Energy Startup Creates Insights Into Consumers Costs with Block Heating
Homii, a energy startup in the netherlands creates insight into heat consumption in block heating for consumers. By integrating data from different sources and performing complex calculations, Homii is now able to create costs forecasts for consumers.
The Goal
Create cost forecasts into heat consumption for consumers that have block heating.
The Challenge
Create accurate forecasts using different data formats of heating meter readings.
The Approach
Create an idempotent datapipeline with a flexible cloud architecture that supports uploading of data for non technical users.
- Sector
- Energy
- Use Case
- MVP
About Homii
Homii is a pioneering solution to address the challenges faced by residents of block-heated apartment buildings in the Netherlands. With the steep rise in gas prices since 2022, it has become increasingly important for individuals to have visibility into their individual gas usage. However, due to the centralized heating system in these buildings, residents lack insight into their consumption patterns.
Homii aims to bridge this information gap by transforming all meter readings of the building into a user-friendly dashboard. This dashboard empowers residents to monitor their energy consumption in real-time, providing valuable insights. Additionally, Homii goes beyond real-time monitoring by offering consumption forecasts for the remaining season. This enables residents to proactively manage their energy usage and make informed decisions to optimize costs.
By providing individuals with access to their energy consumption data and personalized forecasts, Homii empowers residents in block-heated apartment buildings to take control of their gas usage and navigate the challenges of rising gas prices.
The Challenge: Data Processing for Accurate Forecasts
In the context of creating accurate forecasts using different data formats of heating meter readings, Homii faced a significant challenge. They required a mobile-first web app offering valuable insights into energy consumption and the associated costs for individuals residing in block-heated apartment buildings. To tackle this challenge, BiteStreams was entrusted with building a robust back-end system for the mobile and web app. The back end needed to seamlessly integrate various data sources, provide comprehensive usage reporting to users, and deliver reliable projections of future costs.
The Approach: Data Pipeline & Cloud Architecture
To create accurate cost forecasts for block heating consumers and overcome the challenge of handling different data formats, we have implemented an idempotent data pipeline with a flexible cloud architecture. This solution enables non-technical users to easily upload their heating meter readings while ensuring user-friendliness and accuracy in cost forecasting.
Data Collection and Integration: We have developed an intuitive web-based interface that allows non-technical users to upload their heating meter readings effortlessly. Our system supports multiple data formats, including CSV, Excel, and API integrations, to accommodate the various sources of meter readings. To ensure data quality and consistency, we have implemented robust data validation and cleansing processes, effectively identifying and rectifying any issues in the uploaded data.
Data Transformation and Standardization: Once the data is uploaded, we convert it into a unified format that can be readily processed and analyzed. Our data transformation techniques normalize and standardize the data, accounting for variations in units, time zones, and other relevant factors. We handle missing data points or anomalies by utilizing appropriate methods, such as data imputation or outlier detection, ensuring the accuracy and reliability of the transformed data.
By implementing these data collection, integration, transformation, and standardization processes, we ensure that the data used for cost forecasting is of high quality and in a consistent format. This lays a solid foundation for accurate and reliable cost forecasts for consumers with block heating systems.
Conclusion
The project outcome was a successful Minimum Viable Product (MVP) with a cloud-based production-ready architecture. Our focus was on delivering a flexible and accurate data processing system to provide users with precise predictions of their heating usage, which is the core value proposition of Homii.
The developed app exhibits user-friendliness for administrative users and customers, ensuring an intuitive experience. Our adherence to test-driven development practices resulted in high-quality software that can be easily adjusted to accommodate new emerging requirements.
Furthermore, we designed the product to be scalable and adaptable for future enhancements. This includes the capability to seamlessly incorporate future heating predictions into the calculations, ensuring ongoing accuracy and relevance.
Overall, the outcome of the project met the goals of Homii, delivering a robust and user-friendly solution that empowers users with accurate heating usage predictions while maintaining the flexibility to accommodate future needs.
“Working with BiteStreams was a pleasant experience. Communication went smoothly, and their project management and code are of outstanding quality. Would definitely recommend!”