energy efficiency and reduced costs.


Expected Outcomes
Improved Energy Efficiency: Significant reductions in power usage and operational costs.
Enhanced Network Performance: More reliable service delivery to users in underserved areas.


Summary: The simulation-based solution effectively addresses power inefficiency in telecommunications networks serving underserved areas.
Next Steps: Plan for real-world testing of the solution to validate the simulation outcomes.

In the rapidly evolving landscape of telecommunications, underserved areas face significant challenges, particularly regarding power inefficiency and high operational costs.

"Edge Impact team on Edge Runners 3.2 Hackathon"

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