Additionally, Fybr will be showcasing the extensibility of the Fybr Smart City Platform by deploying additional sensors to monitor vehicle activity at bus stops, loading zones, and air quality. Installation of hardware begins in mid-September with evaluations starting on October 1 and running through the end of the year.
Fybr’s parking sensor offers a highly accurate, low-cost solution for detecting vehicles in spaces on-street, in surface lots, or garages.
With ultra-low latency and a 7-10 year battery life, the Parking Sensor III delivers real-time space occupancy – allowing both consumers and cities to make better, informed parking decisions.
Fybr’s Smart City Platform helps communities operate more efficiently, reduce operating costs, and improve the quality of life. With a turnkey solution that collects more information—more efficiently—Fybr provides communities with the best and fastest opportunity to create a return on Smart City investments. Located in Saint Louis, MO, with a 20-year history, Fybr’s patented IoT solutions have over two billion data events logged from real-world applications globally.
Innovating Parking in Columbus: An interview with Robert Ferrin
The Columbus Division of Parking Services embraces the spirit of innovation and the use of technology to create an optimal on-street parking experience in its urban neighborhoods.
Fybr Promotes Linnell Gorden to Executive Vice President, Software Engineering.
Fybr proudly announces Linnell Gordon will be assuming the position of Senior Vice President, Software Engineering. Beginning with Fybr as a consultant in 2014, Gordon was initially brought on board to support the Java-based infrastructure in place at the time.
Recognizing The Truth: Where Camera-Based Recognition Falls Short
Camera-based image recognition systems are built on a simple premise- they are electronic “eyes” capable of recognizing unique items and capturing data. The unique item can be everything from a license plate number to a human face. Once recognized and captured, the resultant data can be applied to a wide variety of use cases, such as parking, traffic, or law enforcement. This simple premise is easy to grasp, and its outcome is a highly-desirable one. But as with many technologies, what works in theory under controlled conditions and what works in practice in real-world situations aren’t always the same.