Buncombe County in North Carolina is set to revolutionize the way non-emergency calls are handled through the introduction of Machine Learning technology. With an average of 825 non-emergency calls flooding their 911 center daily, the county recognizes the need to streamline operations to prioritize emergency calls effectively.
The implementation of Amazon Web Services Solution, known as Machine Learning, will involve a 30-day training period for the system to learn and understand caller inquiries before being fully operational. This cutting-edge technology will enable the system to interact with callers, directing them to the appropriate party promptly.
It is crucial to note that despite this advancement, 911 calls will always be answered by highly trained public safety telecommunicators. In situations where a non-emergency call requires police, fire, or paramedic response, callers will be expediently transferred to a telecommunicator for assistance.
Other jurisdictions that have adopted Machine Learning for non-emergency calls, such as Charleston County in South Carolina and Jefferson County in Colorado, have seen substantial decreases in call volume for call-takers. Buncombe County aims to follow suit and expects Machine Learning to be operational by May 9.
As technology continues to shape the landscape of emergency response systems, Buncombe County’s initiative signifies a progressive step towards optimizing efficiency and enhancing overall service delivery. By harnessing the power of Machine Learning, the county is poised to address the challenges posed by staffing shortages and high call volumes, ensuring that both emergency and non-emergency calls are handled with precision and effectiveness.
