Case Study: Live Building Systems
Services: System Architecture, Software Development, UX/UI Design, System Monitoring
Technologies: React.js, Python, PostgreSQL, Amazon Web Services
Date: 2015 - 2019
Buildings are what make New York City, and they require an immense amount of resources. The systems that provide electric, water, gas, and oil to the city’s 860,000+ buildings are rapidly aging, in a time where real-time tracking and optimizations are more important than ever.
Live Building Systems is the first platform in New York to provide access to all utility activity in real time for landlords and management companies. The Live Buildings Software breaks down utility consumption into data streams, allowing to analyze and diagnose costly inefficiencies.
When we were first contacted about the project, it was not much more than an idea. They knew there was a problem and how to solve it, but not how to execute it on a technical level.
With the rapidly lowering cost of implement IoT (internet of things) devices, and an expert team with decades of experience managing buildings around New York, the team behind Live Building Systems set out to bring these archaic systems into the 21st century.
Reustle.co was in charge of all software development and architecture for the initial 3 years of the company.
Live Reporting Dashboard
Landlords and management companies needed real time access to all of their utility usage data. Using modern libraries like React and Flask (Python), our team put together an easy to use dashboard and reporting platform that vastly improved their daily workflows.
Knowing the amount of data they would need to handle, the team designed the system to accept all types of sensor data from various of sources. We chose to use the hosted Postgres database, RDS, from Amazon Web Services to ensure easy replication and future expansion, and effortless scaling.
In addition to the many APIs and devices we consumed data from, we produced a REST API of our own for external systems to integrate with.
We worked closely with various types of IoT devices to track different data sources. Some devices pushed data to a 3rd party server where we could access it, some pushed data directly to our systems, while others provided endpoints or telnet access to gather the data ourselves constantly.
To ensure the highest level of code quality and maximum system uptime, the team utilized various testing methods and tools such as CircleCI, Sentry, and Selenium.