Implementation Of Fuzzy Logic to Identify Accident Categories In SMS-Based Two-Wheeled Vehicles

Two-wheeled vehicle is the most popular means of transportation in Indonesia. As a result, it would cause several issues. One of them is an increased possibility of an accident to happen. In the event of an accident, quick aid from the public to the victim can reduce the risk of severe injury suffered by him. The person who provides aid to the injured victim may ask for money from the victim's family whose amount is not proportionate with the severity of the accident. In light of this, a system has been devised to identify and categorize the different types of accidents and send the formation to a family phone number registered electronically. The accident level is categorized using the Sugeno-type fuzzy logic method. The parameters used to differentiate the accident categories are speed, slope, and duration of vehicle braking time. The information is then sent to the registered phone via SMS that contains the accident category and the coordinates of the accident location provided by the GPS Neo 6 module. The algorithm is based on the vehicle's tilt angles, which range from 45(to the right) and -45(to the left). The fuzzy logic then determines the category, which processes and produces the accident category based on the speed and vehicle braking duration parameters. The proposed algorithm in this research will be experimented with using a real motorbike. Based on the experimental results, it has been found that the performance of the fuzzy logic method has an accuracy of 88.89% when determining the category of accident (light or heavy) and the time taken to send the information to the family member via SMS is quite fast.