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Smart Cities Ahead: Policy and Regulatory Strategies for Machine Learning and Robotics in Urban Development
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Author(s): Sahil Lal (Galgotias University, Greater Noida, India), Kittisak Wongmahesak (North Bangkok University, Thailand), Manmeet Kaur Arora (Sharda University, India), Christian Kaunert (Dublin City University, Ireland)and Bhupinder Singh (Sharda University, India)
Copyright: 2025
Pages: 20
Source title:
Machine Learning and Robotics in Urban Planning and Management
Source Author(s)/Editor(s): Kamalesh Ravesangar (Tunku Abdul Rahman University of Management and Technology, Malaysia), Christian Kaunert (Dublin City University, Ireland & University of South Wales, UK), Bhupinder Singh (Sharda University, India), Sahil Lal (Galgotias University, Greater Noida, India)and Manmeet Kaur Arora (Sharda University, India)
DOI: 10.4018/979-8-3693-9410-6.ch009
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Abstract
This chapter examines how machine learning (ML) algorithms and robotics could help redesign cities for a future through policies and regulatory approaches. With rapid urbanization, environmental sustainability, and resource constraints emerging as pressing challenges for cities, the adoption of technology-enabled solutions can significantly improve the management of urbanization, resulting in an improved quality of life in cities. The chapter surveys existing policies on smart city initiatives, analyses regulatory challenges around data privacy and algorithmic bias, and compares approaches to smart city governance across countries. If properly implemented, ML and robotics can contribute to effective allocation of resources, service delivery and citizen engagement, as illustrated with successful case studies. It also sheds light on the lessons learned from failed initiatives, pointing to the importance of inclusive policymaking and strong data governance frameworks.
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