API’s & Machine Learning Principles For Fire Systems

Abstract

The FireConnect product line exists as a well-developed system for remote monitoring of fire protection systems with an extensive array of compatibility and iterations based on the controller manufacturers and their product lines, each with their own unique communication protocols. The FireConnect service provides the user with a unique interface for their monitoring service with access through a web-based browser or a dedicated mobile application. This product also collects and aggregates the same data on the service providers cloud-based servers, where we as the manufacturer can access this data via an API, or Application Programming Interface. This provides us, the manufacturer, with a plethora of data with an infinite amount of value, ripe with potential for monetization.

The problem is nothing has been developed to make use of the data and its untapped potential outside of the real-time monitoring system unless an individual with extensive experience and industry knowledge were to examine the data trends. The goal of this project was to use the data in such a way to generate sales based on the logical use of this data and industry specific requirements for maintenance and testing, to provide automatically generated leads. These leads are to be automatically populated on a user interface, not to be confused with the existing product offering, but to be used by customer service or sales managers to proactively engage with customers, while simultaneously generating an email-based notification for the customer on file.