Voice Alert Sebagai Alat Bantu Penglihatan di Lingkungan Rumah dan Jalanan Secara Umum Berbasis Android - Kevin Christian Salim; Liliana Liliana; Rolly Intan (Jurnal Infra, 2021)
According to research conducted by the Governors Highway Safety Assocation in 2017 showed that there are about 6 thousand pedestrians killed in America due to the habit of using smartphones while walking. Another study from Jeff Ronsen showed that the brain is overloaded and cannot function properly when performing these two activities at the same time. Walking while using a smartphone makes the concentration on the atmosphere of the road split and makes pedestrians not focus on the road but rather on the smartphone. Such behavior results in an increased risk of pedestrian accidents. One solution to prevent accidents above is to use the smartphone camera to take pictures in front of the user.Smartphone cameras can be used to retrieve input data in the form of images in real time which is then carried out the process of object detection and issue alerts in the form of sounds that mention the name of the detected object to smartphone users. Detected objects are objects that are generally located in home and street environments such as humans, cars, bicycles, motorcycles, and stop signs. Object detection using SSD MobileNet applied transfer learning that is further trained by using google open image dataset v6 dataset. The result of transfer learning is weight used to detect objects from android camera input.The test results showed that SSD_MobileNet_V2 with a learning rate of 0.01 and steps 10,000 has the best mAP value with 80% in detecting objects. The SSD_MobileNet_V2 can detect objects with an inference time speed of 80ms – 110ms in real time in a standby device, and voice alerts by instantly issuing alerts when an object is detected.