1. Overview
In recent years, economic development and the pursuit of comfort have significantly increased energy demand. The importance of optimizing energy systems is apparent in light of the limited energy resources and the urgency to on serve energy. As a result, the market for smart grids and homes in modern smart cities is growing rapidly.
2. Challenges
It is the challenge of this project to develop and implement a sophisticated system that can seamlessly collect and analyze real-time energy consumption data using an IoT gateway. Achieving this requires establishing an infrastructure that can effectively process data, enable detailed analysis of energy consumption patterns, and revolutionize energy management through real-time insights.
Additionally, a crucial aspect is developing a predictive energy optimization system to cater to tenants across different time zones. This necessitates a system capable of forecasting and customizing energy consumption, aiming to efficiently optimize usage for each tenant sustainably.
The collection and synchronization of data across the entire system is essential for comprehensive analysis and monitoring. In order to facilitate unified system-wide analysis, a resilient infrastructure is needed to harmonize multiple data streams, which will ensure seamless data collection, synchronization, in-depth analysis, and informed decisions.
3. Solutions
As part of the proposed solution, an AWS architectural framework integrated with a data lake centralized on AWS is meticulously designed and implemented. In this system, specialized infrastructure serves as a foundation that can be modified, controlled, and expanded according to the system’s needs.
AI-Powered Energy Consumption Prediction System: Advancing Intelligent Energy Management
Additionally, to improve the accuracy and decision-making process, an AI algorithm has been developed to predict 30-day energy consumption. The predictions have been refined through continuous adjustments to hyperparameters.
The system design includes multi-tiered facilities control across diverse locations and time zones for efficient management. It will be easy for administrators to read the data through a user-friendly interface, providing real-time insights for seamless oversight and operational efficiency.
4. Output
The development of a comprehensive power consumption AI prediction system is both important and challenging, as it requires the collection and analysis of real-time energy consumption data via an IoT gateway. It is essential to establish complete connectivity across all sites in order for smart energy management features to be implemented which will revolutionize energy efficiency to an unprecedented degree.
