Design and Implementation of an Intelligent Assistive System for Visually Impaired People for Aerial Obstacle Avoidance and Fall Detection

This paper proposes an intelligent assistive system based on wearable smart glasses and an intelligent walking stick for visually impaired people to achieve the goals of aerial obstacle avoidance and fall detection. The proposed assistive system comprises wearable smart glasses, an intelligent walking stick, a mobile device app, and a cloud-based information management platform. Visually impaired people can wear the proposed wearable smart glasses and hold the proposed intelligent walking stick to detect aerial obstacles and fall events on roads. Moreover, the proposed intelligent walking stick can vibrate to guide visually impaired people to avoid aerial obstacle collision accidents. Experimental results show that the proposed system can detect aerial obstacles within 3 meters, and the average accuracy of fall detection reaches up to 98.3%. Furthermore, when visually impaired people experience a fall event, an urgent notification is immediately sent to their family members or caregivers.

[1]  Luis Miguel Bergasa,et al.  Unifying Terrain Awareness for the Visually Impaired through Real-Time Semantic Segmentation , 2018, Sensors.

[2]  Manoj Singh Gaur,et al.  Embedded Assistive Stick for Visually Impaired Persons , 2018, 2018 9th International Conference on Computing, Communication and Networking Technologies (ICCCNT).

[3]  Dmytro Zubov,et al.  A Smart City Assistive Infrastructure for the Blind and Visually Impaired People: A Thin Client Concept , 2018 .

[4]  Ali Jasim Ramadhan Wearable Smart System for Visually Impaired People , 2018, Sensors.

[5]  R Legood,et al.  Are we blind to injuries in the visually impaired? A review of the literature , 2002, Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention.

[6]  Titus Zaharia,et al.  Wearable assistive devices for visually impaired: A state of the art survey , 2020, Pattern Recognit. Lett..

[7]  Shu-Li Sun,et al.  Multi-sensor optimal information fusion Kalman filter , 2004, Autom..

[8]  Liang-Bi Chen,et al.  An Implementation of an Intelligent Assistance System for Visually Impaired/Blind People , 2019, 2019 IEEE International Conference on Consumer Electronics (ICCE).

[9]  Lih-Jen Kau,et al.  A Smart Phone-Based Pocket Fall Accident Detection, Positioning, and Rescue System , 2015, IEEE Journal of Biomedical and Health Informatics.

[10]  Josechu J. Guerrero,et al.  Navigation Assistance for the Visually Impaired Using RGB-D Sensor With Range Expansion , 2016, IEEE Systems Journal.

[11]  Joarder Kamruzzaman,et al.  Low-Power Wide-Area Networks: Design Goals, Architecture, Suitability to Use Cases and Research Challenges , 2020, IEEE Access.

[12]  Liang-Bi Chen,et al.  An AI Edge Computing Based W earable Assistive Device for Visually Impaired People Zebra-Crossing Walking , 2020, 2020 IEEE International Conference on Consumer Electronics (ICCE).

[13]  Jinqiang Bai,et al.  Virtual-Blind-Road Following-Based Wearable Navigation Device for Blind People , 2018, IEEE Transactions on Consumer Electronics.

[14]  Ali Farhadi,et al.  You Only Look Once: Unified, Real-Time Object Detection , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[15]  Mohit Gupta,et al.  A Smart Walking Stick Powered by Artificial Intelligence for the Visually Impaired , 2019 .

[16]  Ilenia Tinnirello,et al.  An Indoor and Outdoor Navigation System for Visually Impaired People , 2019, IEEE Access.

[17]  Wang-Rong Chang,et al.  ActionView: a movement-analysis ambulatory monitor in elderly homecare systems , 2009, 2009 IEEE International Symposium on Circuits and Systems.

[18]  Liang-Bi Chen,et al.  i-Car system: A LoRa-based low power wide area networks vehicle diagnostic system for driving safety , 2017, 2017 International Conference on Applied System Innovation (ICASI).

[19]  Shiguo Lian,et al.  Smart guiding glasses for visually impaired people in indoor environment , 2017, IEEE Transactions on Consumer Electronics.

[20]  Juan Manuel Sáez,et al.  Aerial Obstacle Detection With 3-D Mobile Devices , 2015, IEEE Journal of Biomedical and Health Informatics.

[21]  Katherine J. Kuchenbecker,et al.  HALO: Haptic Alerts for Low-hanging Obstacles in white cane navigation , 2012, 2012 IEEE Haptics Symposium (HAPTICS).

[22]  Paola Russo,et al.  An Electromagnetic Sensor Prototype to Assist Visually Impaired and Blind People in Autonomous Walking , 2018, IEEE Sensors Journal.

[23]  Khaled M. Elleithy,et al.  A Highly Accurate and Reliable Data Fusion Framework for Guiding the Visually Impaired , 2018, IEEE Access.

[24]  Alexander A. Kist,et al.  Low Power Wide Area Networks: A Survey of Enabling Technologies, Applications and Interoperability Needs , 2018, IEEE Access.

[25]  René Farcy,et al.  Optical Device Indicating a Safe Free Path to Blind People , 2012, IEEE Transactions on Instrumentation and Measurement.

[26]  Md. Milon Islam,et al.  Developing Walking Assistants for Visually Impaired People: A Review , 2019, IEEE Sensors Journal.

[27]  Chih-Wei Lee,et al.  Improving Mobility for the Visually Impaired: A Wearable Indoor Positioning System Based on Visual Markers , 2018, IEEE Consumer Electronics Magazine.

[28]  Ruiqi Cheng,et al.  Visual Localizer: Outdoor Localization Based on ConvNet Descriptor and Global Optimization for Visually Impaired Pedestrians , 2018, Sensors.

[29]  Khaled M. Elleithy,et al.  Sensor-Based Assistive Devices for Visually-Impaired People: Current Status, Challenges, and Future Directions , 2017, Sensors.

[30]  Ruxandra Tapu,et al.  DEEP-SEE: Joint Object Detection, Tracking and Recognition with Application to Visually Impaired Navigational Assistance , 2017, Sensors.

[31]  Emmanuel Andrès,et al.  From Fall Detection to Fall Prevention: A Generic Classification of Fall-Related Systems , 2017, IEEE Sensors Journal.

[32]  Lilit Hakobyan,et al.  Mobile assistive technologies for the visually impaired. , 2013, Survey of ophthalmology.