Development of a Smart and Sustainable Rating System Platform for Saudi Neighborhoods

Cities around the world are facing growing challenges related to climate change, urban sprawl, infrastructure strain, and digital transformation. In response, smart and sustainable urban development has become a global focus, aiming to integrate technology and environmental stewardship to improve the quality of life. The smart and sustainable city concept is typically applied at the city scale; however, its impact is most tangible at the neighborhood level, where residents interact directly with infrastructure, services, and community spaces. A variety of global frameworks have been developed to assess sustainability and technological integration. However, these models often fall short in addressing localized needs, particularly in regions with distinct environmental and cultural contexts. In Saudi Arabia, Vision 2030 emphasizes livability, sustainability, and digital transformation, yet there remains a lack of tailored tools to evaluate smart and sustainable progress at the neighborhood scale. This study develops HayyScore, a localized evaluation framework and prototype digital platform developed to assess neighborhood performance across five core categories: (i) Environment and Urban Resilience, (ii) Smart Infrastructure and Governance, (iii) Mobility and Accessibility, (iv) Quality of Life and Social Inclusion, and (v) Economy and Innovation. The HayyScore platform operationalizes this framework through an interactive web-based tool that allows users to input data through structured forms, calculate scores, receive category-based and overall certification levels, and view results through visual dashboards. The methodology involved a comprehensive review of global frameworks, expert input to define localized indicators, and iterative prototyping of the platform using Python 3.13.5 and Streamlit 1.45.1. To demonstrate its practical application, the prototype was tested on two Saudi neighborhoods: King Abdullah Petroleum Studies and Research Center (KAPSARC) and King Fahd University of Petroleum and Minerals (KFUPM). Key platform features include automated scoring logic, category weighting, certification generation, dynamic performance charts, and a rankings page for comparing multiple neighborhoods. The platform is designed to be scalable, with the ability to add new indicators, support multilingual access, and integrate with real-time data systems in future iterations.