Published Paper Details:

Blindness and low vision problems are increasing nowadays for both youth and aged society. Working members have to work outside in the day time to earn money for the family. So those people are forced to live alone and facing a difficulty because they cannot see things clearly. In this research, Convolutional Neural Networks (CNNs) for household objects finder is proposed. Raspberry Pi 3 is used to help to see objects and tell the type and location of the objects via voice. YOLO neuron network is selected because of the speed and resource images was prepared and fed into YOLO network as training inputs. YOLO is trained in coco database.. Trained YOLO can detect objects .Prototype of wearable device is built by using a webcam, headphone, push switch, battery and Raspberry Pi 3. Device will capture an image when a push switch is pressed and Raspberry Pi returns pre recorded voice results consist of objects types and their locations through headphone to users.This device can be used for finding various kinds of objects without more delay. Availabiliry of the components create this device easily available in the market and reduces its cost.