IoT2024Senior Laravel Engineer · PureLogics

Save Energy Systems

An enterprise-grade, AI-driven energy intelligence platform designed to monitor, analyze, and optimize real-time power consumption. Built on a high-throughput Laravel architecture, the system aggregates live telemetric data from smart meters, runs predictive optimization models, and automates energy distribution—reducing operational costs and enhancing system reliability.

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The problem

An enterprise-grade, AI-driven energy intelligence platform designed to monitor, analyze, and optimize real-time power consumption.

The solution I built

  • Real-Time IoT Telemetry & Data Processing — Engineered low-latency RESTful APIs and WebSocket pipelines to process high-frequency energy metrics, ensuring real-time visibility across complex industrial setups.
  • AI-Driven Predictive Analytics & Automation — Integrated intelligent algorithms to detect consumption anomalies, forecast peak loads, and trigger automated energy-saving routines to prevent grid overload.
  • Interactive Dashboard & Metric Tracking — Designed an intuitive analytics panel delivering live performance insights, peak-demand heatmaps, and customizable efficiency reports for decision-makers.
  • High-Performance Database & Backend Architecture — Optimized complex time-series database queries, indexing strategies, and caching mechanisms—significantly reducing server load and response times.
  • Enterprise Security & System Integration — Implemented robust authentication, token-based API security, and fail-safe middleware for seamless integration with third-party IoT hardware and energy grids.

Results

Automated scheduling across 200+ hardware units reduced manual intervention by 70% and operating costs by 20%.

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