SEMOCS

Project Goal

The Smart Energy Monitoring, Optimization, and Control System (SEMOCS) represents a transformative leap in energy management, combining IoT connectivity, AI-driven analytics, and automated control to optimize energy use across residential, commercial, and industrial environments. Building on next-generation technologies, SEMOCS integrates advanced features from modern energy management platforms while introducing novel capabilities for sustainability and scalability.

Design Approach

Core System Architecture

IoT Sensor Network

SEMOCS employs a distributed network of smart sensors and meters to monitor electricity consumption, solar/wind input, HVAC performance, and appliance usage in real time. These devices feed data into a centralized AI engine via edge computing nodes, enabling low-latency processing for critical operations like anomaly detection.

AI-Powered Analytics Engine

Load Forecasting: Machine learning models analyze historical usage patterns, weather data, and occupancy trends to predict energy demand with 90%+ accuracy.

Fault Detection: Neural networks identify equipment malfunctions or grid irregularities 40% faster than traditional threshold-based systems.

Automated Control Hub: Implements dynamic HVAC setbacks based on occupancy sensors

Orchestrates appliance schedules to leverage off-peak pricing

Balances grid power with renewable sources using predictive generation forecasts

Color Palette: Earthy and natural tones were selected to represent sustainability, nature, and environmental responsibility.

Visual Elements: Carefully designed icons and imagery were incorporated to reinforce key messages and enhance user engagement.

User Accessibility: The layout was structured to ensure effortless navigation, making complex data digestible and visually compelling.