چکیده مقاله
Today's rapid urban expansion generates immense pressure, creating problems like gridlock, excessive power use, and serious pollution Honestly, the old methods city halls use simply cannot handle the huge, varied data stream coming off sensors and IoT tools in real time This paper tackles this gap head on We performed a systematic review, drawing on twenty seven high quality papers 2018–2025 , to precisely identify AI and ML successes in six key areas: from predicting traffic and optimizing power grids, to smart waste and water management We found that advanced methods like Graph Neural Networks GNNs and Deep Reinforcement Learning do outperform old techniques However, the technology’s promise is still being limited by systemic issues Barriers include: big questions about privacy, models failing to generalize across different cities, evident algorithmic bias, and weak regulatory frameworks In short, achieving truly livable smart cities demands we stop focusing only on the tech and start fixing the governance, ethics, and policy alignment
کلیدواژهها
نویسندگان
Sara Alipour
Department of Computer Engineering West Tehran Branch, Islamic Azad University Tehran, Iran
Azita Shirazipour
Department of Computer West Tehran Branch, Islamic Azad University Tehran, Iran
شیوه ارجاع
Alipour, Sara and Shirazipour, Azita,1404,Applications of Artificial Intelligence and Machine Learning in Smart Cities: A Review,1st International Conference on Management, Computer Science, and Artificial Intelligence,Tehran
ارائهشده در
مجموعه مقالات چهارمین کنفرانس بین المللی دانشجویان جغرافیا و علوم زمین ایران29 بهمن 1404 · تهران