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Review On UrbanVision AI


EOI: 10.11242/viva-tech.01.08.027

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Citation

Suruchi Sawant, Khushbu Pasi, Madhu Thakur, Akshata Raut, " Review On UrbanVision AI ", VIVA-IJRI Volume 1, Issue 8, Article 1, pp. 1-9, 2025. Published by Computer Engineering Department, VIVA Institute of Technology, Virar, India.

Abstract

"The increasing incidence of road traffic accidents poses significant challenges to public safety and emergency response efficiency. This paper presents a novel accident alert system utilizing Internet of Things (IoT) technologies. The system integrates various sensors, including accelerometers, gyroscopes, and GPS modules, to monitor vehicular movements in real-time. Upon detecting an abnormal event indicative of an accident, the system automatically triggers alerts to predefined emergency contacts and local authorities, providing real-time location data for rapid response. Additionally, a mobile application interface enables users to manage notifications and access emergency resources. Experimental results demonstrate the system's effectiveness in accurately detecting accidents and significantly reducing response time, thereby enhancing overall road safety. This approach offers a scalable solution for urban and rural environments, contributing to improved emergency management. The Urban Development Planning Tool is a web-based application designed to support urban planners, developers, and city officials in making informed decisions regarding urban development. By utilizing advanced mapping technologies, AI-powered entity detection, and comprehensive analysis tools, the system enables the evaluation of urban areas and offers data-driven recommendations for development. Incorporating OpenStreetMap data, geospatial analysis, and machine learning, the tool provides real-time insights into urban landscapes, assisting stakeholders in optimizing land use, improving infrastructure planning, and promoting sustainable urban growth.As cities expand, the platform also empowers residents to participate in discussions about their local environments. It enables individuals to explore their neighborhoods, identify areas in need of improvement, and engage in meaningful dialogues on potential changes. By creating an interactive mapping experience, users can search for specific locations, view surrounding areas within a 1 km radius, and generate static images to visualize their neighborhood's current state. "

Keywords

AI-driven urban planning, Sustainable city development, Urban area analysis, Data-driven decision-making, Smart cities technology, MERN stack platform.

References

  1. Tsai, B.-S., Huizer, L., Giampaolo, M., Monté, S., Gong, S., Garcia, G., and Agugiaro, G.: Integration of GIS and CAD data to perform interactive preliminary environmental analyses at district scale, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4/W10-2024, 169–176.
  2. Hu, Li. (2023). Research on the Application of Digital Twin in Smart Cities. Advances in Economics, Management and Political Sciences. 42. 14-20.
  3. Sanchez, T.W. Planning on the Verge of AI, or AI on the Verge of Planning. Urban Sci. 2023, 7, 70. ML Updates for OpenStreetMap: Analysis of Research Gaps and Future Directions 28 Jun 2024 21 pages.
  4. Winston Yap , Patrick Janssen .Free and open source urbanism: Software for urban planning practice,Computers, Environment and Urban Systems,Volume 96,2022.
  5. Muhammad Abul Hassan, Farhat Ullah Intelligent Transportation Systems in Smart City: A Systematic Survey 2024
  6. Eshrat E. Alahi , Arsanchai Sukkuea Integration of IoT-Enabled Technologies and Artificial Intelligence (AI) for Smart City Scenario: Recent Advancements and Future Trendsh 2024.
  7. Tan Yigitcanlar ,Juan M. Corchado ,Rashid Mehmood Responsible Urban Innovation with Local Government Artificial Intelligence (AI): A Conceptual Framework and Research Agendagh.
  8. Xhafa, Sonila & Kosovrasti, Albana. (2024). Geographic Information Systems (GIS) in Urban Planning. European Journal of Interdisciplinary Studies.
  9. Arora, Anuja & Jain, Dr & Yadav, Divakar & Hassija, Vikas & Chamola, Vinay & Sikdar, Biplab. (2023). Next Generation of Multi-Agent Driven Smart City Applications and Research Paradigms. PP. 1-1.
  10. Wolniak, Radosław & Stecuła, Kinga. (2024). Artificial Intelligence in Smart Cities—Applications, Barriers, and Future Directions: A Review. Smart Cities. 7.
  11. Ortega-Fernández, A.; Martín-Rojas, R.; García-Morales, V.J. Artificial Intelligence in the Urban Environment: Smart Cities as Models for Developing Innovation and Sustainability. Sustainability 2024, 12, 7860.
  12. Mandourah, Ammar, and Hartwig H. Hochmair. "Analysing the use of OpenAerialMap images for OpenStreetMap edits." Geo-spatial Information Science (2024): 1-16.
  13. Amati, Marco, Quentin Stevens, and Salvador Rueda. "Taking play seriously in urban design: the evolution of Barcelona’s Superblocks." Space and Culture 27.2 (2024): 156-171.
  14. Cugurullo, Federico, et al. "The rise of AI urbanism in post-smart cities: A critical commentary on urban artificial intelligence." Urban Studies 61.6 (2024): 1168-1182.