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Visual impairments have become one of the most predominant problems for the last few decades. To keep doing their daily tasks, vision-impaired people usually seek help from others. An automated common object and currency recognition system can improve the safe movement and transaction activity of visually impaired people. To develop a system that can identify indoor and outdoor objects, notify the users, and send all information to a remote server repeatedly at a fixed time interval. The proposed system assists the visually impaired to recognize several objects and provides an audio message to aware the user. Four laser sensors are used in the system to detect the objects in the direction of the front, left, right and ground. The proposed system uses Single Shot Detector (SSD) model with MobileNet and Tensorflow-lite to recognize objects along with the currency note in the real-time scenario in both indoor and outdoor environments. Among 375 participants, 82% reacted that the price of the proposed system is reasonable, 13% treated as the cost is moderate and the rest 5% people responded that the cost is relatively high for them. In terms of size and weight, 73% reacted that the size and weight are considerable, 20% treated that the size is not suitable, and weight needs to lessen, and the rest 7% people responded that the system is bulky. Regarding input signal observation, 98% responded that they have heard the sound appropriately and the remaining 2% of individuals missed hearing the signal. This paper represents an IoT-enabled automated object recognition system that simplifies the mobility problems of the visually impaired in indoor and outdoor environments. The overall accuracy of the proposed system in object detection and recognition is 99.31% and 98.43% respectively. In addition, the proposed system sends all processed data to a remote server through IoT.
Rahman et al. (Fri,) studied this question.