معماری و شهرسازی آرمان شهر

معماری و شهرسازی آرمان شهر

نقش هوش ترکیبی در طراحی شهری و هدایت شهرهای هوشمند، مورد مطالعاتی: خیابان نیاوران

نوع مقاله : مقاله پژوهشی

نویسندگان
1 کارشناسی ارشد طراحی شهری، دانشکده هنر و معماری، دانشگاه تربیت مدرس، تهران، ایران.
2 استادیار گروه شهرسازی، دانشکده هنر و معماری، دانشگاه تربیت مدرس، تهران، ایران (نویسنده مسئول).
3 استاد گروه معماری، دانشکده هنر و معماری، دانشگاه تربیت مدرس، تهران، ایران.
10.22034/aaud.2024.464237.2894
چکیده
امروزه ابزارهای هوشمند (هوش مصنوعی) هدایت‌کننده اصلی شهرهای هوشمند هستند. آن‌ها تسهیل‌کننده روندهای پیچیده طراحی و سرعت‌بخش جریانات شهرهای امروزی هستند؛ اما مشکل اساسی استفاده از هوش مصنوعی در فرآیندهای طراحی، عدم حداکثر استفاده از ظرفیت‌های هوش جمعی است امروزه فقدان بهره‌مندی از ظرفیت‌های هوش جمعی یکی از کمبودهای اساسی در زمینه طراحی شهری است.«هوش جمعی به ظرفیت و توانایی ترکیبی یک گروه یا یک تیم برای انجام طیف گسترده‌ای از وظایف و حل مشکلات مختلف اشاره دارد». با توجه ‌به این تعریف آیا می‌توان بدون استفاده از ظرفیت‌های هوش جمعی و بازخوردهای مناسب شهروندان، فضاهای شهری مناسبی را طراحی کرد. حضور و مشارکت شهروندان (خرد جمعی) در فرآیند طراحی با استفاده از هوش مصنوعی الزامی است چراکه آنان صاحبان اصلی فضاهای شهری هستند. هدف اصلی این پژوهش استفاده از هوش جمعی و تجربیات واقعی شهروندان در طراحی خیابان نیاوران است. همچنین استفاده از روش‌های نوین هوش مصنوعی در جمع‌آوری و تجزیه‌وتحلیل داده‌ها یکی دیگر از اهداف این پژوهش کمی به‌شمار می‌آید. ما 107 نفر از شهروندان را به یک آزمایش واقعی در خیابان نیاوران دعوت کردیم. داده‌های پژوهش همان داده‌های مکانی (طول و عرض جغرافیایی) افراد از حضور و گردش در خیابان هستند که به‌وسیله یک اپلیکیشن ردیاب (Geo-Tracker) طراحی شده توسط پژوهشگر جمع‌آوری شده‌اند. سپس داده‌ها در قالب یک فایل JSON کدنویسی شدند. با واردکردن این داده‌های پردازش‌شده در قسمت کدنویسی یک سایت هوش مصنوعی به نام (Geojason) مسیرهای طی‌شده توسط افراد روی نقشه سایت ترسیم می‌شوند. با قرارگیری این مسیرها بر روی یکدیگر، بررسی و شناخت محدوده‌هایی از خیابان که همپوشانی و گره مسیرها در آن نقاط بیش‌تر دیده شدند، صورت پذیرفت. نتیجه آن شد که این نقاط بیش‌تر موردتوجه شرکت‌کنندگان پژوهش قرار گرفته است.
کلیدواژه‌ها

عنوان مقاله English

Role of Collective Intelligence (CI) in Urban Designs and Leading Smart Cities; Case Study: Niyavaran St.

نویسندگان English

Sara Sadeghi 1
Ali Safavi 2
Mohammad Javad Mahdavinejad 3
1 M.A. in Urban Design, Faculty of Art and Architecture, Tarbiat Modares University, Tehran, Iran.
2 Assistant Professor of Urban Planning, Faculty of Art and Architecture, Tarbiat Modares University, Tehran, Iran (Corresponding Author).
3 Professor of Architecture, Faculty of Art and Architecture, Tarbiat Modares University, Tehran, Iran.
چکیده English

Today, smart tools, i.e., artificial intelligence-powered tools are the main drivers of smart cities, facilitating complex design processes and expediting modern urban traffic. The main problem, however, with using Artificial Intelligence (AI) in design processes would be the failure to use capacities of Collective Intelligence (CI), which remains one of the main shortfalls in urban design. Collective intelligence refers to the “shared capacities and potentials of a group or a team to perform a wide range of tasks and solve various problems”  (Chikersal, 2017). The question is whether or not appropriate urban spaces could be designed without using the capacities of collective intelligence and appropriate citizen feedback. Meanwhile, citizens (collective intelligence) need to collaborate and engage in collective intelligence-based design processes because they are the main owners of urban spaces. The main objective of this study was to use collective intelligence and citizens’ actual experiences in designing Niyavaran Street in Tehran. Also, using other modern artificial intelligence-based techniques in collecting and analyzing data was another objective of this quantitative study. To this end, we invited 107 citizens to a real experiment on the street. Study data included the location data (geographical longitudes and latitudes) of the subjects’ presence and walking on the street, collected by a tracker application, called Geo-Tracker, designed by the researcher. The data were then coded into a JSON file. As the processed data were entered into the coding section of an artificial intelligence site, dubbed Geojason, the paths covered by people were drawn on the site’s map. As the paths were overlaid on each other, we could examine and identify the areas of the street where path nodes and their overlaps were most noticeable. It was concluded that these points finally attracted the attention of the study subjects the most.

کلیدواژه‌ها English

Collective Intelligence
Hybrid Intelligence
Digitalism
Niyavaran Street
Machine Learning
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دوره 17، شماره 49
زمستان 1403
صفحه 143-158

  • تاریخ دریافت 02 تیر 1403
  • تاریخ بازنگری 12 آبان 1403
  • تاریخ پذیرش 20 آبان 1403