Fuzzy Logic Based-Assistance System for Detecting Forklift Blind Spot Area Using Radar-Like-Ultrasonic Sensors.

The utilization of forklifts in the industrial sector presents challenges in terms of visibility, particularly in certain areas known as blind spots. The operator's attentiveness when assessing objects in these blind spot areas significantly influences the safety of both the operator and the objects within the operating vicinity. To address this issue, this study aims to develop a system to detect objects within the blind spot area of the forklift unit using fuzzy logic and ultrasonic with a configuration similar to radar. This system can make decisions regarding object severity and positions. The system's scope encompasses the detection of objects in the blind spot areas on the sides, right, left, and rear of the forklift with severity identification. When an object is detected within the blind spot area, the system automatically issues notifications regarding the object's severity and position through LED indicators, RGB lights, and a buzzer. For conducting the experiment, the employed HC-SR04 ultrasonic sensor is firstly tested. The results show that it can continuously detect objects up to a maximum measured distance of 402.46 cm. Several fuzzy logic scenarios are then employed by considering various rules. The first rule considers as the high severity while the object position at the medium distance and behind the unit. The second rule decide otherwise. After conducting the simulation and experiment, the first rule is selected because it provides output with a good agreement with expert references. In brief, based on the testing results, the proposed system has demonstrated its ability to accurately detect object positions and severities.