سیستم کمکی برای هدایت افراد دارای اختلالات بینایی پشت میزهای کار

نوع مقاله : مقاله پژوهشی

نویسندگان

امیرمحمد برسلانی

حمیدرضا محمدی دانیالی

آرمان مردانی

دانشکده مهندسی مکانیک، دانشگاه صنعتی نوشیروانی بابل، بابل، مازندران، ایران

10.22067/jacsm.2025.91402.1310

چکیده

بر اساس گزارش سازمان بهداشت جهانی، بیش از ۳۸ میلیون نفر نابینا و بیش از ۱۱۰ میلیون نفر با مشکلات جدی بینایی روبه‌رو هستند. این پژوهش با هدف ارائه سیستمی کم‌هزینه و در دسترس برای کمک به افراد نابینا در محیط‌های کاری، از یک دوربین تک‌گانه (مثلاً دوربین تلفن همراه) و مدل‌های ازپیش‌آموزش‌دیده بهره می‌برد. با استفاده از روش پردازش تصویر با حجم محاسباتی کم، هزینه‌های سخت‌افزاری و پردازشی بهینه می‌شود. در این سیستم، اشیاء و دست کاربر تشخیص داده می‌شوند و ارتفاع اجسام و فاصله آن‌ها تا دست محاسبه می‌شود. سپس از طریق راهنمایی صوتی، کاربر برای دسترسی ایمن به اشیاء هدایت می‌شود. در مقایسه با روش‌های پرهزینه مانند سیستم‌های دو دوربینه یا سنسور کینکت، نوآوری اصلی این پژوهش کاهش چشمگیر هزینه‌ها با حفظ دقت کاربردی است؛ چرا که برای هدایت افراد نابینا در محیط‌های کاری، دقت میلی‌متری ضروری نیست. عملکرد سیستم به‌منظور دستیابی به خطای تخمین فاصله‌ای در حدود ۵ تا ۱۰ میلی‌متر بررسی خواهد شد؛ انتظار می‌رود دقت این سیستم در مقایسه با روش استریوویژن مشابه باشد.

کلیدواژه‌ها

سیستم کم‌هزینه

افراد نابینا

تشخیص اشیاء

راهنمایی صوتی

مدل‌های پیش‌آموزش‌دیده

دوربین تک‌گانه

موضوعات

• رباتیک

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عنوان مقاله English

Assistive system to guide visually impaired people behind work desks

نویسندگان English

Amirmohammad Barsalani

Hamidreza Mohammadi Daniali

Arman Mardani

Department of Mechanical Engineering, Babol Noshirvani University of Technology, Mazandaran

چکیده English

According to the World Health Organization (WHO), over 38 million people are blind and more than 110 million suffer from severe visual impairments. This research aims to develop a low-cost, accessible assistance system for blind individuals in work environments, utilizing a single camera (e.g., a smartphone camera) and pre-trained deep learning models. By employing computationally efficient image processing techniques, the system optimizes hardware and processing expenses. It detects objects and the user’s hand, computes object heights and their distances to the hand, and then provides real-time audio guidance (e.g., verbal directions) to enable safe object retrieval. Compared to expensive alternatives like dual-camera setups or Kinect sensors, the core innovation lies in dramatically reducing costs while retaining functional accuracy, as millimeter-level precision is unnecessary for workplace navigation. System performance will be validated to achieve a distance estimation error of approximately 5-10 mm; its accuracy is anticipated to match that of comparable stereo vision approaches.

کلیدواژه‌ها English

Low-cost

Blind Individuals

Workstation Assistance

Object Detection

Audio Guidance

Pre-trained Models

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