Case Study - Smart Home

Overview

E.ON, one of Europe's largest energy companies, developed an innovative IoT solution aimed at empowering their customers with greater control over their energy consumption. This project represented a significant step forward in E.ON's commitment to smart home technology and energy efficiency.

The core of the solution was a smart gateway equipped with Zigbee and Bluetooth Low Energy (BLE) capabilities. This gateway served as the central hub for an ecosystem of smart devices, including thermostats, lights, and smart power outlets. By connecting these devices, E.ON customers gained the ability to monitor their energy usage in real-time and manage their connected devices remotely.

Our team was responsible for developing the backend infrastructure that powered this IoT network, ensuring seamless communication between the smart devices, the gateway, and E.ON's cloud services. We also created user-friendly interfaces that allowed customers to easily view their energy consumption data and control their smart home devices from their smartphones or computers.

This project not only enhanced E.ON's product offerings but also contributed to their broader goals of promoting energy conservation and giving customers more control over their energy usage. By providing real-time data and remote management capabilities, E.ON empowered their customers to make informed decisions about their energy consumption, potentially leading to reduced energy bills and a smaller carbon footprint.

This project was finally discontinued and is currently not available anymore.

What we did

To implement this sophisticated IoT solution for E.ON, we leveraged cutting-edge technologies and cloud services, primarily focusing on Google Cloud Platform (GCP) for its scalability and robust IoT support. Here's a detailed breakdown of our technical implementation:

1. Serverless Backend on GCP: We developed a serverless backend using Google Cloud Functions, which allowed for automatic scaling and cost-efficiency. This architecture handled incoming data from the smart gateways and devices, processed it, and stored it in the database. We used Node.js for our Cloud Functions due to its event-driven nature and excellent performance for I/O operations.

2. Pub/Sub: Google Cloud Pub/Sub was employed as a messaging middleware to ensure reliable, asynchronous communication between different components of the system. This allowed for decoupling of services and improved system resilience.

3. NoSQL Database: For data storage, we chose Google Cloud Firestore, a flexible, scalable NoSQL database. It stored device states, user preferences, and historical energy consumption data. We designed the data model to optimize for frequent reads and writes, ensuring fast access to real-time data.

4. Rules Engine (Node-RED): We implemented a sophisticated rules engine using Node-RED. This engine processed incoming device data and user-defined rules to trigger actions or alerts. For example, it could automatically adjust thermostat settings based on energy prices or user preferences.

5. BigQuery and Data Studio: To provide insightful analytics to E.ON and its customers, we used BigQuery for data warehousing and analysis. We set up data pipelines to continuously import data from Firestore to BigQuery. Data Studio was then used to create interactive dashboards and reports, giving users detailed insights into their energy consumption patterns.

6. Security: Security was a top priority. We implemented end-to-end encryption for all data in transit and at rest. We used Cloud Key Management Service (KMS) for key management and Cloud Identity and Access Management (IAM) for fine-grained access control.

7. Continuous Integration/Continuous Deployment (CI/CD): We set up a robust CI/CD pipeline using Cloud Build, Container Registry, and Cloud Source Repositories. This allowed for rapid, automated testing and deployment of new features and updates.

This architecture allowed E.ON to provide a responsive, scalable, and secure IoT solution to their customers, enabling real-time energy monitoring and smart device control while ensuring data privacy and system reliability.