Affiliation:
1. CMR Institute of Technology, India
2. NSB Academy, India
3. Faculty of Computers and Information, Mansoura University, Egypt
Abstract
In many developing counties, urban slums pose significant challenges to residents and authorities alike. The lack of accurate, up-to-date information on slum settlements hampers effective urban planning and slum upgrading initiatives. This chapter explores the potential of artificial intelligence (AI) coupled with drone technology in mapping and analysing slum areas for the purpose of informing and supporting slum upgrading programs. By leveraging AI algorithms for image processing and analysis, coupled with high-resolution aerial imagery captured by drones, this approach offers a cost-effective and efficient method for mapping slum areas, identifying key features, and prioritizing interventions. The chapter discusses the technical aspects, challenges, and opportunities associated with AI-based slum mapping, along with case studies done by selecting 10 slums in Bangalore and recommended government and local corporation to implement the schemes of government as early as possible to see the practical applications to demonstrate its effectiveness in supporting slum upgrading efforts.
Reference20 articles.
1. The ‘Environmentalism of the Poor’ revisited: Territory and place in disconnected glocal struggles
2. AntonyM.MaheshwaranG. (2001). Social Segregation and Slums – The Plight of Dalits in the slums of Delhi. Indian Social Institute.
3. Bakshi, D. (1987). Socio Economic fesilities to Slum Dwellers. Council for Social Development.
4. Spatial dimension of social exclusion. An imperial investigation into the relationship of housing and social exclusion in the slums of Dhaka;H.Begum;Management Research and Practice,2010
5. Recounting the poor – Poverty in India (1983 – 1999);S. S.Bhalla;Economic and Political Weekly,2003