IoT Energy Management Platform for Smart Climate Control

Reducing Energy Costs Through Intelligent Climate Automation

Automating heating and cooling management to minimize electricity costs in a dynamic tariff environment in the UK.

In the UK, electricity prices vary significantly throughout the day depending on the provider’s tariff (dynamic, day, or night rates). Typically, users heat their spaces on fixed schedules, which leads to unnecessary costs during peak pricing hours. Maintaining a balance between comfort and cost has traditionally required constant manual monitoring and device adjustments.

The key challenge was to build a system that eliminates the need for manual control after the initial setup and automatically optimizes energy consumption based on the most cost-efficient tariffs, without compromising indoor comfort.

AI-Powered Energy Optimization for Smart Climate Control

An AI-powered IoT ecosystem that generates optimized daily schedules based on energy prices, weather forecasts, and user profiles.

At the core of the solution is a device used to connect heaters and air conditioners to the platform.

Each morning, the AI model processes user preferences, room parameters, weather forecasts, and electricity price fluctuations to generate an individualized device operation schedule.

Through a mobile application, users define preferred temperature settings for different time periods, while the system continuously monitors device performance and environmental conditions in real time.

A dashboard provides energy consumption analytics per room and enables users to evaluate overall efficiency and resource usage.

Scalable IoT Architecture for Reliable Device Management

A multi-layered architecture combining IoT hardware, cloud infrastructure, and a mobile control interface.

The technical infrastructure is composed of several key components to ensure reliability and accuracy:

Hardware and Firmware
The device is a smart plug controlled by a microcontroller that stores the daily schedule and manages power load accordingly. In case of failures in load control or deviations from expected power consumption, the device automatically shuts down.

Cloud Infrastructure
The system uses two interconnected backend layers: one manages the AI optimization model and communication with devices, while the other supports the mobile application and web interface.

Data Management
DynamoDB is used to store and manage device statuses and telemetry data, as it is well-suited for IoT scenarios due to its high write throughput, flexible data model, and efficient handling of time-series data.

Integration and Deployment
Each device is registered by scanning a unique QR/barcode via the mobile application. The infrastructure is defined as code and deployed using Terraform, ensuring reproducible and controlled updates across development, staging, and production environments.