The purpose of this paper is to present a method to detect bike trail conditions while displaying real-time data on a mobile application. Using a Global Positioning System (GPS) unit, microprocessor and multiple accelerometers built on the concept of Internet of Things (IoT), the entire device employs real-time data to collect, analyze, and identify bumps and cracks in public infrastructure. The main purpose of this research is aimed at helping the government evaluate the severity of road conditions to better assist in strategic decision making about maintaining or repairing damaged infrastructural areas as well as to notify pedestrians of potential bumps or cracks along their route. The authors propose an algorithm that sets a window range to vertically process the raw accelerometer data to accurately distinguish bumps. By integrating this algorithm onto a mobile application, the data collected by this program can be shared between users to help avoid potential risks or dangerous road conditions and to assist in the evaluation of infrastructural deterioration.