AI-based Surveillance for Environment Management at Civil Construction Sites: A Case Study of Delhi State

Abstract

The rapid pace of urban development and infrastructure projects in Delhi has highlighted the environmental concerns associated with civil construction activities, including air pollution, noise pollution, waste mismanagement and unsafe construction practices. The existing construction site environment monitoring methods are generally inefficient, due to manual supervision and non-real-time reporting. This paper proposes a new surveillance system for environmental management in Civil Construction Sites in Delhi using an Artificial Intelligence (AI) based system. The research is mixed methods; this study relied on secondary data from governmental environmental reports and published academic literature, regulatory documents and existing case studies on AI technologies and construction site management. This research analyzes the application of Artificial Intelligence (AI) technologies such as machine learning (ML), computer vision, drones, smart sensors and Internet of Things (IoT) for improving environmental monitoring and compliance. The findings show that the AI-based surveillance system is good in real-time monitoring of dust emissions, noise and waste disposal in the construction site. The technology also enables predictive analysis, minimisation of human error, operational efficiency and assists regulatory bodies in enforcing environmental regulations. High implementation cost, lack of technical expertise and data privacy concerns remain significant challenges to the widespread application. The study concludes that the AI-based surveillance systems can help a lot in the sustainable management of the environment in construction sites by reducing pollution, auto supervised environmental compliance, and automatic environmental compensation charges in case of non-compliance. The concept requires significant investment, more regulatory support and greater cooperation between the State Pollution Control Board and construction agencies to be well implemented.